U.S. Department of Commerce Volume 102 Number 1 January 2004 Fishery Bulletin U.S. Department of Commerce Donaid L. Evans Secretary National Oceanic and Atmospheric Administration Vice Admiral Conrad C. Lautenbacher Jr., USN (ret.) Under Secretary for Oceans and Atmosphere National Marine Fisheries Service William T. Hogarth Assistant Administrator for Fisheries .^TOFCo. X K 1 ^ / The Fishery' Bulletin (ISSN 0090-0656) is published quarterly by the Scientific Publications Office, National Marine Fish- N( >AA, 7600 Sand Point Way NE, BIN C15700, Seattle. WA 981 15-0070. Periodicals postage is paid at Seattle, WA, and at additional mailing offices. POST- MASTER: Send address changes for sub- scription- to Fishery Bulletin. Superin- tendent of Documents, Attn.: Chief. .Mail List Branch, Mail Stop SSOM, Washing- ton. DC 20402-9373. Although the contents of this publica- tion have not been copyrighted and may be reprinted entirely, reference to source is appreciated. The Set if Commerce has deter- mined that the publication of tin ording to law for the transaction of public business of this Department. Use of funds for printing of nodical has been approved by the oroftheOffii cement and Budget. For sale by the Superintendent of nuts. US. Government Printing I mice, Washington, DC 20402. Subscrip- tion pi i it: $55.00 domestic and $68.75 foreign. Cost per single issue: $28.00 dome ,5.00 foreign. See back for order form. Scientific Editor Dr. Norman Bartoo Associate Editor Sarah Shoffler National Marine Fisheries Service, NOAA 8604 La Jolla Shores Drive La Jolla, California 92037 Managing Editor Sharyn Matriotti National Marine Fisheries Service Scientific Publications Office 7600 Sand Point Way NE, BIN C15700 Seattle, Washington 981 15-0070 Editorial Committee Dr. Harlyn O. Halvorson Dr. Ronald W. Hardy Dr. Richard D. Methot Dr. Theodore W. Pietsch Dr. Joseph E. Powers Dr. Harald Rosenthal Dr. Fredric M. Serchuk Dr. George Watters University of Massachusetts, Boston University of Idaho, Hagerman National Marine Fisheries Service University of Washington, Seattle National Marine Fisheries Service Universitat Kiel, Germany National Marine Fisheries Service National Marine Fisheries Service Fishery Bulletin web site: www.fishbull.noaa.gov The Fishery Bulletin carries original research reports and technical notes on investigations in fishery scien ring, and economics. It began as the Bulletin of the United States Pish Commission in 1881; it became the Bulletin of the Bureau of Fisheries in 1904 and the Fishery Bulletin of the Fish and Wildlife Service in 1941. Separates were issued as documents tl volume 46; the last document was No. 1103. Beginning with volume 47 in 1931 and continuing through volume 62 in 196.1 ired as a numbered bulletin. A new system began in 1963 with volume 6:3 in which papers are bound together in a single issue of the bulletin. Beginning with volume 70. number 1. January 1972, the Fishery Bulletin became a lieal, issued quarterly. In this form, it is available by subscription from the Superintendent of Documents. U.S. Government Printing Office, Washington, DC 20402. It is also available free in limited numbers to libl irch institutions. State and Federal agencies, and in exi for other scientific publications. U.S. Department of Commerce Seattle, Washington Volume 102 Number 1 January 2004 Fishery Bulletin Contents ary MAR 5 2004 The conclusions and opinions expressed in Fisher)' Bulletin are solely those of the authors and do not represent the official position of the National Marine Fisher- ies Service (NOAA) or any other agency or institution. The National Marine Fisheries Service (NMFS) does not approve, recommend, or endorse any proprietary product or pro- prietary material mentioned in this pub- lication. No reference shall be made to NMFS. or to this publication furnished by NMFS, in any advertising or sales pro- motion which would indicate or imply that NMFS approves, recommends, or endorses any proprietary product or pro- prietary material mentioned herein, or which has as its purpose an intent to cause directly or indirectly the advertised product to be used or purchased because of this NMFS publication. Articles 1-13 Alonzo, Suzanne H., and Marc Mangel The effects of size-selective fisheries on the stock dynamics of and sperm limitation in sex-changing fish 14-24 Baba, Katsuhisa, Toshifumi Kawajiri, Yasuhiro Kuwahara, and Shigeru Nakao An environmentally based growth model that uses finite difference calculus with maximum likelihood method: its application to the brackish water bivalve Corbicula /aponica in Lake Abashiri, Japan 25-46 Brodeur, Rick D., Joseph P. Fisher, David J. Teel, Robert L. Emmett, Edmundo Casillas, and Todd W. Miller Juvenile salmomd distribution, growth, condition, origin, and environmental and species associations in the Northern California Current 47-62 Garcia-Rodrfguez, Francisco J., and David Aurioles-Gamboa Spatial and temporal variation in the diet of the California sea lion (Zalophus californianus) in the Gulf of California, Mexico 63-77 Jung, Sukgeun, and Edward D. Houde Recruitment and spawning-stock biomass distribution of bay anchovy (Anchoa mitchilli) in Chesapeake Bay 78-93 Kellison, Todd G., and David B. Eggleston Coupling ecology and economy: modeling optimal release scenarios for summer flounder (Paralichthys dentatus) stock enhancement 94-107 Kritzer, Jacob P. Sex-specific growth and mortality, spawning season, and female maturation of the stripey bass (Lut/anus carponotatus) on the Great Barrrier Reef Fishery Bulletin 102(1) 108-117 Orr, Anthony J., Adria S. Banks, Steve Mellman, Harriet R. Huber, Robert L. DeLong, and Robin F. Brown Examination of the foraging habits of Pacific harbor seal (Phoca vitulina richardsi) to describe their use of the Umpqua River, Oregon, and their predation on salmonids Companion paper with Purcell et al., see "Notes" below. 118-126 Park, Wongyu, R. Ian Perry, and Sung Yun Hong Larval development of the sidestriped shrimp (Pandalopsis dispar Rathbun) (Crustacea, Decapoda, Pandahdae) reared in the laboratory 127-141 Pearson, Donald E., and Franklin R. Shaw Sources of age determination errors for sablefish (Anop/opoma fimbria) 142-155 Powell, Allyn B., Robin T. Cheshire, Elisabeth H. Laban, James Colvocoresses, Patrick O Donnell, and Marie Davidian Growth, mortality, and hatchdate distributions of larval and juvenile spotted seatrout (Cynoscion nebulosus) in Florida Bay, Everglades National Park 156-167 Santana, Francisco M., and Rosangela Lessa Age determination and growth of the night shark (Carcharhinus signatus) off the northeastern Brazilian coast 168-178 Smith, Keith R„ David A. Somerton, Mei-Sun Yang, and Daniel G. Nichol Distribution and biology of prowfish (Zaprora silenus) in the northeast Pacific 179-195 Ward, Peter, Ransom A. Myers, and Wade Blanchard Fish lost at sea: the effect of soak time on pelagic longlme catches 196-206 Watanabe, Chikako, and Akihiko Yatsu Effects of density-dependence and sea surface temperature on interannual variation in length-at-age of chub mackerel (Scomber japonicus) in the Kuroshio-Oyashio area during 1970-1997 Notes 207-212 Llanos-Rivera, Alejandra, and Leonardo R. Castro Latitudinal and seasonal egg-size variation of the anchoveta (Engrauhs nngens) off the Chilean coast 213-220 Purcell, Maureen, Greg Mackey, Eric LaHood, Harriet Huber, and Linda Park Molecular methods for the genetic identification of salmonid prey from Pacific harbor seal (.Phoca vitulina richardsi) scat Companion paper with Orr et al., see "Articles" above. 221-229 Weng, Kevin C, and Barbara A. Block Diel vertical migration of the bigeye thresher shark (Alopias superciliosus), a species possessing orbital retia mirabilia 231 Subscription form Abstract— Fisheries models have tradi- tionally focused on patterns of growth, fecundity, and survival offish. However, reproductive rates are the outcome of a variety of interconnected factors such as life-history strategies, mating patterns, population sex ratio, social interactions, and individual fecundity and fertility. Behaviorally appropriate models are necessary to understand stock dynamics and predict the success of management strategies. Protogynous sex-changing fish present a challenge for management because size-selective fisheries can drastically reduce repro- ductive rates. We present a general framework using an individual-based simulation model to determine the effect, of life-history pattern, sperm production, mating system, and man- agement strategy on stock dynamics. We apply this general approach to the specific question of how size-selective fisheries that remove mainly males will impact the stock dynamics of a protogynous population with fixed sex change compared to an otherwise identical dioecious population. In this dioecious population, we kept all aspects of the stock constant except for the pattern of sex determination (i.e. whether the species changes sex or is dioecious). Protogynous stocks with fixed sex change are predicted to be very sensitive to the size-selective fishing pattern. If all male size classes are fished, protogynous populations are predicted to crash even at relatively low fishing mortality. When some male size classes escape fishing, we predict that the mean population size of sex-chang- ing stocks will decrease proportionally less than the mean population size of dioecious species experiencing the same fishing mortality. For protogynous spe- cies, spawning-per-recruit measures that ignore fertilization rates are not good indicators of the impact of fishing on the population. Decreased mating aggregation size is predicted to lead to an increased effect of sperm limitation at constant fishing mortality and effort. Marine protected areas have the poten- tial to mitigate some effects of fishing on sperm limitation in sex-changing populations. Manuscript approved for publication 23 July 2003 by Scientific Editor. Manuscript received 20 October 2003 at NMFS Scientific Publications Office. Fish. Bull 102:1-13(2004). The effects of size-selective fisheries on the stock dynamics of and sperm limitation in sex-changing fish Suzanne H. Aionzo Institute of Marine Sciences and the Center lor Stock Assessment Research (CSTAR) University of California Santa Cruz 1156 High Street Santa Cruz, California 95064 E-mail address shalonzoiS'ucscedu Marc Mangel Department of Applied Mathematics and Statistics Jack Baskin School of Engineering and the Center for Stock Assessment Research (CSTAR) University of California Santa Cruz 1156 High Street Santa Cruz, California 95064 Fisheries models are generally used to predict the impact of fishing on stock dynamics and yield (Quinn and Deriso, 1999; Haddon, 2001). Classic models have focused mainly on growth, fecundity, and survival of species, with- out considering the impact of mating patterns on reproduction, survival, and recruitment. It is now recognized that life-history strategies and mating behavior will affect stock dynamics. Even so, general quantitative predic- tions regarding the effect of specific life-history patterns on fished popula- tions are limited and further theory is needed (Levin and Grimes. 2002). It is likely that management strategies taking into account a species' reproduc- tive behavior will greatly improve our ability to manage stocks (e.g. Beets and Friedlander, 1999). We would also like to know when the mating behavior and reproductive strategies of a stock will be worth investigating and when tradi- tional management techniques will be sufficient. For example, in a manage- ment context, how do sex-changing stocks differ from separate-sex species? Here, we take an initial step toward generating a theory of the combined effect of life history and mating pat- terns on stock dynamics by focusing on the potential for and effect of sperm limitation in a protogynous (female to male) sex-changing stock. We focus on protogyny for this article because numerous protogynous species are com- mercially important, namely red porgy {Pagrus pagrus), gag grouper iMyc- teroperca microlepis), and California sheephead iSemicossyphus pulcher). Sex-changing fish present a unique challenge for management because size- selective fisheries have the potential to drastically reduce reproductive rates and population size at levels of fishing that would not pose a problem for dioe- cious (separate-sex) species (Huntsman and Schaaf, 1994; Armsworth, 2001; Fu et al., 2001). On the other hand, pro- togynous stocks may be less sensitive to the removal of large individuals if females are not fished and fertilization rates remain high. Many commercially important species are known to change sex (Bannerot et al., 1987; Shapiro, 1987; Coleman et al., 1996; Brule et al., 1999; Adams et al., 2000; Armsworth, 2001; Fu et al., 2001). Previous models have shown that sex-changing fish may be vulnerable to fishing (Bannerot et al., 1987; Huntsman and Schaaf, 1994; Armsworth, 2001; Fu et al.. 2001). Complications arise because the ef- fect of fishing on a sex-changing spe- cies is mediated by many aspects of their reproductive biology, such as sex ratio, size-dependent fecundity, spawn- ing aggregation size, and reproductive skew. Furthermore, patterns of sex change have cascading effects on the sex ratio, social interactions, population Fishery Bulletin 102(1) fecundity, and male sperm production — all of which can affect stock dynamics. Thus, we cannot treat sex change as an isolated aspect of a species. Instead, we must consider sex change within the context of the mating system and the life history of the species to make general predictions. Behaviorally appropriate models are required to gener- ate constructive qualitative and quantitative theory. Past theory has indicated that sex-changing populations exhibit stock dynamics that often differ from those of dioecious populations (Bannerot et al., 1987; Huntsman and Schaaf, 1994; Armsworth, 2001; Fu et al, 2001 ). Furthermore, pro- togynous stocks are predicted to be sensitive to fishing pat- tern and may exhibit nonlinear dynamics that could lead to population crashes (Armsworth, 2001). However, it is not known which aspects of the mating behavior and life his- tory pattern of sex-changing stocks drive these differences. Here we focus on comparing a protogynous stock with an otherwise identical dioecious population to determine the effect of mating aggregation size, fertilization rates, and life history pattern on stock dynamics. Size-selective (or age-selective) fisheries can impact a species through a decrease in spawning stock biomass, in general and through the removal of highly fecund larger and older individuals, in particular (Sadovy, 2001). How- ever, in protogynous species, fisheries that preferentially remove large males can also change the population sex ratio; however, the exact effect of fishing pressure on stock dynamics in a protogynous species is complex. At one extreme, the complete removal of males from the popula- tion would cause a stock to crash, potentially making sex- changing species more vulnerable than dioecious species in the face of high fishing pressures. At the other extreme, sex-changing species may be less affected by size-selective fisheries if female fecundity limits recruitment and males are not removed in such numbers as to reduce mating or fertilization rates. Currently, there is no theory that predicts the potential for sperm limitation in protogynous stocks as a function of gamete production, fertilization rates, and mating pattern. It has been suggested that marine reserves may be a vi- able management option for species where highly fecund older individuals are critical to reproduction (Levin and Grimes, 2002). However, no theory exists that can predict the impact of marine reserves on stock dynamics in sex- changing species. We consider the impact of a no-take marine reserve on the stock dynamics. We compare the effect of setting aside 0-30% of the spawning population in a reserve. We assume that larval production is exported from within the reserve to the rest of the population and determine whether the reserve can mediate some of the ef- fects of fishing outside the reserve because this represents the optimal scenario for marine reserves. We also compare mean catch rates in the presence and absence of a reserve as a function of fishing mortality. Spawning-per-recruit (SPR) measures are often used to estimate the impact of fishing on a stock (Parkes, 2000; Jennings et al., 2001). Ideally, a spawning-per-recruit mea- sure would keep track of per-recruit production of larvae or eggs (Jennings et al., 2001). However, spawning stock biomass per recruit (SSBR) is commonly used to estimate the reproductive output per recruit at different intensities of fishing. One assumes that the biomass of mature fish is linearly related to reproductive output, which may be the case when egg production limits biomass and fecundity in- creases linearly with biomass. In protogynous stocks, over- fishing of males alone may decrease fertilization rates and hence reproductive output without affecting either female biomass or egg production. Thus, in protogynous stocks or sex-selective fisheries, classic measures of spawning per re- cruit may misrepresent the impact of fishing on the stock's reproduction and hence population stability (Punt et al., 1993). We examine a variety of per-recruit measures and determine their ability to predict changes due to exploita- tion in mean population size. In this study, we describe a general approach using sex- and size-dependent individual-based simulation models that predict reproduction, size distribution, and sex ratio in fished populations as a function of mating system and sex-change pattern. We examine the case where sex change occurs at a specific size threshold. We recognize that plastic and socially mediated sex-change patterns have been ob- served, and our results will apply only to species with fixed sex change. We explore the impact of mating aggregation size, sperm production, and asymptotic fertilization rates on the predicted stock dynamics in the presence of exploita- tion. We make predictions regarding the effects of fishing on population size, reproduction, sex ratio, size distribu- tion, and fertilization rates. We also compare our results to previous work and discuss future directions. Methods We used an individual-based simulation to predict the size distribution, individual and population fecundity, popula- tion sex ratio, fertilization rate, and population size as a function of fishing mortality (Fig. 1). Individuals vary in age, size, sex, and mating site. Population size varies as a function of baseline survival, fishing mortality, reproduc- tion, and larval recruitment. Reproduction depends on the pattern of sex change, mating system, sex ratio, mating site, and fecundity (or fertility) of individual males and females. For each annual time period, we determined individual survival, the size and age of these individuals in the next time period, and the total production of surviving offspring by those individuals. Initial analyses showed that a station- ary size, sex, and age distribution is found within approxi- mately 50 time periods and is independent of the initial population conditions. Thus, we simulated 100 time periods prior to examining the impact of fishing on stock dynamics to ensure that the population had already reached the sta- tionary size and sex distribution for that scenario and set of parameters. We then examined the model for 100 repro- ductive seasons in the presence of fishing with a constant mean fishing mortality. Because a number of elements of the model were stochastic, we examined 20 simulations for each scenario and set of parameter values. Initial analyses indicated that 20 simulations were more than sufficient to lead to low variability in the key measures of interest. We assumed that reproduction occurs at the level of the mating Alonzo and Mangel: The effects of size-selective fisheries on the stock dynamics of and sperm limitation in sex-changing fish 3 group at different reproductive sites. Individual sur- vival, maturation, sex change, and mating site were determined stochastically as described below. Fishing and adult survival We assumed that adult survival is density indepen- dent but depends on fishing selectivity, fishing mor- tality, and baseline adult mortality in the absence of fishing. For simplicity, we assumed that age and size do not affect nonfishing adult mortality p. A . We assumed that the fishery is size selective; we let L represent fish size, F represent annual fishing mortality, L f represent the size at which there is 50% chance an individual of that size will be taken, and r represent the steepness of the selectivity pattern. Then fishing selectivity per size class siL) is given by siD- l + exp-HL-L,)) and adult annual survival becomes cr(L) = exp(-/i A -Fs(L)) (1) (2) We assumed that fishing does not differentially affect the sexes independent of size. We recognize, however, that for some species this may not be the case. We also assumed that fishing occurs each year prior to reproduction and can represent either pulse or continuous fishing with an annual mortality F. We let N it) represent the number of individuals in age class a at time t so that population size N(t)= S a N a (t). Population dynamics We assumed that the number of larvae that enter the popu- lation is determined by the production of fertilized eggs Pit) and the probability that those larvae will survive to recruit. Pit) is determined by the adult fecundity and fertilization rates described below. For computational tractability, we also assumed that a population ceiling N max exists (Mangel and Tier, 1993, 1994 ). However, we chose N mBX large enough that the stable population size was below the ceiling. Larval survival has both density-independent and density-depen- dent components (e.g. Cowen et al., 2000; Sale, 2002). We used a Beverton-Holt recruitment function to determine larval survival to the next age class (Quinn and Deriso, 1999; Jennings et al., 2001). Larvae represented the zero- age class N (t) and thus the number of larvae surviving to recruit in any year t is given by N n it) = (oPit))/(l+pPit)) if (ctP(t))/(l+pP(t)) +J j Njt)exp(-A). (4) Mating system We assumed that reproduction occurs at the level of the mating group, and we examined the effect of varying mating group size and the number of mating sites. We assumed Fishery Bulletin 102(1) that juveniles and adults exhibit site fidelity but that larvae settle randomly among mating sites. We also assumed that the population carrying capacity is split equally among the mating sites and that the total capacity of all mating sites exceeds the maximum population size in the absence of fish- ing as determined by adult mortality and the recruitment function. Therefore, mating sites do not limit recruitment but may affect reproductive rates. We examined three cases: 1 ) the entire population mates at one site (one mating site with up to 1000 individuals); 2) a few large mating groups exist ( 10 sites with a maximum of 100 individuals per site); and 3) many small mating aggregations exist (20 mating sites with a maximum of 50 individuals per site). For sim- plicity, we assumed that within a mating site, individuals mate in proportion to their fertility and fecundity. Therefore, large males and females have higher expected reproductive success. However, we assumed that all males that are large enough to change sex have a chance of reproducing propor- tional to their fertility. This is equivalent to assuming that females exhibit a mate choice threshold I Janetos, 1980) that has evolved with the size-at-sex change and that females have an equal probability of mating with males above this size threshold. However, a large male mating advantage clearly still exists. We also assumed that fishing mortality remains constant as mating aggregation size varies. Thus, we assumed that fishing effort per site does not increase as the number of mating sites decreases. An alternative would be to assume that total fishing mortality increases as the number of mating aggregations decreases. Maturity The probability that an individual matures p m (L) is deter- mined by size. Once an individual matures, she remains female until sex change (see below). We let L m represent the length at which 50% of the individuals will have matured. EiL)=aL h , (7) P,JL)- 1 where a and b are constants. Once an individual has changed sex (as determined by the sex change rule described above) sperm production (in millions) S(L) is given by S{L)=cL d , (8) l + exp(-q(L- L m (5) where c and d are constants. Size-dependent fecundity has been measured in many fish species (e.g. Gunderson, 1997). A general allometric relationship between sperm production and size has not been established. Therefore, we assumed that male gamete production increases with size at the same rate as that for females ib=d). We also assumed that males produce many more sperm at any body length than females produce eggs. Clearly, other possible patterns exist. We examined the case where males produce from 10 2 to 10 6 sperm for every egg produced by a female. In the pelagic spawning wrasse (Thalassoma bifasciatum ), large males release ap- proximately 1000 times more sperm than females release eggs (Schultz and Warner, 1991; Warner et al., 1995). We used recently published data on sperm production and fertilization rates in the bluehead wrasse (Thalas- soma bifasciatum) to generate a biologically appropriate fertilization function for our model (Warner et al., 1995; Petersen et al., 2001). It is critical to consider a biologically appropriate form for the function to express fertilization rates when considering the potential for sperm limitation. The probability an egg will be fertilized is an increasing function of the number of sperm available for that mat- ing (Fig. 2). The number of eggs released per mating also affects the fertilization rate (Fig. 2). For simplicity, we cal- culated the average expected fertilization rate per mating site based on the total production of sperm and eggs at the site. We let S represent the number of sperm released (in millions) and £ the number of eggs released at each mating site. We assumed that the proportion of eggs fertilized per mating site p F is given by where q determines the steepness of the probability function. Sex change The probability of sex change, p c iL), is a logistic function of absolute size L P,.(L) = l + exp(-p(L-L, )) (6) where L r represents the size at which 50% of the indi- viduals will change sex from female to male and p is a constant. Reproduction We assumed that female fecundity E(L) depends on indi- vidual size according to the allometric relationship Pf l + iisE + X )S (9) where k and % are constants fitted to the data. The number of eggs fertilized per group is p h -E and the total production of fertilized eggs. Pit), is the sum of the number of eggs fertilized in all mating groups. Measures of spawning stock biomass per recruit To measure the impact of fishing on stock dynamics, we computed the total spawning stock biomass per recruit starting from the beginning of fishing for the next 50 years. We used the generally recognized pattern that fish wet weight tends to be approximately proportional to the cube offish length (Gunderson, 1997) to convert fish length, L, into relative biomass, B(L)~L\ Then we calculated total female and male spawning stock biomass Alonzo and Mangel: The effects of size-selective fisheries on the stock dynamics of and sperm limitation in sex-changing fish per recruit (SSBR). We also kept track of the total fecundity (egg production per recruit I, fertility (sperm production per recruit), and eggs fertilized per recruit. Marine reserves ^=150 (about 60 females) OS- 'S 0.6 ■s 0.4 02 We examined the effect of no-take marine reserves on the predicted stock dynamics by comparing the stock dynamics in the presence and absence of reserves. Without a reserve, individuals at all mating sites are subject to fishing. In the presence of a no-take marine reserve, we "protect" a percentage of the mating sites (and thus the population) from fishing. We examined cases in which 09c, 10%, 20%, and 30% of mating sites were protected from fishing. We assumed that the population is completely open among mating sites. Thus, eggs produced from all mating sites enter one larval pool and recruitment occurs randomly between mating sites. Clearly other possibili- ties exist and could be considered in future analyses, but this case represents a reasonable baseline situation to con- sider because many marine fish have pelagic larval phases. We also recognize that these analyses ignore the effect of interactions between species within the reserve on stock dynamics. We examined two situations. In the first case, reduced fishing effort occurs when mean fishing mortality is decreased in the presence of reserves because fishing mortality (F) at the unprotected sites remains the same as before the reserve. In the second case, the redistribution of fishing effort occurs when mean fishing mortality across all sites remains the same because fishing mortality increases at the unprotected sites. Comparison of sex-changing stocks and dioecious stocks Ideally, we would like to distinguish the effects of sex change in isolation from the confounding effects of mating pattern, sex ratio, survival, growth, and population fecundity on stock dynamics. To differentiate whether sex change in iso- lation or other aspects of the mating system determine the predicted stock dynamics, we also examined a version of the model described above for a population where sex is fixed at birth. In this dioecious population, we keep all aspects of the stock constant except for the pattern of sex determi- nation (whether the species changes sex or is dioecious). One would generally expect a dioecious population with no differences between the sexes in mortality to exhibit a 50:50 sex ratio ( Fisher, 1930; Trivers, 1972; Charnov, 1982 ). However, we wanted to control for all differences between the dioecious and protogynous stocks other than the sex- determination pattern. Therefore, we considered the same sex ratio at maturity (0.67=the proportion of adults that are female) as found in the sex-changing population in the absence of fishing. Assuming no sex-specific differences in survival to maturity, this is the same as assuming a 0.67 sex ratio at birth. In this model, individuals remain one sex (determined randomly at birth) throughout their lifetime. K m =1750 (about 700 females) K>750 (about 300 females) 5.000 10.000 1 5.000 20,000 Sperm number (S) (in millions, about 1 to 100 males) Figure 2 Fertilization rate as a function of the number of eggs and sperm per mating site. The saturation parameter K m =\E+x is taken from Equation 9. Fishing is size but not sex selective. We assumed that males mature at the same size as females. Parameter values We used previous research on California sheephead (Lab- ridae, Semicossyphus pulcher), a commercially important sex-changing fish, to provide evolutionarily and ecologi- cally reasonable parameters for the model. Although the growth, survival, and reproduction of this species have been studied, less is known about the factors that induce sex change and mating behavior. In this species, sex change occurs at approximately 30 cm although the exact pattern varies among populations (Warner, 1975; Cowen, 1990). It is not known whether sex change is fixed or socially medi- ated. Because nothing is known about fertilization rates in the California sheephead, we generated k and y L c ), the general patterns remain the same, but for the same fishing mortality (.F), the effect of fishing on the population is less (Fig. 4). Female biomass does not decrease much with fish- ing mortality when L f =L c even though some females are removed by the fishery because the probability of a female changing sex is the probability of it being fished. Therefore, female loss due to the fishery affects male biomass rather than female biomass in the population. Sperm limitation and production The removal of large males from the population is pre- dicted to cause sperm limitation and decreased fertiliza- tion rates (Fig. 3, A and C), leading to a decrease in mean population size (Fig. 4A). The degree to which the fertiliza- tion rate and thus the population size decreases depends to a great extent on the pattern of sperm production and fertilization. We assumed that only a few males are needed to fertilize the eggs of many females (Fig. 2). We also assumed that per-capita reproduction and recruitment are high even at a low population size (Barrowman and Myers, 2000). Thus, protogynous populations with lower sperm production or fertilization rates would experience greater effects from fishing than predicted in the present study. Similarly, populations with lower production or sur- vival would experience larger decreases in population size even with the same level of sperm limitation and fishing. In general, however, the removal of males alone from a pro- togynous population with a fixed sex change is predicted to cause decreased fertilization rates and lower mean popula- tion size even when the fertilization rate function is asymp- totic and individual male sperm production is high. Mating aggregation size As mating aggregation size decreased and fishing mortality and effort remained constant, the effect of fishing on the pop- Eggs produced 1 1.5 2 Fishing mortality (F) Figure 3 Spawning-per-recruit measures. Results are presented for the sex-changing stock with one mating site when L^= L c and r=l. Means across 20 simulations are given. For details see the general text. ulation increased. As described above, we assumed that fish- ing effort would not be concentrated on the few large mating aggregations and thus increase total fishing mortality. The sex ratio, mean size, mean fecundity, and mean fertility all remained the same across different mating aggregation sizes with constant fishing mortality. However, the mean fertilization rate and number of fertilized eggs per recruit decreased with mating group size ( Fig. 5 ) even though male biomass and SSBR remained the same. Both predicted mean population size and biomass taken decreased as fish- ing mortality increased (Fig. 5). This pattern was generated by sperm limitation in small mating groups. Smaller groups have higher probabilities that sperm production within the group will not be sufficient to fertilize the eggs produced within the mating group. Small mating aggregations may not only be sperm limited but also be male limited and fail to reproduce completely; populations with small group sizes (50 individuals or less) were predicted to become extinct in Fishery Bulletin 102(1) 5-25% of the simulations as fishing mortality (F) increased from to 1. The impact of mating group size on stock dynam- ics is thus predicted to be nonlinear. A threshold mating aggregation size appeared to exist below which sperm limi- tation and reproductive failure become common. Spawning-per-recruit measures For size-selective fishing, the spawning stock biomass per recruit of females is not predicted to decrease significantly with increased fishing mortality as long as some male size classes escape fishing (Lr>L v ). However, male biomass per recruit and sperm production per recruit are both predicted to decrease. Although egg production is not predicted to 900 800 A L,>L C CD n 700 to ^\ L,=L C <= 600 J o 'ra 500 " 3 g- 400 " Q. c 300 " ra | 200 ' \l,, ra £? 300.000 D T3 a a> c > < ° 200.000 CD 100,000 U/< 0.5 1 15 2 2.5 3 Fishing mortality (F) Figure 4 The effect of size-s ilect ive fishing on stock dynamics. We present results for the sex-changing stock with one mating site when r=l. Means across 20 simulations are given. For details see the general text. decrease with increasing size-selective fishing pressure, the number of fertilized eggs is predicted to decrease. When all male size classes are fished iL.>L c ), the stock is predicted to crash and therefore clearly female biomass and egg production are predicted to decrease with fishing mortality. In general, the predicted decrease in mean popu- lation size and reproduction is driven for the most part by decreased sperm production and consequently a reduction in the number of eggs fertilized per recruit. The relation- ships between fishing pressure and the classic spawning- per-recruit measures do not indicate the true effect that fishing is predicted to have on the protogynous population (Fig. 6). When L f >L c , female spawning stock biomass per recruit and eggs produced per recruit showed almost no effect of fishing on the population, even as mean population size decreased. Because of the size-selec- tive fishing pattern, total and male biomass per recruit decreased with fishing mortality and decreasing mean population size. However, male and total biomass per recruit did not reflect the increased effect of fishing on populations with smaller mating aggregations. The production of fertilized eggs per recruit decreased with increased fishing pressure and decreased more sharply for smaller mating aggregations. Only the number of fertilized eggs per recruit could assess the predicted effect of fishing on the protogynous population. Thus, classic SPR measures were predicted to fail in the presence of sperm limitation to assess the impact of fishing on a protogynous stock. Marine reserves and fishery management In the situation considered in this study, the pattern of fishing is more important to stock dynamics than the presence of marine reserves. We assumed a size- selectivity that allowed on average 50% of individuals of sex-changing size to escape the fishing gear. Thus, although the sex ratio does increase (become more female) by 20-40%, all males are not lost from the population (when L f s.L t . and r=l ). If fishing selectivity occurs at a smaller size, then the effects on the popula- tion are predicted to be much greater and the protogy- nous stock would suddenly become more affected than the dioecious population. For example, at L^=25 cm the protogynous stock is predicted to crash whenever F^l. This occurs not because of a reduction in the produc- tion of eggs but rather because of a failure to fertilize the eggs produced by surviving females. When males of all size classes are fished, populations can become male limited and fertilization rates drop drastically. A decrease in the production of fertilized eggs can lead to a decrease in female biomass, but it is the removal of males rather than females that causes this decline. When fishing effort is not redistributed after the formation of a reserve, the impact of fishing on the mean population size and SPR measures is predicted to decrease (e.g. Fig. 7A). However, if fishing effort is redistributed among unprotected areas, the benefit of the reserves to the protogynous stock decreases (Fig. 8A). Protecting some sites allows large males to Alonzo and Mangel: The effects of size-selective fisheries on the stock dynamics of and sperm limitation in sex-changing fish 9 escape fishing and thus increases the pro- duction of fertilized eggs at the population level. However, yield decreased proportion- ally to the percentage of sites protected by the reserve unless fishing effort is redis- tributed among the remaining sites. We as- sumed that fish do not move between sites after the larval stage, and thus larger and older individuals do not leave the reserve and become exposed to fishing. Although this assumption is clearly appropriate for some species, it is important to realize that the dy- namics and predictions would differ for more closed populations or migratory species. For the fishing pattern and biological scenario examined in this study, marine reserves are not predicted to increase biomass available to the fishery (Figs. 7B and 8B). Dynamics of dioecious versus protogynous stocks In the dioecious stock with a single ran- domly mating aggregation, both male and female biomass per recruit and fecundity or fertility per recruit are predicted to decrease as fishing mortality increases ( Fig. 6). Because both egg production and sperm production decrease with increased fishing pressure in the dioecious stock, the number of eggs fertilized per recruit did not differ much from the other SPR measures. Thus, SSBR and eggs per recruit also indicated the impact of fishing on the stock in dioecious stocks with large mating aggregations. The percent drop in population size and fertil- ized egg production is predicted to be much greater in dioecious species and occurred more quickly than in the sex-changing stock because of a reduction in overall population fecundity even in the absence of decreased fertilization rates. However, dioe- cious stocks are predicted to exhibit larger mean population size for the same fishing mortality and to support a larger fishery because of the additional egg production of large fecund females. At very small mating aggregations, sperm limitation is predicted even in the dioecious stock and fertilized eggs per recruit become a better indicator of stock dynamics in the presence of fishing. Dioecious stocks are also predicted to benefit from marine no-take reserves through the protection of large fecund females ( Fig. 7 ). Discussion In this study we developed a general frame- work that examines the consequences to 0.95 0.9 0.85 Egg production (per recruit) Fertilized eggs (per recruit) Mean population size Figure 5 Mating aggregation size affects the response to fishing. Large (one large mating aggregation ) and small ( 10 smaller mating aggregations I situations are compared. Percent change in the presence of fishing (from F=0 to F=l> in egg production per recruit, mean fertilized egg production per recruit, and mean population size are given. Total population fecundity and mean body size are lower for the smaller mating aggregations. PROTOGYNOUS POPULATION 1 1 F=3 Eggs produced F=0 r& S 0.9- 0.8- Eggs fertilized _n .a St' »■" 0.7- a® x o Eggs produced and fertilized DIOECIOUS POPULATION 0.6- 0.5. ft ti * 0.4 F=3 F=0 600 650 700 750 800 850 900 950 Mean population size Figure 6 Spawning-per-recruit (SPR) measures in a protogynous (squares) and dioe- cious (triangles) stock: Mean egg production per recruit (filled) and mean fertilized eggs per recruit (open) are shown for a randomly mating popula- tion with one large mating group. Error bars indicate the standard error of the mean. For the dioecious population, the two SPR measures overlap. 10 Fishery Bulletin 102(1) fisheries management of a behaviorally and evolution- ary reasonable life-history and sex-change pattern. We based our assumptions and parameter values on patterns observed in natural populations that have presumably evolved given the life history tradeoffs and expected repro- ductive success associated with these behaviors. However, we made various assumptions that affect the predicted patterns such as a fixed sex-change pattern, male mating success proportional to sperm production, and a very resil- ient recruitment function. Despite these assumptions, a number of general patterns emerge. Life-history pattern is important but not sufficient to predict stock dynamics In general, we predicted that a protogynous stock with fixed sex change will respond to the same fishing pressure o o ^ fl Q.— ' °> S3, -= cr> X 0) (yi + 7 2 s, <0) and t, = s, - 7i > 0) (s, -/, <0) (7) (8) where t i = dRIRS on the /th day from the first sampling; Yv Yz = coefficients of the equations; and Sj = dRIRL on the /th day from the first sampling. Model estimation Likelihood function The location and scale parameters at the first sampling (o and fe ), the coefficients of Equa- tion 6 (s max , a, and p k ), and the coefficients of Equations 7 and 8 (y-j and y 2 ) are estimated as values that maximize total log-likelihood. The total log-likelihood is evaluated by the adequate probability density function selected in the first step. The log-likelihood functions take the follow- ing forms: Normal distribution log, L„ ormal (a Q ,b„, s max , a j , p k , y v y 2 ) = X2>g* -A r exp[-(Z <7i -a,)/24 2 ] 2nb (9) Largest extreme value distribution s, =s max / 1 + exp 2>a+£a b * (61 where s i = dRIRL on the /th day from the first sampling; s max = potential maximum dRIRL of the animal; a., P k = coefficients of each independent variable; A = categorical variable ( a dummy variable indi- cating animal ages ) that takes the value 1 orO; E kl = the kt\\ environmental factor on the /th day from the first sampling; n A = number of age categories; and n E = number of environmental factors. The categorical variable takes the value of 1 when the animal is the category, otherwise it takes 0. The multivari- ate logistic function with s max = 1 is used for logistic regres- sions (Sokal and Rohlf, 1995). A method of giving a value to the categorical variable is described by Zar ( 1999). Modeling the change in scale The daily relative increase rate of scale parameter (dRIRS) and dRIRL must be cor- log e -L,ar gcs /o ,fe ,s max ,a,,^„7 1 ,)' 2 ) N n q =XZ 1 °g«{ (1/ V ex p[-^-«,> / 4] xexp{-exp[-(Z 9i -<5 9 )/feJU, (10) where a , 6 = values of the location and scale param- eters, respectively, at the first sampling; s max> a j> Pk = coefficients of Equation 6; Y v y 2 - coefficients of Equations 7 and 8; N = number of samplings; n q = number of data at the qth sampling; a q = location parameter at the qth sampling estimated by Equation 5 (r,=s, ); b q = scale parameter at the qth sampling esti- mated by Equation 5 (r~^); and / = length of the /th individual at the fiO ; M 4^%, -^— Turbidity -•— Salinity -■ 40 - 1/ \ 20 - l"'"l I 1 1 1 ~wj Mode (estimated by model 4.1) 90% confidence interval (estimated by model 4.1) ° Mode (sample) Date Figure 3 Environmental fluctuations and prediction of the growth oiCorbiculajapon- ica juveniles spawned in 1997 in Lake Abashiri by the best model (Model 4.1 in Tablel). (Al Insignificant environmental factors (factors excluded in the model selection), turbidity (equivalent to kaolin density, ppmi and salinity (psu, practical salinity unitl. (Bl Significant environmental factors (factors included in the model selection I, temperature (°C) and water fluorescence (equivalent to uranin density, /'g/L>. (Cl Daily relative increase rate of loca- tion parameter (dRIRLl and daily relative increase rate of scale parameter (dRIRS) estimated by the model. (Di Growth of Corbicula japonica; verti- cal bars represent 90% confidence intervals for the shell lengths of the samples. length distribution becomes asymmetric during growth, skcwness of the distribution would increase according to growth. However, there is no correlation between the skewness and the means of the shell lengths. Therefore, we thought that the shell length distribution of the cohort was already asymmetric just after settlement. Such a distribu- tion might be influenced by fluctuations in larval settle- ment during the spawning season; and larval settlement would be influenced by fluctuations in larval supply from the water column. During the spawning season of 1997. the average planktonic larval density gradually increased from 26 ind/m 3 on 25 July to a maximum of 603 ind/m 3 on Baba et al.: An environmentally based growth model for |uvenile Corbicula japonica 21 Table 2 95% confidence limits of location and scale parameters at the first sampling and coefficients of the best model constructed based on the largest extreme value distribution (models 4.1 in Table 1) estimated by profile likelihood method. dRIRL = daily relative increase rate of location parameter. dRIRS = daily relative increase rate of scale parameter. Temp. = water temperature, WF = water fluorescence, Sal. = salinity, Turb. = turbidity. Parameters at 1st sampling Max. dRIRL Age categorization Environmental factors Expressing relationship between dRIRS and dRIRL A, a, a. Temp. ft WF ft Sal. ft Turb. ft Lower 95 % Upper 95 % 0.294 0.304 0.039 0.045 0.010 -26.6' 0.013 -11.5' -14.6 -6.4 0.41 1.00 0.27 0.64 0.0027 0.0039 0.734 0.793 1 One common coefficient for the two categorical variables. 13 August. Then it sharply decreased to 3 ind/m 3 on 19 August (Baba et al., 1999). Such a pattern of larval-density fluctuation might have caused the asymmetric distribution of shell lengths of the settled juveniles. Another possible factor that influenced the shapes of the shell length distri- butions and the relationship between dRIRL and dRIRS is size-dependent mortality, e.g. predations and fisheries. Size-dependent mortality has been reported in several marine bivalves (e.g. Nakaoka, 1996). Potential predators of C.japonica are fishes, such as Japanese dace (Tribolo- don hakonensis) (also known as big-scaled Pacific redfin, FAO), Pacific redfin (Tribolodon brandtii), common carp (Cyprinus carpio), and the So-iny mullet (Liza haemato- cheila ) (Kawasaki 4 ). In our study, the size-dependent mor- tality was negligible because the range of the shell lengths observed in this study was very narrow. The shape of the distribution to describe a single cohort should be determined from the data. In contrast, single cohorts are usually separated from multicohort data by as- suming a normal distribution of lengths in a single cohort (e.g. Fournier and Sibert, 1990). Therefore, it is possible that multicohort analysis done without selection of an adequate distribution to describe a single cohort causes substantial bias in estimations of various stock features of animal populations, such as age composition, growth, mortality, and recruitment. In our preliminary analyses, we also tested smallest extreme value distribution, inverse Gaussian distribution, and lognormal distribution. The in- verse Gaussian distribution was the best for two samples; the lognormal distribution, was the best for two samples; the largest extreme value distribution was the best for ten samples. Therefore, it is reasonable to select the largest ex- treme value distribution. We selected a single distribution for our analyses, otherwise a discontinuous point would have appeared in the growth curve. Relatively large confidence intervals were obtained in the coefficients of the linear component of Equation 6, i.e. a , and /3 ; , (Table 2). The relatively large confidence inter- vals may indicate that the number of estimated coefficients is somewhat larger than the number of samplings. There- fore, to estimate these coefficients more precisely, we may need to investigate more cohorts spawned in other years in future investigations. Growth of C. japonica We identified extremely slow growth in C. japonica juve- niles, which grew to a modal shell length of 0.7 mm during the first year in Lake Abashiri, which lies at 43.7°N. Spats of C. japonica collected from 1992 to 1997 in Lake Shinji, which lies at 35.5°N, grew to a mean shell length of 6.7 mm in natural conditions by the first winter (Yamane et al. 2 ). Using environmental factors measured in Lake Shinji from 1990 to 1998 at monthly intervals (Seike 5 ), we simu- lated the growth of C. japonica with model 4.1. Corbicula japonica grew to a mean shell length of 1.4 mm (standard error, 0.37 ) by the first winter in the simulations. Therefore, the large difference in juvenile growth between the two habitats cannot be explained by environmental differences because the results of the simulation were apparently an underestimate. We think that the extremely slow growth of the juveniles (prolonged phase of meiobenthic develop- ment ) in Lake Abashiri is probably a geographical varia- tion, which is genetically determined, within C. japonica. However, there remains a possibility that the juvenile growth differences depend on other environmental factors not measured in this study. Therefore, the geographical 4 Kawasaki, K. 1997. Lagoon structure and fish produc- tion in Ogawara-ko Lagoon. /;; Final reports on fisheries in Ogawara-ko Lagoon (Tohoku Construction Corporation ed.), p. 4-33. Unpubl. rep. Construction Office for Takasegawa General Development of Tohoku Regional Construction Bureau, 3 Ishido, Hachinohe, Aomori 039-1165, Japan. 6 Seike, Y. 1990-98. Gobiusu: monthly report of water quality in Lake Shinji and Lake Nakaumi. Unpubl. rep. Faculty of Science and Engineering. Shimane University, 1060 Nishi- kawatsu, Matsue, Shimane 690-0S23, Japan. 22 Fishery Bulletin 102(1) 10 Sep 1997; mode: 0.30mm, scale: 0.04, n=341 13 May 1998; mode: 0.41mm, scale: 0.06, n=38 11 Jun 1998; mode: 0.51 mm, scale: 0.12, n=292 10 Jul 1998; mode: 0.57mm. scale: 0.10, n=610 13 Aug 1998; mode: 0.64mm, scale: 0.12. n=456 1 1 Sep 1998; mode: 0.70mm. scale: 0.17, n=202 14 Oct 1998; mode: 0.76mm. scale: 0.17. n=162 0.0 22 Apr 1999; mode: 0.74mm. scale: 0.15, n=265 + + 13 May 1999; mode: 0.81mm, scale: 0.20. n=241 0.2 t t H 0.1 00 28 Jul 1999; mode: 2.14mm, scale: 1.06, n=63 ^#T>fffi^^ 3456 0123456 Shell length (mm) Figure 4 Shell-length compositions of a single cohort of Corbicula japonica spawned in 1997. The raw data (shell lengths) are shown by +. The largest extreme value distribution estimated by the best model ( model 4. 1 in Table 1 1 is shown by a solid line. The largest extreme value distribution independently fitted by the maximum likelihood method is shown by a dashed line. The sampling date and values of location parameter I mode) and scale parameter independently fitted by the maximum likelihood method are shown in each panel. variation should be validated by reciprocal transplanta- tions or laboratory experiments (or both) in future inves- tigations. Prolonged phases of meiobenthic development have been reported in some marine bivalves (Nakaoka, 1992; Harvey and Gage, 1995). However, a prolonged phase of meiobenthic development as a geographical variation is rarely reported. In many species of bivalve, populations from higher lati- tudes have a slower initial growth rate; but longevity and ul- timate size in these populations are frequently greater than at lower latitudes (Newell, 1964; Seed, 1980). The extremely slow growth of C. japonica juveniles in Lake Abashiri may be an extreme example of this phenomenon. In Lake Abashiri, C. japonica failed to spawn in ten out of 21 years for which Baba et al An environmentally based growth model for juvenile Corbicu/a japonica 23 data were available because of low water temperatures dur- ing the summer spawning season (Baba et al., 1999). This means that a long life span is essential to sustain popula- tions of C. japonica in northern habitats. We think that a long life span is the ultimate factor for the extremely slow growth rate of C. japonica juveniles in Lake Abashiri. The growth response of C. japonica juveniles is much less susceptible to environmental factors before the second win- ter than after and is the proximate factor for an extremely slow growth rate. Nuculoma tenuis, a detritus feeder, de- velops its palp proboscides, its feeding apparatus, during the prolonged phase of meiobenthic development (Harvey and Gage, 1995). The change of growth susceptibility to en- vironmental factors in young ages may suggest that some functional morphological changes occur in C. japonica, also a filter feeder. In our preliminary analyses, we could not find a better model when we used different values of s max in Equation 6 between ages instead of categorical variables indicating ages. Therefore, we conclude that the difference in growth rates between ages is not due to a difference in potential maximum growth rate, at least in the range of the shell length observed in our study. When our model is ap- plied to a wider range of the shell lengths or other species, it is best to examine the age dependence of s max . Acknowledgments We express our thanks to T Kato, Vice-Head of the River Improvement Section in the Abashiri Local Office of the Hokkaido Development Bureau, for providing environmen- tal data on Lake Abashiri. We also thank the reviewers of Fishery Bulletin for providing helpful suggestions on our manuscript. 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Prentice Hall, Upper Saddle River, NJ. 25 Abstract— Information is summarized on juvenile salmonid distribution, size, condition, growth, stock origin, and species and environmental associations from June and August 2000 GLOBEC cruises with particular emphasis on differences related to the regions north and south of Cape Blanco off Southern Oregon. Juvenile salmon were more abundant during the August cruise as compared to the June cruise and were mainly distributed northward from Cape Blanco. There were distinct differ- ences in distribution patterns between salmon species: chinook salmon were found close inshore in cooler water all along the coast and coho salmon were rarely found south of Cape Blanco. Dis- tance offshore and temperature were the dominant explanatory variables related to coho and chinook salmon distribution. The nekton assemblages differed significantly between cruises. The June cruise was dominated by juve- nile rockfishes, rex sole, and sablefish, which were almost completely absent in August. The forage fish community during June comprised Pacific herring and whitebait smelt north of Cape Blanco and surf smelt south of Cape Blanco. The fish community in August was dominated by Pacific sardines and highly migratory pelagic species. Esti- mated growth rates of juvenile coho salmon were higher in the GLOBEC study area than in areas farther north. An unusually high percentage of coho salmon in the study area were preco- cious males. Significant differences in growth and condition of juvenile coho salmon indicated different oceano- graphic environments north and south of Cape Blanco. The condition index was higher in juvenile coho salmon to the north but no significant differences were found for yearling chinook salmon. Genetic mixed stock analysis indicated that during June, most of the chinook salmon in our sample originated from rivers along the central coast of Oregon. In August, chinook salmon sampled south of Cape Blanco were largely from southern Oregon and northern Cali- fornia; whereas most chinook salmon north of Cape Blanco were from the Central Valley in California. Manuscript approved for publication 30 June 2003 by Scientific Editor. Manuscript received 20 October 2003 at NMFS Scientific Publications Office. Fish. Bull 102:25-46 (2004). Juvenile salmonid distribution, growth, condition, origin, and environmental and species associations in the Northern California Current* Rick D. Brodeur Northwest Fisheries Science Center National Marine Fisheries Service, NOAA 2030 S. Marine Science Drive Newport, Oregon 97365 E-mail address: Rick-Brodeuriffinoaa-gov Joseph P. Fisher College of Ocean and Atmospheric Sciences Oregon State University Corvallis, Oregon 97331 David J. Teel Northwest Fisheries Science Center National Marine Fisheries Service, NOAA Seattle, Washington 98112 Robert L. Emmett Northwest Fisheries Science Center National Marine Fisheries Service, NOAA 2030 S Marine Science Drive Newport, Oregon 97365 Edmundo Casillas Northwest Fisheries Science Center National Marine Fisheries Service, NOAA Seattle, Washington 98112 Todd W. Miller Cooperative Institute for Marine Resources Studies Oregon State University Newport, Oregon 97365 The need to understand the direct and indirect linkages between oceano- graphic conditions and salmon sur- vival in the marine environment has increased with the listing of many West Coast salmon stocks as threat- ened or endangered. Recent studies have shown that long-term changes in climate affect oceanic structure and produce abrupt differences in salmon marine survival and returns (Francis and Hare, 1994: Mantua et al., 19971. A major regime shift in the subarctic and California Current ecosystems during the late 1970s may have been a factor in reducing ocean survival of salmon in the Pacific Northwest and in increas- ing marine survival in Alaska ( Hare et al., 1999). Fluctuations in mortality of salmon in the freshwater and marine environments have been shown to be almost equally significant sources of annual salmonid recruitment variability ( Bradford, 1995 ). Unlike in the freshwa- ter environment, the physical and bio- logical mechanisms and factors in the marine environment that cause mor- tality of salmon are largely unknown. Predation, inter- and intraspecific competition, food availability, smolt quality and health, and physical ocean conditions likely influence survival of salmon in the marine environment. Thus, increasing our understanding of nearshore ocean environments, their linkages to oceanographic conditions, and the role they play in salmonid survival, could provide management options for increasing adult returns. Characterization of the space-time vari- ability of the environmental conditions that smolts encounter when they enter the nearshore ocean, and the eventual survival of these smolts will allow us to identify which biotic and abiotic ocean conditions are correlated with various ocean survival levels. Many anadromous salmonid popula- tions along the west coast of the United States have declined over the last few decades (Nehlsen et al., 1991), and most stocks show a regional north-south pat- tern in degree of extinction risk (Kope and Wainwright, 1998). This pattern suggests that both marine habitat con- ditions and mesoscale climate patterns affect salmonid population status (e.g. Lawson, 1993). A dramatic example is the population trend of coho salmon (Oncorhynchus kisutch) along the Or- egon coast. Populations along the coast north of Cape Blanco (43°N) have exhib- ; Contribution number 364 of the U.S. GLOBEC program. NEP Office, Oregon State University, Corvallis. OR. 26 Fishery Bulletin 102(1) ited a strong decline in size and survival in the mid-1990s; whereas populations south of Cape Blanco have not shown this trend (Lewis 1 ). This finding suggests that these two populations have experienced different ocean conditions. The quality of the marine habitat (in terms of habitat complexity, prey density, and temperature) undoubt- edly influences fish growth and condition. Growth and indices of condition can be used as measures of habitat quality for juvenile salmon and to identify essential links between oceanographic conditions and survival of salmon populations during the critical juvenile life history phase. Measures such as growth (growth rate, size variation, and allometric relationships) (Lorenzen, 1996; McGurk, 1996) and accumulation of energetic reserves used in growth and sustenance during the low-productivity winter periods have been used previously to characterize habitat quality and to describe how it ultimately affects the individual and the population (Perry etal., 1996; Paul and Willette, 1997). Environmental factors are known to affect growth, repro- duction, survival, and ultimately population recruitment (Hinch et al., 1995; Marschall and Crowder, 1995; Fried- land and Haas, 1996). As such, fish condition, growth rate, and size in the pre-adult stages are parameters that can be used to identify the influence of natural and anthropogenic ocean conditions on marine survival. Much of our current knowledge of the dominant nekton of the pelagic ecosystem off the coasts of Oregon and Wash- ington is derived from a series of 17 cruises conducted by Oregon State University (OSU) from 1979 to 1985. These collections, consisting of >900 quantitative purse seine sets in the northern California Current, were made to examine geographic distributions and temporal trends of the domi- nant nekton and how these relate to physical and biotic conditions at the time of capture. The primary purpose of these cruises was to collect data for assessment of the abundance, distribution, growth, migration, and ecology of juvenile salmon in coastal waters. Data on the distribution, migration and growth of juvenile salmon from these cruises have been summarized in Fisher and Pearcy (1988; 1995). Pearcy and Fisher ( 1988, 1990), and Pearcy ( 1992). Analy- sis of the nonsalmonid data includes studies on their abun- dance and distribution (Brodeur and Pearcy, 1986; Emmett and Brodeur, 2000), feeding habits (Brodeur et al., 1987) and interannual variability in relation to oceanographic conditions (Brodeur and Pearcy, 1992). In addition, the distribution of juvenile salmon (mainly coho and chinook salmon [O. tshawytscha}) has been studied more recently as a component of a multiyear Columbia River Plume study (Emmett and Brodeur, 2000; Teel et al., 2003; Brodeur et al., 2003). However, all these cruises extended only as far south as Cape Blanco, with the exception of one cruise (July 1984), which extended as far south as Eureka, California, but included only a few collections south of Cape Blanco (Pearcy and Fisher, 1990). Thus, the region south of Cape Blanco is almost completely unknown in terms of juvenile 1 Lewis, M. A. 2002. Stock assessment of anadromous salmo- nids 2001. Monitoring program report OPSW-ODFW-2002-04, 57 p. Oregon Dept. Fish Wildlife, Portland. OR 97207. salmon distribution, pelagic nekton, and biological ocean- ography in general, despite being an area of very strong upwelling and high productivity. Also, the fine-scale dis- tribution of juvenile salmon in relation to environmental variables has not been studied in any detail. The California Current is not homogeneous but rather can be divided into distinct subunits or regions, each with its own physical and biological characteristics (U.S. GLO- BEC, 1994). A break between the northernmost two regions occurs at Cape Blanco, where the equatorward upwelling jet veers sharply off the shelf and into the California Cur- rent (Barth et al., 2000). The upwelling zone north of the cape is narrow, extending out about 30 km, whereas south of Cape Blanco, it can extend up to 100 km offshore. This area also appears to represent a faunal break for some zoo- plankton communities (McGowan et al., 1999; Peterson and Keister, 2002) and is a break point for alternative salmon migration strategies (Weitkamp et al., 1995; Weitkamp and Neely, 2002). During the summer of 2000, we conducted broad-scale sampling and fine-scale process studies from central Or- egon to northern California to examine the distribution of juvenile salmon and associated species in relation to environmental conditions. This was one component of a multidisciplinary U.S. Global Ocean Ecosystem Dynamics (GLOBEC) Northeast Pacific study examining the north- ern California Current ranging in scope from the physics up to the top trophic levels (Batchelder et al., 2002). We were interested in examining the distribution of juvenile salmon north and south of Cape Blanco, the origin of these fish, and any regional differences in growth and condition of salmon across the range of sampling. Evidence exists that the physical conditions and the associated biota are different within this geographical scale. Thus, analyses of the relationship between oceanographic conditions and the response of resident biota can provide insights into the linkages associated with physical and biological processes that shape the biological community, and in particular, those associated with salmon recruitment. Methods Field surveys Surveys were conducted over two time periods — early summer (29 May-18 June, 2000) and late summer (28 July-15 August, 2000). Each survey consisted of a meso- scale grid along designated GLOBEC transects that had been monitored for several years and by fine-scale pro- cess sampling at stations of interest based on features observed in the physical environment (fronts or eddies) or by acoustic sampling conducted by two accompanying oceanographic vessels (RV Wecoma and RV New Horizon). Further details on the physical and biological conditions occurring at the time of our sampling have been reported by Batchelder et al. (2002). For the mesoscale survey, stations were established at 1, 5, 10, 15, 20, 25 and 30 nautical miles from shore on each of five transects. Inclement weather, particularly Brodeur et al.: Distribution, growth, condition, origin, and associations of |uvenile salmonids 27 during the first cruise, prevented us from sampling all the stations along each transect. At each station, a Nordic 264 rope trawl built by Nor'Eastern Trawl Systems, Inc. (Bainbridge Island, WA) was towed in surface waters by a chartered fishing vessel (FV Sea Eagle) at a speed of 6 km/h. This rope trawl has a maximum mouth opening of approximately 30 m x 18 m. Mesh sizes ranged from 162.6 cm in the throat of the trawl near the jib lines to 8.9 cm in the codend. To maintain catches of small fish and squid, a 6.1-m long, 0.8-cm mesh knotless liner was sewn into the codend. All tows were 30 minutes in duration. All fish and squid caught were counted and measured at sea. After fork length (FL) was measured to the nearest mm, all juvenile salmon were immediately frozen for later determinations of growth, condition, food habits, genetic analysis, and as- sessment of pathological condition. The physical and biological environment was monitored and sampled at each station immediately prior to setting the trawl. A CTD (conductivity, temperature, and depth) cast was made with a Sea-Bird SBE 19 Seacat profiler to 100 m at deep stations or within 10 m of the bottom at shallow stations. Chlorophyll and nutrient samples were collected from 3 m depth with a Niskin water sampler. A neuston tow with a 1-m 2 mouth containing 333-,(im mesh net was towed for 5 minutes out of the wake of the vessel at each station. General Oceanics flow meters were placed inside the net to measure the amount of water sampled. Additional details on the analysis of these neuston trawls are available in Reese et al. 2 Condition and growth analysis Each salmonid was remeasured (FL to the nearest mm) and weighed (to the nearest 0.1 g) in the laboratory. A por- tion of hepatic and muscle tissue was excised, placed in individual capsules, frozen in liquid nitrogen, and stored at -80°C until analyzed. The bioenergetic health of juve- nile salmon was evaluated by assessing changes in water content (as a surrogate measure of fat accumulation) of liver and muscle to estimate dry tissue weight. The water content was determined by drying tissue samples to a con- stant weight at 105°C. The accumulation of energy reserves during the growth season ( energy reserves of salmon in August in relation to salmon collected in June) that would enhance survival of juveniles during the winter when food availability is lower was also measured. The condition of juvenile salmon was assessed by examining weight residu- als (by using either the wet weight or dry weight) derived from the allometric relationship between length and weight of individual juvenile salmon after logarithmic transforma- tion (Jakob et al., 1996) of salmon captured in June and August. Wet-weight residuals are representative of the traditional condition index of animals and are a reflection 2 Reese, D.C., T.W.Miller, and R.D. Brodeur. 2003. Community structure of neustonic zooplankton in the northern California Current in relation to oceanographic conditions. 22 p. Unpubl. manuscript. Northwest Fisheries Science Center, NMFS. 2030 S. Marine Science Drive, Newport, OR 97365. of somatic tissue growth. Dry-weight residuals are respon- sive to accumulation of fat stores and are a reflection of the bioenergetic health of the individual animal (Sutton et al., 2000; Post and Parkinson, 2001). To contrast growth characteristics during 2000 in differ- ent latitudinal ranges of the California Current, we com- pared ocean growth rates of juvenile coho salmon south and north of Cape Blanco in the GLOBEC study area, and in the area from Newport, Oregon, north to northern Washington. The physical and biological characteristics of these three regions of the coastal ocean differ greatly (U.S. GLOBEC, 1994), and these differences may impact the dis- tribution and abundance of prey of juvenile salmonids and therefore may also affect salmonid growth. Data north of Newport, Oregon, were collected during a separate study of the Columbia River plume and the adjacent coastal ocean (hereafter called the "plume study") using the same trawl and a similar sampling strategy as in the GLOBEC study (see Emmett and Brodeur [2000] and Teel et al. [2003] for details). Scales were examined from 45 juvenile coho salmon caught during the June and August 2000 GLOBEC cruises and 252 juvenile coho salmon caught during the 2000 plume cruises. The scales were mounted on gummed cards from which acetate impressions were made. Using a video camera attached to a compound microscope and Optimas® imaging software (vers. 5.1, Optimas Inc., Se- attle, WA) we measured the distance (scale radius) along the anterior-posterior axis of each scale from the focus (F) to the ocean entry mark (OE) and to the scale margin (Fig. 1). The fork-length of each fish at the time of ocean entry (FL 0E ) was estimated from the scale radius (SR 0E ) at ocean entry using the Fraser and Lee back-calculation method (Ricker, 1992): FL„ (FL- 36.07) SR xSR of . +36.07, where FL = length at capture; SR = scale radius at capture; and 36.07 = the intercept from a regression of SR on FL for juvenile coho salmon caught in the ocean (Fig. 2A). In an analogous fashion, fish weight at time of ocean entry (Wr 0£ ) was back-calculated f length at ocean entry (FL 0E ): (Wt 0E ) was back-calculated from the estimated fish fork \ni Wt 0E ) = (ln(Wr 1 + 12.633) ln(FL) xln(FL r , F 1-12.633, where Wt = weight at capture; and -12.633 = the intercept from a linear regression of ln(Wr) on ln(FL) for juvenile coho salmon caught in the ocean (Fig. 2B). The growth rate in FL, (FL-FL 0E )lAd, 28 Fishery Bulletin 102(1) Figure 1 Scale from a 352-mm FL male juvenile coho salmon (Oncorhynchus kisutch) caught during the August 2000 GLOBEC cruise showing the axis of measurement (black line), the focus (F), the mark of ocean entry (OE), and the scale margin (SM). and the instantaneous growth rate in weight: G = (MWt)-MWt 0E ))/M, where Ad = estimated days between ocean entry and cap- ture, were estimated for each salmon. The meaning of the instantaneous growth rate G can be stated as follows: if salmon growth is exponential between ocean entry and capture, then Wt Wt„ and at any instant the fish's weight increases at the rate of G of its body weight per day. G can be multiplied by 100 to give the instantaneous growth rate in terms of percentage of body weight per day. Although the dates of ocean entry of individual lish were unknown, seaward migration of coho salmon smolts in California, Oregon, and Washington rivers occurs mainly between mid-April and mid-June, and there is no consis- tent latitudinal trend in timing of the migration ( Weitkamp et al., 1995). Peak downstream migration of coho salmon smolts was between mid-May and very early June in the Columbia River estuary, 1978-83 (Dawley et al., 1985), and in the lower Trinity River, California, 1997-2000 (US- A FL (mm) vs scale radius (mm) GM Regression: FL = 152.22 SR +36.07 r 2 = 0.94, n=370 1 2 Scales radius (mm) B Wt(g)vs FL(mm) In(WI) = 3.2273'ln(FL) - 12 6329 or Wt(g) = 3.263x1 (T 5 FL(mm) 32273 n=1018V = 0.99 s — 5 In (FL) Figure 2 (A) Regression of fork length (FL) on scale radius and. 'Bi regression of ln(WY) on ln(FL) for juvenile coho salmon {On- corhynchus kisutch) caught during the May 1998-September 2000 Columbia River plume study. FWS 3 ). In 2000, peak downstream migration of mainly nonhatchery coho salmon smolts at 13 monitoring sites in coastal Oregon rivers north of Cape Blanco occurred from April 2 to May 20; median peak migration occurred 26 April ( Solazzi et al. 4 ) From the information available on timing of seaward migration of coho salmon smolts. we used an ocean entry date of 15 May when calculating Ad and estimating ocean growth rates of unmarked coho salmon from scales. In addition to estimating growth rates of juvenile coho salmon from scales, we also estimated instantaneous growth rates in weight between hatchery release and cap- ture in the ocean of 28 coded-wire-tagged (CWT) juvenile coho salmon: USFWS (U.S. Fish and Wildlife Service). 2001. Juvenile sal- monid monitoring on the mainstem Klamath River at Big Bar and mainstem Trinity River at Willow Creek, 1997-2000, 106 p. Annual report of the Klamath River Fisheries Assessment Pro- gram. Areata Fish and Wildlife Office, Areata, CA 9552 1 . Solazzi, M.F., S.L.Johnson, B.Miller, and T.Dalton. 2002. Sal- monid life-cvele monitoring project 2001. Monitoring program report OPSW-ODFW-2002-2, 25 p. Oregon Dept. Fish and Wildlife, Portland. OR 97207. Brodeur et al.: Distribution, growth, condition, origin, and associations of juvenile salmonids 29 G = (MWt)-MWt R ))/M, where Wt = weight of the CWT fish at capture; Wt R = the average weight of fish in the CWT group at time of release; and Ad = days between hatchery release and capture in the ocean. Estimated growth rates of these CWT fish, of known release date and known average release weight were used to vali- date the growth rates estimated from scale analysis Our analysis of the growth of chinook salmon based on scale characteristics is not far enough advanced to report in this article. We plan to present these data in a later article. Contribution of hatchery coho salmon to catches The total numbers, percentages of marked fish ( any exter- nal fin clips or internal tags) and grand average weights of hatchery coho salmon smolts released in 2000 are sum- marized for different release regions in Appendix Table 1. These data were used to compare the estimated average weights of fish at time of ocean entry (from scale analy- sis ) with the average weights of hatchery fish at time of release, and also to estimate the proportions of hatchery coho salmon in our catches. We calculated the expected percentage (E%) of marked fish in each catch if 100% of the fish were hatchery fish: E% X*.*4, where i?, = the proportional contribution of region i to the catch (this paper for the GLOBEC catches, and from Teel et al., 2003 for the plume study catches); and A, = the percentage of hatchery fish that were marked in region i ( from Appendix Table 1 ). The percentage of hatchery fish in each catch sample (H%) was then estimated as 0% H% = — xlOO, E% where O c A = observed percentage of marked fish. Genetic analysis The freshwater origins of juvenile chinook and coho salmon and steelhead (O. my kiss) were studied by using standard methods of genetic mixed stock analysis (Milner et al., 1985; Pella and Milner, 1987). According to the methods described by Aebersold et al. (1987), samples of eye, liver, heart, and skeletal muscle were extracted from frozen whole juvenile salmon and analyzed with horizontal starch-gel protein electrophoresis. Data from previous studies char- acterizing genetic (allozyme) differences among spawning populations in California and the Pacific Northwest were then used as baseline data to estimate the stock composi- tions of our ocean caught mixed-stock samples. Baselines consisted of 32 gene loci and 116 populations for chinook salmon (Teel et al. 5 ), 58 loci and 49 populations for coho salmon (Teel et al., 2003), and 55 loci and 57 populations for steelhead (Busby et al., 1996). Estimates of stock com- positions were made by using the maximum likelihood procedures described by Pella and Milner (1987) and the Statistical Package for Analyzing Mixtures (Debevec et al., 2000). Estimates of individual baseline populations were then summed to estimate contributions of regional stock groups. Precision of the stock composition estimates was estimated by bootstrapping the estimates 100 times with resampling of the baseline and mixture genetic data as described in Pella and Milner (1987). Habitat and assemblage analysis The raw numbers offish and squid caught from each trawl were converted to densities based on the volume filtered per trawl to standardize for differences in effort between tows. Density contours of juvenile salmon and other nekton were produced using specialized graphics programs. We then tested whether the habitat associations of the domi- nant salmonids were significantly different from the total habitat sampled by following the methods outlined in Perry and Smith ( 1994). This procedure involved comparing the cumulative distributions of salmon catch with observed environmental conditions (temperature, salinity, chloro- phyll-a at one meter, water depth, and neuston displace- ment volume). We performed 5000 randomizations of the data and used the Cramer-von Mises test statistic recom- mended by Syrjala ( 1996) as being robust to the effects of inordinately large catches. To explore the relationship between juvenile salmon and other fish species and environmental variables, we used several types of multivariate analyses (McCune and Grace, 2002 ). Original data from each of the two cruises formed complimentary species and environmental matrices. The June and August cruises were analyzed individually to look at spatial patterns of species composition in relation to environmental gradients (Gauch, 1982). To avoid spurious effects of rare species, we excluded species from the data matrix that had a frequency of occurrence of less than 10% of the possible occurrences for each cruise (McCune and Grace, 2002). To minimize the effect of very large catches, the data were log transformed. Stations with no species present were eliminated from the data set to allow for anal- ysis of sample units in species space. Data transformations and their effects on the summary statistics were examined prior to analysis. Analyses of data were performed by using PC-ORD version 4.28 (McCune and Mefford, 1999). Agglomerative hierarchical cluster analysis (AHCA) using the Bray-Curtis dissimilarity measure and Wards Teel, D. J„ P. A. Crane. C. M. Guthrie, III, A. R. Marshall. D. M. Van Doornik, W. D. Templin, N. V. Varnavskaya, and L. W. Seeb. 1999. Comprehensive allozyme database discriminates chinook salmon from around the Pacific Rim. (NPAFC docu- ment 440), 25 p. Alaska Department of Fish and Game, Divi- sion of Commercial Fisheries, 333 Raspberry Road, Ancorage, AK 99518. 30 Fishery Bulletin 102(1) linkage function was applied to arrange the nekton spe- cies assemblages and stations into cluster groups. The cutoff level to form optimal groups within the species and station dendrograms was based on several criteria: 1) biological meaning; 2) significance tests of groups using a multi-response permutation procedure (MRPP); and 3i comparison of cutoff level MRPP results with those groups obtained from one cutoff level below and above the level of interest. A nonparametric procedure, MRPP compares the a priori groupings from AHCA and tests the hypothesis of no difference between the groups. For cluster analysis of stations, indicator species analysis (ISA) was used to determine nekton species strongly associated with indi- vidual groups. ISA assigns indicator values to each spe- cies according to relative abundance and frequency, then tests the significance (Monte-Carlo permutation test) of the highest species-specific indicator value assigned to a particular group. Nonmetric multidimensional scaling (NMS; Kruskal, 1964) was used to ordinate sample units in species space and to compare station cluster groups to environmental gradients. NMS was chosen for this analysis because it is robust to data that are non-normal and that have high numbers of zeros. Initial runs of NMS from both cruise da- tasets resulted in three-dimensional solutions. Subsequent reapplication of NMS using a three-dimensional solution (Sorensen distance, 400 maximum iterations, and 40 runs with real data) was applied for the final ordinations. To examine the environmental or station factors associated with each NMS axis that may have affected the distribu- tion of the dominant taxa, we correlated the NMS station and species scores to a suite of environmental variables including water depth, distance offshore, latitude, surface temperature, surface salinity, chlorophyll-a concentration, and neuston zooplankton settled volumes. Pearson and Kendall correlations with each ordination axis were used to measure strength and direction of individual species and environmental parameters. Results Distribution of juvenile salmon and other species We collected a total of 18,852 nekton individuals: two ceph- alopod, one agnathan, two elasmobranch, and 57 fish taxa from 163 surface trawls (see Table 1 for scientific names of all species). With the exception of market squid in June and blue shark in August, most of the nonteleost nekton occurred in only a few collections. Substantially fewer fish were caught in the June cruise than in the August cruise, but the diversity was much higher in the June cruise. The catch in June was dominated by forage fishes such as Pacific herring, surf and whitebait smelt, and juvenile rock- fishes, sablefish, and flatfishes. Salmonids, mainly juvenile chinook and coho salmon and steelhead, comprised a rela- tively minor proportion of the catches (only 114 juvenile salmonids; 1.9 % of the total). The August cruise was dominated by several large catches of Pacific sardine (Table 1 ). Jack mackerel was the most common nonsalmonid caught. Many of the juvenile fish taxa caught during the June cruise were absent during the August cruise; those that did occur ( sablefish. rex sole) were much lower in abundance. Mesopelagic fishes of the family Bathylagidae and Myctophidae were collected only during the August cruise, mainly because of the inclusion of more offshore stations and occasional collections during nondaylight hours. As in the earlier cruise, salmonids com- prised a relatively minor percentage of the catch (3.19f ) but were more common and abundant during this survey. Juvenile chinook salmon were broadly distributed lati- tudinally during both cruises, but their distribution was mainly restricted to nearshore stations within the 100-m isobath (Fig. 3). Coho salmon juveniles were more common north of Cape Blanco during both cruises and were found generally farther offshore than chinook salmon juveniles (Fig. 3). In contrast, steelhead juveniles were found mainly south of Cape Blanco, especially in June, but their zonal distribution overlapped that of coho salmon juveniles. Size and condition of juvenile salmon Fork length of yearling chinook salmon averaged 227 ±42 mm FL in June and 230 ±30 mm FL in August and aver- aged 135 ±12 mm FL for subyearling chinook salmon in August, whereas juvenile coho salmon averaged 162 ±32 mm FL in June and 286 ±46 mm FL in August ( Table 2 ). No significant differences in fork length of juvenile chinook or coho salmon north or south of Cape Blanco were evident. Juvenile coho salmon weighed significantly more on a wet-weight basis for a given fork length in the region north of Cape Blanco compared to juveniles captured south of Cape Blanco (Fig. 4). This pattern was also similar and significant when evaluated on a dry-weight basis (bioen- ergetic growth). Although the stock composition in the two regions could account for some of these differences, the growth responses likely reflect habitat-specific features in the region north of Cape Blanco that benefit coho salmon. No difference in condition of yearling chinook salmon cap- tured north or south of Cape Blanco, on either a wet- or dry- weight basis, was evident (Fig. 4). Information regarding size and condition of subyearling chinook salmon are not presented because few subyearling chinook salmon were caught in June and all but one subyearling chinook salmon in August were caught in the region south of Cape Blanco, OR. Insufficient subyearling chinook salmon were avail- able for an analysis comparable to that done for yearling chinook and coho salmon. Proportions of wild and hatchery coho salmon Most of the juvenile coho salmon caught during the plume study north of Newport, Oregon, originated in hatcher- ies (Table 3). In June and September 2000 we estimated that wild fish comprised only W9i and 25 r < . respectively, of the catch. Wild fish, however, comprised a proportion- ally much higher percentage of the catch of coho salmon in the GLOBEC study area in June north of Cape Blanco (67$ I, and in August south of Cape Blanco (619! I, than in the plume study area farther to the north. Most jacks and Brodeur et al.: Distribution, growth, condition, origin, and associations of |uvenile salmonids 31 Table 1 Phylogenetic listing of nekton catch in numerical composition, frequency of occurrence (F.O.) and size range cau ght for each cruise. (j) indicates juvenile stage; (a) adult. ML = mantle length, TL = total length. FL = fork length, SL = standard length ( in mm). Class and Family Common name June (84 stations) August (79 stations) Scientific name dumber F.O. Size range Number F.O. Size range Cephalopoda Onychoteuthidae Pacific clubhook squid Onychoteuthis borealijaponicus 19 6 21-80 ML 302 6 21-227 ML Loliginidae Market squid Loligo opalescens 301 14 33-122 ML 1 1 35 ML Agnatha Petromyzontidae Pacific lamprey Lampetra tridentata 1 1 625 TL Chondrichthyes Alopiidae Thresher shark Alopias vulpinus 1 1 36-576 TL Carcharhinidae Blue shark Prionace glauca 18 10 1300-1660 TL Osteichthyes Xenocongridae Eel leptocephalus Thalassenchelys coheni 3 1 214-243 TL 2 2 260-305 TL Clupeidae Pacific herring Clupea pallasi 1022 9 127-195 FL Pacific sardine Sardinops sagax 7 2 237-260 FL 10,327 15 178-290 FL Engraulididae Northern anchovy Engraulis mordax 49 12 148-165 FL Salmonidae Chinook salmon (j,a) Oncorhynchus tshawytscha 56 18 121-780 FL 252 26 109-910 FL Coho salmon (j,a) Oncorhynchus kisutch 35 15 122-580 FL 111 25 210-736 FL Cutthroat trout (j,a) Oncorhynchus clarki 1 1 186 FL 3 3 258-341 FL Steelhead trout (j,a) Oncorhynchus mykiss 22 8 176-284 FL 36 13 261-430 FL Osmeridae Smelt (j) Osmeridae 14 4 37-52 SL 74 5 31-50 SL Surf smelt Hypomesus pretiosus 846 8 128-184 FL 351 7 140-187 FL Whitebait smelt Allosmerus elongatus 946 6 60-114 FL 79 3 76-132 FL Bathylagidae Popeye blacksmelt Bathylagus ochotensis 1 1 76 SL Paralepidae Slender barracudina Lestidium ringens 3 1 72-76 SL Myctophidae Northern lampfish Stenobrachius leucopsarus 96 4 14-70 SL Bigfin lanterfish Symbolophorus californiensis 61 4 89-102 SL Blue laternfish Tarletonbeama crenularis 10 3 33-87 SL Gadidae Gadid(j) Gadidae 10 3 42-58 SL 13 3 53-57 SL Pacific cod 1 j ) Gadus macrocephalus 23 1 38-60 SL Pacific tomcod ( j ) Microgadus proximus 6 4 35-55 SL 8 2 49-80 SL Scomberesocidae Pacific saury Cololabis saira 26 1 182-229 FL 66 6 131-194 FL Atherinidae Jacksmelt Atherinopsis californiensis 1 1 302 FL Trachipteridae King-of-the-salmon (j ) Trachipterus altivelis 2 2 71-270 SL 12 2 40-83 SL Gasterosteidae Threespine stickleback Gasterosteus aculeatus 1 1 60 SL Scorpaenidae Pacific ocean perch (j ) Sebastes alutus 1 1 33 SL Darkblotched rockfish (j Sebastes crameri 154 14 29-54 SL 1 1 53 SL Yellowtail rockfish (j) Sebastes flavidus 1350 24 20-63 SL 1 1 18 SL Shortbelly rockfish (j ) Sebastes jordani 1 1 37 SL Black rockfish (j,a) Sebastes melanops 1 1 30 SL 1 1 335 FL Bocaccio (j ) Sebastes paucispinis 20 5 21-36 SL Canary rockfish (j ) Sebastes pinniger 27 5 22-39 SL Bank rockfish (j ) Sebastes rufus 8 1 16-28 SL Stripetail rockfish (j) Sebastes saxicola 13 3 32-37 SL Hexagrammidae Lingcod (j) Ophiodon elongatus 20 9 76-81 FL Anoplopomatidae Sablefish (j ) Anoplopoma fimbria 182 14 55-136 FL 4 2 173-241 FL continued 32 Fishery Bulletin 102(1) Table 1 (continued) Class and Family Common name Scientific name June (84 stations) August 179 stations) Number F.O. Size range Number F.O. Size range Cottidae Irish lord Ij) Hemilepidotus spp. 2 1 38-40 FL Cabezon (j ) Scorpeanichthys marmoratus 12 7 33-38 SL Pacific staghorn sculpin Leptocottus armatus 1 1 180 TL Agonidae Sturgeon poacher (j) Podothecus acipenserinus 1 1 80 TL Cyclopteridae Pacific spiny lumpsucker Eumierotremus orbis 1 1 253 TL Carangidae Jack mackerel Trachurus symmetricus 111 3 364-583 FL 839 20 227-589 FL Bramidae Pacific pomfret Brama japonica 5 2 387-434 FL Anarhichadidae Wolf-eel (j) Anarrhichthys ocellatus 15 13 215-555 TL 8 7 442-582 TL Ammodytidae Pacific sandlance Ammodytes hexapterus 4 4 45-82 SL Zaprodidae Prowfish (j) Zaprora silenus 1 1 68 SL Scombridae Chub mackerel Scomber japonicus 74 6 266-421 FL Centrolophidae Medusafish Icichthys lockingtoni 3 3 37-50 SL 8 6 87-129 FL Bothidae Sanddabs (j) Citharichthys spp. 23 13 35-43 SL 3 2 269-288 TL Pacific sanddab (j ) Citharichthys sordidus 32 4 32^4 SL Speckled sanddab (j ) Citharichthys stigmaeus 60 10 30-43 SL Pleuronectidae Dover sole (j) Microstomas pacificus 2 2 40-50 SL 3 1 27-34 SL Sand sole (j) Psettichthys melanostictus 3 3 22-39 SL Slender sole (j) Eopsetta exilis 1 1 66 SL Starry flounder Platichthys stellatus 2 1 349-399 TL Curlfin sole (j) Pleuronichthys decurrens 5 3 25-31 SL English sole Parophrys vetulus 1 1 303 TL Rex sole (j ) Errex zachirus 581 12 34-79 SL 48 11 44-70 SL Molidae Ocean sunfish Mola mola 1 1 620 TL Total 5974 12,878 about one half of the nonjacks caught north of Cape Blanco in August were hatchery fish. Two factors, however, may have lead to inaccuracies in estimation of hatchery-wild ratios of coho salmon in the GLOBEC study area. First, because of low sample sizes, the data were pooled from both June and August catches for the genetic stock analysis; therefore we do not know the proportional contributions of the different release areas to the catches in either month alone. Second, all the fish released from Klamath River and Trinity River hatcheries had been clipped on the maxillary. We were unaware that the maxillary clip was being used, did not look for it, and consequently may have classified fish with this mark as unmarked. Therefore, the proportion of hatchery fish in the catch of coho salmon during GLOBEC may have been higher than is shown in Table 3. Age and growth of juvenile coho salmon Forty-three percent (24 of 56) of the juvenile coho salmon caught during the August GLOBEC cruise were preco- cious males ("jacks") according to the testes-weight to body-weight criteria of Pearcy and Fisher ( 1988). This is a much higher percentage of jacks than found among juve- nile fish caught in September 2000 in the plume study off Oregon and Washington, where only 4.5% offish (6 of 132) were precocious males or females according to the same criteria. Because the jacks were considerably larger than the nonjacks, average growth rates of the two groups were reported separately. Estimated average growth rates in FL between ocean entry and capture were higher for fish caught in the August 2000 GLOBEC cruises (1.56-2.22 mm/d) than for fish caught in any other cruises (Table 3). The fish caught in August 2000 were also larger when they entered the ocean (average 170- 178 mm FL) than fish caught in other cruises (averagel54-160 mm FL). Average growth rate of jacks from north of Cape Blanco (2.22 mm/d), was significantly higher (/-test, P<0.05) than growth rates of nonjacks (1.56-1.67 mm/d). Growth rates of nonjacks north and south of Cape Blanco were not significantly different la- test, P<0.05). The combination of large size at ocean entry Brodeur et al.: Distribution, growth, condition, origin, and associations of juvenile salmonids 33 45.0 44.5 44.0 43.5 43.0 42.5 42.0 41.5 Newport Chinook > 1 to 5 6 to 150 Coho A 1 10 5 A 6 to 150 J Oregon r California 45.0 44.5 44.0 43.5 43.0 42.5 42.0 41.5 125.5 125.0 124.5 124,0 123.5 125.5 Longitude (W) 125.0 124.5 124.0 123.5 Figure 3 Catch distribution for juvenile coho (Oncorhynchus kisutch) and chinook salmon (O. tshawytscha) for the (A) June and (B) August cruise overlaid on surface temperature contours. Plus signs are stations sampled where no salmon were caught. and favorable conditions for growth in the ocean probably contributed to the very high percentage of jack coho salmon in August 2000 in the GLOBEC study area. Estimated average growth rates between ocean entry and capture of juvenile coho salmon were higher in the GLOBEC area than in the plume study area U-tests, P<0.05). For fish caught in June, average growth rate was 1.06 mm/d and 0.63 mm/d in the GLOBEC and plume study areas, respectively. For fish caught in August or September, average growth rate was 1.57-2.22 mm/d in the GLOBEC study area and 1.17 mm/d plume in the study area (Table 3). The higher growth rates of coho salmon caught in the GLOBEC study area suggests that in 2000 conditions for growth were bet- ter there than those in the plume study area farther north off Oregon and Washington. Average instantaneous growth rates in weight were also higher (/-tests, P<0.05) for the fish caught in the June and August 2000 GLOBEC cruises (2.0 and 2.1-2.8% body wt/d, respectively) than for the fish caught in the June and September 2000 plume study cruises (1.2 and 1.7 % body wt/d, respectively; Table 4A). In addition, the average condition index (CI) of juve- nile coho salmon in June was significantly higher (/-test, P=0.03) in the GLOBEC study area (1.12, n=32, SD=0.087) than in the plume study area (1.07, n=245, SD=0.117). Similarly, the average CI of nonjack juvenile coho salmon was higher (/-test, P=0.002) in August in the GLOBEC study area (1.24, n=32, SD=0.096) than in September in the plume study area (1.18, n=132, SD=0.100). Both the high instantaneous growth rates in weight and the high CI of juvenile coho salmon caught in the GLOBEC study area suggest that conditions for growth of coho salmon in this area were very good in 2000. Growth rates estimated from the few CWT fish caught during these cruises (Table 4B) were similar to, and help validate, the growth rates estimated from scales (Table 4A). Average weights at time of ocean entry back-calculated from scales for coho salmon caught in June in the GLOBEC area and in all months in the plume study area (Table 4A) were slightly higher than the average weights of hatchery coho salmon at time of release (Appendix Table 1). For ex- ample, in the plume study area, average back calculated weights at ocean entry ranged from 37.5 g to 42.4 g (Table 4A) — slightly higher than the expected average weights at release of about 32-33 g based on the stock composi- 34 Fishery Bulletin 102(1) Table 2 Summary of mean, standard deviation, and range of FL measured in the field, weight measured in the laboratory, and condition index (CI) of subyearling (age 0.0) and yearling (age 1.0) chinook salmon and yearling (age 1.0) coho salmon caught during the June and August cruises north (N) and south (S) of Cape Blanco (latitude 42.837°). Precocious coho salmon are indicated with a "J". Field FL (mm) Laboratory weight (g) C.I. (wtx 10 5 / FL 3 ) n Mean SD Range Mean SD Range Mean SD Chinook (age 0.0) June (N) 1 121 — — 18 — — 1.04 — August (N) 1 172 — — 70 — — 1.37 — August (S) 125 134 12 109-175 28 9 12-70 1.10 0.08 Chinook (age 1.0) June (N) 27 229 42 144-280 178 91 33-306 1.32 0.10 June(S) 1 174 — — 67 — — 1.28 — August (N) 54 229 26 187-318 164 72 80-468 1.32 0.09 August (S) 35 231 35 190-349 176 94 80-535 1.32 0.07 Coho (age 1.0) June (N) 30 161 33 122-276 56 51 19-292 1.13 0.08 June (S) 2 172 172-172 49 1 48-49 0.95 0.01 August (N-J) 24 365 31 310-415 690 209 375-1198 1.38 0.12 August (N) 24 285 51 210-385 326 188 97-766 1.26 0.10 August (S) 8 293 33 239-334 308 103 157-433 1.19 0.05 Table 3 Catch, percentage of the catch that was marked, estimated percentage of hatchery origin, size of scale sample, FL at ocean entry (OE) back calculated from scales, FL at capture, and estimated growth rate in FL while in the ocean for juvenile coho salmon caught during the 2000 GLOBEC and Columbia River plume studies. All length data are from the scale sample only. An ocean entry date of 15 May was used when calculating growth rate in FL. Cruise Catch (n) Marked Estimated % Scale sample hatchery origin (n) Back- calculated FL at OE (mm) mean (SD) FL at capture (mm) Growth rate (mm/d) mean (SD) mean(SD) GLOBEC June 2000 32 32% 33% 11 155 (29.0) 177(42.3) 1.06(1.01) Aug 2000 North of C.Blanco Jacks 24 71% 74% 19 170(22.8) 370(28.1) 2.22 (0.35) Nonjacks 24 46% 48% 9 178(21.6) 309(46.1) 1.67 (0.51) South of C. Blanco Nonjacks 8 38% 39% 6 178(13.0) 303 (29.3) 1.56 (0.22) Plume study May 2000 165 68% 76-80% ; 79 157(16.5) 166(17.7) 0.97(1.15) Jun 2000 245 76% 90% 97 160(14.5) 185(23.4) 0.63 (0.53) Sep 2000 132 65% 75% 76 154(19.0) 305 (24.9) 1.17(0.23) ' No genetic stock analysis was available. The higher estimate assumes the same stock composition as in June, hatchery fish were from the Columbia River. the lower estimate assumes that all Brodeur et al.: Distribution, growth, condition, origin, and associations of |uvenile salmonids 35 A 0.004 0002 -0.002 -0.004 □ Wet Wt (Somatic Growth) to as -0.006 "D Dry Wl (Energetic Growth) CO 1) 0.02 -, o B 0.01 - — L — H^H -0.01 - -0.02 - -0.03 - -0.04 - -0.05 - l -0.06 - -0.07 - Cape Blanco Cape Blanco North South Figure 4 Wet and dry weight residuals ( + 1 standard error) for (A) yearling chinook (On- corhynchus tshawytscha) and (B) juvenile coho salmon (O. kisutch) collected North and South of Cape Blanco. Weight residuals are derived from the linear relationship between fork length and wet or dry weight (log-transformed data) of juvenile salmon captured in June and August. tion of these catches (Teel et al., 2003) and the release weights (Appendix Table 1). Similarly, the back-calculated weight at ocean entry in June in the GLOBEC area (45.5 g) was slightly higher than the expected average weight at hatchery release (about 41 gl based on the stock compo- sition (Table 5) and the average release weights. These fairly small differences between back-calculated size at ocean entry and average size at release could be due to growth during downstream migration, selectively higher mortality of small smolts, or a bias in the back-calculation procedure. However, the average back-calculated weights at time of ocean entry offish caught in August in the GLOBEC study area (60-69 g) were over two standard deviations above the average weights of hatchery fish released from the Oregon coast or northern California — the main contributors to this catch (Appendix Table 1). These were obviously atypical coho salmon, and the very high proportion of jacks (preco- 36 Fishery Bulletin 102(1) Table 4 (A) Weights at ocean entry I OE ) back-calculated from scales, weights at capture and estimated instantaneous rates of growth while in the ocean iGl for juvenile coho salmon caught during the 2000 GLOBEC and Col umbia River plume studies. An ocean entry date of 15 May was used when calculating growth rate. (B) Similar data for CWT fish. Growth rates of the CWT coho salmon were estimated for the periods between hatchery release and capture in the ocean. A Cruise ;; Back-calc. Wt. at OE (g) Weight at capture (g) G mean (SD) mean(SD) mean (SD) GLOBEC June 2000 11 45.5 (26.8) 78.0(76.4) 0.020(0.015) Aug 2000 North of C. Blanco Jacks 19 68.9(27.2) 719.7(200.0) 0.028 (0.005) Nonjacks 9 59.5 (26.3) 419.2(177.2) 0.023 (0.006) South of C. Blanco Nonjacks 6 60.3(12.8) 336.2 (96.2) 0.021 (0.002) Plume study May 2000 79 39.4 (10.8) 47.9(14.6) 0.020(0.024) Jun 2000 97 42.4(12.5) 71.9(33.3) 0.012(0.009) Sep 2000 75 37.5(13.7) 347.2(158.3) 0.017(0.003) B Cruise n Wt. at release (g) Wt. at capture (g) G mean (SD) mean (SD) mean (SD) GLOBEC Jun 2000 4 44.4(1.3) 86.6 (30.9) 0.018(0.005) Aug 2000 3 35.6 (9.8) 395.7(215.0) 0.024(0.003) Plume study Jun 2000 11 28.3(4.5) 66.1(32.3) 0.012(0.005) Sep 2000 10 33.4(10.91 392.4(283.3) 0.018(0.002) cious, sexually developed males) among the fish was prob- ably a consequence of their very large size at ocean entry and their high rates of growth in the ocean. Freshwater origins of juvenile salmonids Allozyme data were collected from samples of 247 chinook salmon, 88 coho salmon, and 58 steelhead. Genetic mixed stock analyses indicated that chinook salmon in June were predominately (54%, SD=0.18) from rivers and hatcheries along the mid Oregon coast, an area immediately north of Cape Blanco (Table 5, Fig. 5). In August, chinook salmon were largely from rivers that enter the sea south of Cape Blanco. Fish from the Sacramento and San Joaquin rivers in northern California were estimated to comprise 90% (SD=0.07) of the chinook salmon sampled in August north of Cape Blanco. The largest concentration of chinook salmon we sampled was south of Cape Blanco in August, and these fish were mostly from rivers in southern Oregon (539(, SD=0.10) and the Sacramento and San Joaquin rivers (20%, SD=0.05). Chinook salmon from the Colum- bia River Basin were also present, but were estimated to comprise only 18% (SD=0.15) of the June sample and 8% (SD=0.05) of the August sample north of Cape Blanco. Recoveries of hatchery chinook salmon bearing coded-wire tags (CWT) provided direct evidence of stock origins for ten fish, all taken in trawls north of Cape Blanco (Table 5). These data reveal that hatchery fish released from the Umpqua River on the central Oregon coast (;;=6), Columbia River Basin («=3) and Sacramento River (« = 1) contributed to our sample of chinook salmon. The propor- tion of CWT fish from the Umpqua River in our August catch north of Cape Blanco (8%) indicated that the con- tribution of mid Oregon coastal fish was underestimated in the genetic analysis likely because of the small size of the mixture sample. Genetic estimates of coho salmon indicated that most fish originated from coastal Oregon rivers north of Cape Blanco (479S , SD=0.10) and from the Columbia River (13%, SD=0.08 ) (Table 5 ). However, a substantial proportion (40 r /i , SD=0.09) of coho salmon were from coastal rivers south of Cape Blanco, a region that includes spawning populations in the Rogue and Klamath rivers. Eight coho salmon in our sample contained CWTs and showed that fish from Brodeur et al.: Distribution, growth, condition, origin, and associations of juvenile salmonids 37 Table 5 Estimated percentage stock compositions, samples sizes, and recoveries of coded wire tags (CWTs) for chinook and coho salmon and steelhead sampled in trawl surveys along the Oregon and California coasts in 2000 Some of tht major baseline stocks are given for coastal stock groups. None of the steelhead sampled contained coded wire tags. June (rc=35) August (?!=157) August (n=55) Entire South of North of Study Area Cape Blanco Cape Blanco Chinook salmon stock group Est. SD CWT Est. SD CWT Est. SD CWT Columbia and Snake Rivers 18 0.15 2 3 0.03 8 0.05 1 North Oregon coast (Nehalem, Trask, Alsea, and Siuslaw Rivers) 0.00 0.00 0.00 Mid Oregon coast (Umpqua, Coquille, Sixes, and Elk Rivers) 54 0.18 3 3 0.03 1 0.02 3 South Oregon coast (Rogue. Chetco, and Winchuck Rivers) 26 0.16 53 0.10 0.00 Klamath and Trinity Rivers 0.00 14 0.07 0.00 North California Coast (Mad, Eel, and Mattole Rivers) 2 0.05 7 0.07 1 0.04 Sacramento and San Joaquin Rivers 0.00 20 0.05 90 0.07 1 June and August (rc=88) Coho salmon stock group Entire study area Est. SD CWT Columbia River 13 0.08 2 North and Mid Oregon coast (Nehalem, Siletz, Alsea, Umpqua, and Coos Rivers) 47 0.10 5 Rogue and Klamath Rivers 40 0.09 1 North California Coast (Mad, Russian, Little, and Scott Rivers) 0.00 June and August (n=58) Steelhead trout stock group Entire study area Est. SD Columbia and Snake Rivers 0.00 North and Mid Oregon coast (Nehalem, Siletz, Alsea, Umpqua, Coos, and Coquille Rivers) 1 0.03 South Oregon coast (Elk, Rogue, Chetco, and Winchuck Rivers) 53 0.08 Smith, Klamath, and Trinity Rivers 0.00 North California Coast (Mad, Eel, and Ten Mile Rivers) 10 0.05 Sacramento and San Joaquin Rivers 14 0.05 Central and South California Coast (San Lorenzo River and Scott, Pauma, and Gaviota Creeks 3 0.02 Unknown 19 — hatcheries in the Umpqua River (n=5), Rogue River (n=l), and Columbia River (n=2) were in our study area. Genetic analysis of steelhead samples showed that a large proportion were from the Rogue River and nearby coastal streams (53%, SD=0.08). Steelhead from the Sacra- mento and San Joaquin rivers (14%, SD=0.05) and north- ern California coastal rivers (10%, SD=0.05) were also present. Estimates for steelhead originating from rivers north of Cape Blanco and from south of the San Francisco Bay were near zero. Approximately 19% of the steelhead mixture was not allocated to any source population, sug- gesting that our baseline data for the species is incomplete. No steelhead in our collections contained CWTs. Species associations of juvenile salmonids and other species From cluster analysis of species based on station assem- blages (Fig. 6), MRPP of both sample periods showed strong within-group agreement (P<0.0001) at the first level (two groups); all subsequent groups had sequentially higher levels of within-group agreement. As a result, the cutoff level was determined by balancing a lower percent infor- mation remaining (<30%) in the model while retaining bio- logically meaningful groups. For June this cutoff resided at the second level (three groups) and for August, at the third level (four groups ). For the June cruise, all salmonids includ- 38 Fishery Bulletin 102(1) 1 A I 127° i 122" 1 117"W — 50°N Vancouver "~-~~ Island ^fc--- B.C. - Pacific Ocean Olympic Peninsula Puge! ^ Sound , r" r£*\ •/ - 46" Columbia R -5sk^ "X Columbia R L wA J Snake R _ — 42" N -38" ^ Newport Cape Blanco / ,-.-, / • Yj Crescent City vC7 Eel R. /\\ I s" Umpqua Rogue R CU / o> r /, 3 ) A 3 ( L- o \ ;o V i R. 1 OR V ID CA 3 arvJ u 1 1 1 1 00 200 km I B 1 1 127- 122- 1 117"W June -so-N entire study area .^^ - © f|°oo ~ 46 ' August north of Cape Blanco ° o o 7\ - 4 -' W i August south of #•'-. i Cape Blanco i # • 100 200 km 1 1 •• 1 1 — 50* N c — r 132" 127° 122° ' 46 'June and August entire study area — 42" O • N J_ _L J. Figure 5 (A) Map of study area and location of GLOBEC sampling (hatching). (B) Stock compositions of chinook salmon (Oncorhynchus tshawytscha). Stock groups are North of Columbia River (grey), Columbia River Basin (green), north Oregon coast (pink), mid Oregon coast (yellow), south Oregon coast (dark blue), Klamath River Basin (black), north California coast (light blue), and Central Valley (red). (C) Stock compositions of coho salmon (O. kisutch). Stock groups are Columbia River (green), mid and north Oregon coast (dark pink), Rogue and Klamath rivers (blue), and north California coast (orange). Brodeur et al.: Distribution, growth, condition, origin, and associations of juvenile salmonids 39 June 100 Information remaining (%) 75 50 25 H 1 1 1 H Coho Chinook (a) Wolfeel Chinook (j) Lmgcod Steelhead Sablefish Market squid Whitebait smelt Pacific herring Surf smelt Darkblotched rockfish — , Yellowtail rockfish — T~ Rex sole — Speckled sanddab — i August 100 r- Information remaining (%) 75 50 25 H 1 1 1 h i Coho (a) Coho (j) Chinook (a) Chinook (j) Surf smelt Steelhead Medusafish Pacific saury Wolfeel Osmeriid (j) Blue shark Northern anchovy Rex sole Chub mackerel Pacific sardine Jack mackerel Figure 6 Cluster species groupings by cruise. The dashed lines indicate the cutoff levels for each cluster group. See Table 1 for scientific names. i> ing steelhead were classified within the same grouping that included several pelagic juvenile taxa, including wolf-eel, lingcod, and sablefish (Fig. 61. Two other clusters that were not associated with juvenile salmon included a southern inshore group consisting of market squid. Pacific herring, and two species of smelt and an offshore northern group consisting primarily of juvenile rockfish and rex sole. For the August cruise, all salmonid juveniles and adults again clustered together in one large group with surf smelt and medusafish ( Fig. 6 ). The remaining three groups were much smaller and consisted primarily of offshore pelagic species. Cluster analysis of stations based on species assem- blages, and subsequent examination of the cutoff level us- ing MRPP, resulted in three groupings from both sample periods (Fig. 7). MRPP revealed strong within-group agreement for all levels (P<0.0001); however, delineation at three groups was based on maintaining lower percent in- formation remaining (<30%) and still having a meaningful level of resolution. There was some measure of geographic separation among the three groups (Fig. 7). In June, group A was predominantly inshore and mostly in the southern half of the sampling area, group B was found mainly in the middle shelf region and was more northern, and group C was found predominantly offshore. In August, group A consisted of only three stations, all south of Cape Blanco, whereas groups B and C both spanned the entire shelf and offshore region and had no particular north-south affin- ity (Fig. 7). ISA of the groups from both sampling periods showed that only groups A and C had indicator species (Tables 6 and 7), whereas the intermediate groups had none. Ordination analyses and environmental correlates NMS ordination of the June sampling period (Fig. 8A) revealed most of the variance in the data: axes 1 and 40 Fishery Bulletin 102(1) June 2000 AAAAAn] a 44.5- □ A * rw 44.0- cPa A a n nrriAAA d 43.5- n nriAA'fY/ • 43.0- A \ D AA \ ( □□ ao/ duster Groupings 42.5- ' Group A O , Group B A aA Group C [ 42.0- OnA , , , i i , , , , 1 42.0- August 2000 rr D| &A A 125.5 125.0 124.5 124.0 1235 125.5 125.0 124.5 124.0 123.5 Longitude (W) Figure 7 Map showing locations of cluster station groupings by cruise. Table 6 Indicator species analysis showing indicator values for dominant pelagic nekton captu mean, standard deviations (SD), and P- values for each cluster grouping. Cluster Group mined to be indicators of that group. •ed in pelagic trawls during June 2000 and B did not have any species that were deter- Group Species Observed indicator value (IV) Indicator value IV from randomized groups P-value Mean SD A chinook (age 0.0 1 61.0 15.7 6.54 <0.001 A lingcod 26.1 12.6 5.67 0.024 A Pacific herring 71.7 12.8 5.88 <0.001 A surf smelt 86.5 11.8 5.59 <0.001 A whitebait smelt 31.5 10.4 5.55 0.007 A market squid 50.8 15.0 6.20 <0.001 C darkblotched rockfish 66.8 1 5 8 6.31 <0.001 C rex sole 46.0 15.0 6.24 0.002 C sablefish 31.1 16.2 6.32 0.035 C speckled sanddab 52.5 13.4 5.94 0.001 C yellowtail rockfish 98.8 19.0 6.30 <0.001 3 represented 31% and 237f, respectively (stress=16.3). Temperature, depth and salinity best explained the ordi- n;it ion of stations, representing a cross shelf gradient from nearshore high levels of salinity to increasing temperature and depth offshore. Ordination of August stations (Fig. 8B) represented 42' i of the variance in the data, and 23% of the variance was loaded on axis 2 and 19% on axis 3 (stress=19.4). As with June, salinity increased toward the coast and temperature and depth increased off the shelf. The groups derived from the cluster analysis tended to group together in multivariate space, with the exception of group B in the June cruise (triangles in Fig. 8A). Brodeur et al.: Distribution, growth, condition, origin, and associations of |uvenile salmonids 41 Table 7 Indicator Species Analysis showing indicator values for dominant pelagic nekton captured in pelagic trawls during August 2000 and mean, standard deviations (SD), and P-values for each cluster grouping. Cluster Group B did not have any species that were determined to be indicators of that group. Group Species Observed indicator value (IV) Indicator value IV from randomized groups P-value Mean SD A chinook (age 1.0) 76.5 21.3 11.18 0.004 A A chinook (age 0.0) surf smelt 80.4 97.9 22.1 12.4 11.62 8.21 0.003 <0.001 C chub mackerel 33.3 12.8 8.88 0.021 C jack mackerel 73.7 23.0 11.86 0.006 Table 8 Results of statistical tests for habitat associations between juvenile salmon and environmental or station variables from each cruise in 2000. Fish marked by zeros indicate subyearlings and those marked with one indicate yearlings. Shown are the P-levels for 5000 randomizations of the cumulative frequency of the habitat variable and the proportion of the standardized salmon catch associated with each habitat observation. Results are based on the Cramer von-Mises test statistic determined from binned data for depth and neuston biomass. Significance values <0.05 are shown in boldface. Cruise Jun Aug Taxon and age Surface temp. Surface salinity 1-m chlorophyll Bottom depth Neuston biomass chinook (age 1.0) 0.30 0.60 0.13 0.18 0.13 coho (age 1.0) 0.33 0.48 0.21 0.17 0.31 chinook (age 0.0) 0.36 0.25 0.13 0.35 0.42 chinook (age 1.0) 0.04 <0.01 <0.01 0.02 0.29 coho (age 1.0) 0.68 0.04 0.07 0.02 0.45 There were few instances where the habitat associations of juvenile salmon were significantly different from the distribution of environmental variables sampled (Table 8). None of the variables were significant for yearling chinook and coho salmon in the June sampling (no subyearling salmon were caught during that cruise). In August, all the variables except neuston biomass were significant for yearling chinook salmon. These fish were collected at cooler temperatures, higher salinities, higher chlorophyll-o con- centrations, and at shallower depths than have been typi- cally recorded (Fig. 9). Coho salmonjuveniles were found in higher salinities and shallower depths than at the sampled habitat (Fig. 9). These results correlated with the capture of juvenile chinook salmon and to a lesser with extent coho salmon at nearshore stations in the upwelling zone. Discussion Understanding the mechanisms underlying the dynamics of multispecies communities is one of the biggest challenges in ecology. Most communities contain many interacting spe- cies, each of which is likely to be affected by multiple biotic and abiotic factors. In order to effectively characterize a system, we need to differentiate variability resulting from both temporal and spatial factors. Our observations took place during two time periods of about 20 days each and thus were not synoptic "snapshots" of the system. Indeed, during our June sampling, conditions changed markedly from the beginning to the end of the cruise because of the arrival of an anomalous major southwest storm ( Batch- elder et al., 2002), which likely completely altered the hydrography and biology of the system. Thus, short-term temporal variability may obscure patterns observed over the spatial scale of our sampling. The pelagic nekton community sampled during these cruises was not that different from what had previously been shown for purse seine and trawling collections off the coast of Oregon and Washington ( Brodeur and Pearcy, 1986; Emmett and Brodeur, 2000; Brodeur et al., 2003). The early summer nekton community was dominated by coastal forage fishes such as smelts and Pacific herring, but also comprised juveniles of many rockfish, sculpin, and flatfish species. These winter-spring spawning species eventually settle out to demersal habitats sometime in summer (Shenker, 1988; Doyle, 1992), which may in part explain the paucity of these taxa in the August cruise. In contrast, the August nekton community consisted of large, 42 Fishery Bulletin 102(1) highly migratory species such as Pacific sardines, jack mackerel, and chub mackerel. Pacific sardine, which was almost completely absent from the system in the 1980s, has undergone a substantial resurgence and is now one of the most abundant species off the coast in summer (Brodeur et al., 2000; Emmett and Brodeur, 2000; McFarlane and Beamish, 2001). It should be noted, however, that some of the differences between cruises could be accounted for by the inclusion of substantially more offshore stations during A; a a REXS SPSD cr A A A 3 A U STHD t A MASO o WBSM DBRF °-,YTRF D cP SABF A Temperature Depth , Salinity n n LGCD - <% PHER »* D d 1 CHIN1 COHO A A * 1 Axisl (r 2 =0.31) CO CO X < B A A * A * REXS A D STHD A COHOA A D a coftoj D A a D -Depth a Salinity D Temperature CHINO BLSH OSMJ ° CO CD PSAR CHIN1 O o a o ^OEL a °0 CO o Axis 2 (r 2 =0.23) Figure 8 Nonmetric multidimensional scaling (NMS) ordination plot of stations and nekton species with environmental parameters from June (A) and August (B) 2000 GLOBEC cruises. Station symbols denote: onshore tO>. mid-shelf !▲). and slope (D) groupings; Species abbreviations denote the following taxa: CHIN (chinook, age 0), CHIN 1 (chinook, age al.ll, STHD (steelhead trout). SUSM (surf smelt), PSAU (Pacific saury), WOEL (wolf-eel juvenile), OSM J (osmerid juvenile), REXS (rex sole, larval i, MEDF (medusafish ), PSAR (Pacific sardine), .JAMA (jack mack- erel), CHMA (chub mackerel), NANC (northern anchovy). BLSH (blue shark). the second cruise. Our results from the community analy- ses suggest that juvenile salmon tend to co-occur with each other and with a variety of other pelagic nekton, including adult salmon, and that this spatial overlap varies tempo- rally. Brodeur et al. (2003), in analyzing community struc- ture based on previous pelagic sampling data off Oregon and Washington, arrived at similar results. In both studies, the geographic boundaries of the pelagic assemblages often overlap and are not as distinct as demersal assemblages. However, the pelagic environment is much more spatially and temporally heterogeneous than the demersal environ- ment, and many of the species examined in our study are highly mobile and are likely to respond quickly to changing conditions. Research is presently underway to examine the trophic interactions among salmonids and with other sym- patric nekton species in order to determine what ecological relationships (e.g. predation, competition), if any, are occur- ring in this system. From the results of our sampling, we concluded that ju- venile salmonids, with the possible exception of steelhead, occupy the cool, high salinity, inshore upwelling regions off the southern Oregon coast. However, particularly for the June cruise, many of the coho and chinook salmon juveniles collected may have recently entered the ocean with little time to disperse offshore, so that the capture location may not reflect true habitat preferences. Moreover, the vertical dimensions of our trawl also precluded us from sampling the nearshore, subtidal regions where some subyearling chinook may reside shortly after entering the ocean. Salmon and steelhead differed considerably in stock com- position. The pattern for coho salmon was similar to that of chinook salmon in that fish from sources both north and south of Cape Blanco contributed to our catches. However, steelhead from rivers north of Cape Blanco were absent, presumably having migrated offshore and north shortly after entering the sea, as shown by Pearcy et al. (1990). Although our stock composition estimates for steelhead should be viewed with caution because of an incomplete ge- netic baseline and a relatively small number of samples, our findings support Pearcy et al.'s suggestion that steelhead from rivers south of Cape Blanco have a unique marine distribution and reside throughout the summer in the up- welling zone off northern California and southern Oregon. Our study revealed seasonal shifts in the abundance and stock composition of juvenile salmonids. Although salmo- nids comprised small portions of the vertebrate catches of both the June and August cruises, juvenile chinook salmon, coho salmon, and steelhead were much more abundant later in the summer, likely indicating that fish moving into our study area are from shoreline or riverine habitats. The greater abundance of chinook salmon in late summer can be explained in part by the northern migration offish that originated in rivers south of our study area. Chinook salmon from the Sacramento and San Joaquin rivers in California's Central Valley comprised substantial propor- tions in the August catches both south (20%) and in nth i 90' i ) of Cape Blanco. In contrast, the few chinook salmon caught in June were mostly (549r ) from streams that en- ter the sea immediately north of Cape Blanco such as the Umpqua, Coquille, Sixes, and Elk rivers. Chinook salmon Brodeur et al.: Distribution, growth, condition, origin, and associations of juvenile salmonids 43 E o •Chinook 1 Coho 1 .0 -Habitat 12 14 Water temperature (C) j ■*" 09 - ~~, r. ..---' OR - , * 07 - / ■" . .. 06 - r- ' 05 - r' 04 - 03 - - -Chinook 1 02 - f J " Coho 1 n 1 - 1 V Habitat n - 10 15 Chla concentration 1 09 08 07 06 0.5 04 03 0.2 1 31.50 J i - - -Chinook 1 X ' Coho 1.0 Habitat Y 1 ^ } # > ,' 4 ja _ _ _ J 3250 3300 Salinity (PSU) •Chinook 1 -Coho 1.0 -Habitat 100 150 200 Water depth (m) Figure 9 Cumulative distribution curves for salmon and environmental or station variables. Only the August variables that showed at least one significant difference are included. See Table 8 for results of the statistical tests. from these rivers are known to primarily migrate north of our study area along the coast (Nicholas and Hankin, 1988). By August, fish from these stocks were nearly absent from our samples. Oregon rivers south of Cape Blanco, an area that includes the Rogue, Chetco, and Winchuck riv- ers, produce chinook salmon with a more southerly pattern of ocean migration (Nicholas and Hankin, 1988; Myers et al., 1998). Chinook salmon from these rivers were found throughout the summer and contributed 53% to our largest catches of chinook salmon along transects south of Cape Blanco in August. Results from our 2000 GLOBEC cruises identified Cape Blanco as an important breakpoint in salmonid life-his- tory variation. Stock distributions of both juvenile salmon and steelhead indicated that different migration patterns of fish originating from southern and northern rivers are evident during their early marine phase. Our August sur- vey also revealed sharp contrasts in life-history type and freshwater origin between the juvenile chinook salmon population in the marine area north of Cape Blanco and that to the south. Chinook salmon captured north of Cape Blanco were nearly all yearlings and largely from the Sac- ramento River drainage. Subyearlings predominated in our catches south of Cape Blanco and included a much larger proportion offish from coastal streams in southern Oregon and northern California. Comparisons of our results with similar studies conduct- ed further north show differences in salmonid migrations on a somewhat broader geographic scale. In several years of sampling during the summers of 1981 through 1985 off the central Oregon to northern Washington coast, most juvenile chinook salmon bearing CWTs were from Columbia River hatcheries (Pearcy and Fisher, 1990; Fisher and Pearcy, 1995). Only one tagged chinook salmon from a river south of Cape Blanco (Klamath River) was captured. Pearcy and Fisher also found that juvenile coho salmon were largely from the Columbia River and that smaller contributions were from coastal rivers north of Cape Blanco. Their find- ings have been corroborated by more recent surveys in the same region (Emmett and Brodeur, 2000) using genetic 44 Fishery Bulletin 102(1) data (Teel et al., 2003). Samples from subsequent cruises will be used to examine the persistence of such fine- and broad-scale geographic structure in the juvenile migrations of salmonid stocks. A major source of error in our estimates of growth rates of juvenile coho salmon back-calculated from scales was uncertainty of when individual fish entered the ocean. We used a single date of ocean entry for all fish (15 May), but individual fish, of course, entered the ocean at different times over the course of a month or more. Consequently, coefficients of variation were relatively large (84—119% and 75-120% of mean growth rate in FL and weight, respec- tively) for fish caught in May and June, when errors in es- timated growth periods likely were large in relation to the actual growth periods. Conversely, coefficients of variation were relatively small ( 14-30% and 10-26% of growth rate in FL and weight, respectively) for fish caught in August or September, when errors in estimated growth periods likely were small in relation to the actual growth periods. (Note the decrease in standard deviation of mean growth rates with month of capture in Tables 3 and 4A). Growth rates of CWT coho salmon between hatchery release and capture in the ocean (Table 4B) were very similar to the growth rates of unmarked salmon estimated from scales for the same months and areas. In addition, the growth rates of the former group ( CWT coho salmon ) helped to validate the growth rates of the latter group (Table 4A). Significant differences in growth and condition of ju- venile coho salmon indicate that different oceanographic environments exist north and south of Cape Blanco. The length of the fish indicated that substantial growth oc- curred in juvenile coho salmon during the study period. As- sessment of other growth features (condition) revealed that juvenile coho salmon grew better north of Cape Blanco. Because we included measurement of condition in both the June and August period in the evaluation, changes in stock composition, described earlier, may be partly responsible for this observation. Although genetic stock composition was different between months, month of sampling was not a significant factor, suggesting that stock composition is not likely a significant factor affecting the difference in condition (a performance metric) of juvenile salmon north and south of Cape Blanco. Several lines of evidence further support the hypothesis that areas north of Cape Blanco benefit juvenile yearling chinook and coho salmon. There were greater numbers of juvenile yearling chinook and coho salmon to the north of Cape Blanco. Although our overall sampling effort was greater north of Cape Blanco, in the mesoscale portion of our survey designed to assess general distribution patterns, more yearling chinook and coho salmon were captured north of Cape Blanco. Secondly, when we evaluated the growth rate of juvenile coho salmon in the GLOBEC region compared to juveniles captured off northern Oregon and Washington, juveniles from the GLOBEC region grew much better. The similar tracking of resource (distribution and abundance) and performance (measured in terms of either somatic and energetic growth or growth rate) metrics for juvenile yearling chinook salmon and coho salmon ninth of Cape Blanco suggests that habitat quality in this region was better. The results of this study help define the biogeo- graphical zones for salmon growth and establish regional- based management strategies for depleted salmon stocks. Acknowledgments We thank the captain and crew of the FV Sea Eagle for their expert help in conducting the trawling operations under sometimes adverse weather conditions. We are grateful to Jackie Popp-Noskov, Paul Bentley, Marcia House, and Becky Baldwin for assistance in field sampling. Donald Van Doornik and David Kuligowski collected the genetic data. We thank Anne Marshall for the use of unpublished chinook salmon allele frequency data. Stephen Smith and Alex De Robertis helped with the statistical analy- sis. Earlier versions of this manuscript were improved by the helpful comments of two anonymous journal reviewers. Research was conducted as part of the U.S. GLOBEC program and was jointly funded by the National Science Foundation (Grant no. OCE-0002855) and the National Oceanic and Atmospheric Administra- tion (NOAA). We also acknowledge the Bonneville Power Administration for funding the plume study. Literature cited Aebersold, P. B., G. A. Winans, D. J. Teel. G. B. 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Weitkamp, L., and K. Neely. 2002. Coho salmon [Oncorhynchus kisutch I ocean migration patterns: insight from marine coded-wire tag recoveries. Can. J. Fish. Aquat. Sci. 59: 1 100- 1 1 1 5. Weitkamp, L. A., T. C. Wainright, G. J. Bryant, G. B. Milner, D. J. Teel, T G. Kope, and R. S. Waples. 1995. Status review of coho salmon from Washington. Oregon, and California. NOAA Tech. Memo. NMFS- NWFSC-24, 258 p. Appendix Table 1 Summary of releases of coho salmon smolts in 2000 by region. This summary of releases of all hatchery coho salmon smolts by region was calculated from data in the Pacific States Marine Fisheries Commission Regional Mark Information System (http://www.rmis.org/ [accessed 5 April 2003]) and in USFWS 2001 (see Footnote 2 in the general text). No. of release groups ToHl fish Release weight (gl released Marked mean I SD ) All British Columbia 250 13,612,715 71.4', 19.6(5.7) Washington: St. Juan de Fuca, Puget Sound, Skagit River, Nooksack River, etc. 83 15,316,299 86 r, 29.1 (19.7) Washington: North of Columbia River to Cape Flattery 63 7,630,257 76 7', 31.6(5.3) Columbia River 140 29,879,137 89.09i 32.0^ 1 Oregon Coast north of Cape Blanco 14 809,962 95.69! 41.6(7.41 Southern Oregon and Northern California: Rogue, Klamath, and Trinity Rivers 5 745.060 99.8^' 42.1 (4.4) ' 100% of the fish released from Klamath and Trinity Rivers were clipped on the maxillary. 47 Abstract— Between June 1995 and May 1996 seven rookeries in the Gulf of Cali- fornia were visited four times in order to collect scat samples for studying spa- tial and seasonal variability California sea lion prey. The rookeries studied were San Pedro Martir, San Esteban. El Rasito, Los Machos, Los Cantiles. Isla Granito, and Isla Lobos. The 1273 scat samples collected yielded 4995 otoliths (95.3%) and 247 (4.7%) cepha- lopod beaks. Fish were found in 97.4% of scat samples collected, cephalopods in 11.2%, and crustaceans in 12.7%. We identified 92 prey taxa to the species level, 11 to genus level, and 10 to family level, of which the most important were Pacific cutlassfish (Trichiuruslepturus), Pacific sardine (Sardinops caeruleus), plainfin midshipman (Porichthys spp. ), myctophid no. 1, northern anchovy (Engraulis mordax). Pacific mackerel (Scomber- japonicus), anchoveta (Ceten- graulis mysticetus), and jack mackerel (Trachurus symmetricus). Significant differences were found among rooker- ies in the occurrence of all main prey (P<0.04), except for myctophid no. 1 (P>0.05). Temporally, significant dif- ferences were found in the occurrence of Pacific cutlassfish, Pacific sardine, plainfin midshipman, northern an- chovy, and Pacific mackerel (P<0.05). but not in jack mackerel lx 2 =2.94, df=3, P=0.40 1, myctophid no. l(;r= 1.67, df= 3, P=0.64 ), or lanternfishes ( x 2 =2.08, df=3, P=0.56). Differences were observed in the diet and in trophic diversity among seasons and rookeries. More evident was the variation in diet in relation to availability of Pacific sardine. Spatial and temporal variation in the diet of the California sea lion (Zalophus californianus) in the Gulf of California, Mexico Francisco J. Garcia-Rodriguez David Aurioles-Gamboa Centra Interdisciplinary de Ciencias Mannas-lnstituto Politecnico Nacional Departamento de Biologia Manna y Pesquerias Apdo. Postal 592 La Paz, Ba|a California Sur, Mexico E-mail address (for F J. Garcia-Rodriguez) fjgrodriifflcibnor.mx Manuscript approved for publication 9 October 2003 by Scientific Editor. Manuscript received 20 October 2003 at NMFS Scientific Publications Office. Fish. Bull. 102:47-62 (2004). The population of the California sea lion (Zalophus californianus), in the Gulf of California numbers approxi- mately 23,000 individuals, 82% of which inhabit the northern region of the gulf above latitude 28° (Aurioles- Gamboa and Zavala-Gonzalez, 1994). In this region are found the most important reproductive areas and the highest pup production of the Gulf. Aurioles-Gamboa and Zavala-Gonzalez (1994) suggested that the high con- centration of animals in this region is related to high abundance of pelagic fish such as Pacific sardine (Sardinops caeruleus) (also known as South Ameri- can pilchard, FAO), Pacific mackerel (Scomber japonicus). Pacific thread herring (Opisthonema libertate), and anchoveta (Cetengraulis mysticetus) (Cisneros-Mata et al., 1987 1 ; Cisneros- Mata et al., 1991 2 ; Cisneros-Mata et al., 1997 3 ). Despite the importance of the north- ern gulf region, feeding studies of the California sea lion at Gulf of California rookeries have been few and have been conducted at different time periods. Researchers have studied sea lion diet in Los Islotes (Aurioles-Gamboa et al., 1984; Garcia-Rodriguez, 1995), Los Cantiles (Isla Angel de la Guarda), Isla Granito (Sanchez-Arias, 1992; Bautista- Vega, 2000), and Isla Racito (Orta-Davi- la, 1988). These studies have shown that sea lions consume a variety of prey and that differences exist between the diet of sea lions found at different rookeries within the Gulf of California. At Los Islotes, the most important prey were cusk eel (Aulopus bajacali), bigeye bass (Pronotogrammus eos), threadfin bass (Pronotogrammus multifasciatus), and splitail bass (Hemanthias sp.) (Aurioles- Gamboa et al, 1984; Garcia-Rodriguez. 1995). At Los Cantiles and Isla Granito important prey were lanternfish (Dia- phus sp.), northern anchovy (Engraulis mordax). Pacific cutlassfish (Trichiurus nitens), shoulderspot (Caelorinchus scaphopsis), and Pacific whiting (Mer- luccius productus) (Sanchez-Arias, 1992; Bautista-Vega, 2000), whereas at Isla Racito, important prey were Pacific sardine (Sardinops caeruleus). Pacific mackerel (Scomber japonicus), grunt (Haemulopsis spp.), rockfish (Sebastes 1 Cisneros-Mata, M. A.. J. P. Santos-Molina, J. A. DeAnda M.,A. Sanchez-Palafox, and J. J. Estrada. 1987. Pesqueria de sardina en el noroeste de Mexico ( 1985/86 ). Informe Tecnico, 79 p. Centro Regional de Inves- tigaciones Pesqueras de Guaymas. INP. SEPESCA. Calle 20 No. 605 Sur Col. La Cantera. Guaymas, Son. CP. 85400. 2 Cisneros-Mata, M. A., M. O. Nevarez- Martinez, G. Montemayor-Lopez, J. P. Santos-Molina, and R. Morales- Azpeitia. 1991. Pesqueria de sardina en el Golfo de California de 1988/89-1989/90. Informe Tecnico. 80 p. Centro Regional de Investigaciones Pesqueras de Guaymas. INP. SEPESCA. Calle 20 No. 605 Sur Col. La Cantera. Guaymas, Son. CP. 85400. 3 Cisneros-Mata, M. A., M. O. Nevarez- Martinez, M. A. Martinez-Zavala, M. L. Anguiano-Carranza, J. P. Santos-Molina, A. R. Godinez-Cota, and G. Montemayor- Lopez. 1997. Diagnosis de la pesqueria de pelagicos menores del Golfo de Califor- nia de 1991/92 a 1995/96. Informe Tecnico, 59 p. Centro Regional de Investigaciones Pesqueras de Guaymas. INP. SEMARNAP. Calle 20 No. 605 Sur Col. La Cantera. Guavmas, Son. CP. 85400. 48 Fishery Bulletin 102(1) spp. ), and Pacific whiting (Merluccius spp. ) (Orta-Davila, 1988). Some California sea lion prey are important fisheries resources in Mexico. The Pacific sar- dine, for example, is the target of a fishery be- gun in 1967 and which, along with the northern anchovy, contributed to most of the volume of the catch (200,870 t during the 1995-96 season) obtained in the Gulf (Cisneros-Mata et al. 3 ). The central and northern regions of the Gulf of California harbor the greatest abundance of sea lions and schooling fishes, such as the sar- dine and anchovy. Because of this, knowledge of sea lion feeding habits and their temporal and spatial variability is relevant to understanding the potential interaction between sea lions and fisheries in the area (Orta-Davila, 1988; San- chez-Arias, 1992; Bautista-Vega, 2000). In this article, we present the results of concurrent diet studies conducted at various rookeries and haulout areas of sea lions in the northern rookeries of the Gulf of California to examine the prey consumed, and spatial and temporal variability in their diet. Materials and methods 32° 28° 24° 20° 16° 12° Scat samples of California sea lions were collected at Isla San Pedro Martir (SPM, 28°24'00"N, 112°25'3"W), Isla San Esteban (EST, 28°42'00"N, 112°36'00"W), Isla Rasito (RAS, 28°49'30"N, 112°59'30"W), Isla Granito (GRA, 29°34'30"N, 113°32'15"W), Isla Lobos (LOB, 30°02'30"N, 114°. 28'30"W), and at two colonies of Isla Angel de la Guarda known as Los Machos (MAC, 29°20'00"N, 113°30'00"W), and Los Cantiles (CAN, 29°32'00"N, 113°29'00"W, Fig. 1). The total number of California sea lions in these seven rookeries was approximately 15,000 animals (that were hauled out) of which about 12.2% inhabit San Pedro Martir. 34.7% San Esteban, 2.8% El Rasito, 10.0% Los Machos, 8.7%. Los Cantiles, 11.0% Isla Granito, and 20.6% Isla Lobos (Aurioles-Gamboa and Zavala-Gonzalez, 1994). All the animals were spread out along the shoreline of each island, except at Isla Angel de la Guarda, where they were clustered within two areas: Los Cantiles, on the eastern shoreline and Los Machos on the western shoreline. Scat samples were obtained at reproductive and non- reproductive haulout areas between June 1995 and May 1996. At El Rasito, sampling was done only at one reproduc- tive area; fresh and dried samples were collected (Fig. 2). If for any reason a scat was not collected (because it was found in pieces or in poor condition), it was destroyed and the site was cleared to avoid collection during subsequent trips. All fresh and dried samples collected were pooled to represent each sampling period. We assumed that the diet information corresponded to a time period close to the col- lection trip, but some dried scats could have been deposited shortly after the last collection. Pacific Ocean 122° 118° 114° 110° 106° Figure 1 Map of Baja California showing location of California sea lion rook- eries that were studied in the Gulf of California. Scats were stored in plastic bottles and then dried shortly thereafter to prevent decomposition offish otoliths and other hard parts (which were used in subsequent prey identification) until the scats could be processed at a later date. The samples were processed by soaking in a weak biodegradable detergent solution for 1 to 7 days before being sifted through nested sieves of 2. 00-, 1.18-. and 0.5-mm mesh size. Fish bones and scales, eye lenses of fish and squid, otoliths, cephalopod beaks, and crustacean fragments were extracted from the samples. Cephalopod beaks were stored in 70% ethanol, and the other items were dried and stored in vials. Sagittal otoliths and cephalopod beaks were used to identify teleost fish and cephalopods, re- spectively. Identifications were made by using photographs and diagrams from Clarke (1962), Fitch ( 1966), Fitch and Brownell (1968), and Wolff (1984), as well as voucher specimen material from the 1) Center Interdiseiplinario de Marinas Ciencias (CICIMAR), 2) Instituto Tecnologico y de Estudios Superiores de Monterrey, Guaymas, 3) Los Angeles County Museum of Natural History, California, and 4) Centro de Investigacion Cientifica y de Educacion Superior de Ensenada (CICESE). Baja California, Mexico. Prey species identifed to family level were coded by using Garcia-Rodriquez and Aurioles-Gamboa: Spatial and temporal variation in the diet of Zalophus californianus 49 San Pedro Martir (SPM) 28° 24'- HA San Esteban (EST) 112°40' 112=38' 1 12=36' 112=34' 112=32' J L 28=44- 28=42' El Rasito (RAS) Angel de la Guarda 28=49' 113=40' 113=30' 113=20' 113=10' 113=00' I I i i i 29=30'- r^\ «— Los Cantiles (CAN) / (RAyHA) 29° 20'- A\ ^-. 29° 10- Los Machos (MAC)\ ^ (RA y HA) ^v \ M Isla Granito (GRA) Isla Lobos (LOB) 113' 34' 113° 33' i 29° 35'- s RA RA ha *\y 29=34'- 30=03'. 114=29' 1 114= 28 I | RA K HA - Figure 2 Location of sites where samples of California sea lion scats were collected at each island. RA = reproductive area; HA = haulout area. the family name plus a sequential number. Otoliths from prey species that were not identified to species, genus, or family level were coded with "fish species" plus a number. Three indices were used to describe the diet of sea lions. Percent number (PN) represents the percentage of the number of individuals for each prey taxon over the total number of individuals found in all scat samples. Percent of occurrence (PO) represents the percentage of scats hav- ing a given prey taxon and indicates the percentage of the population that is consuming a particular prey species. The third index, index of importance (IIMP) incorporates PN and PO and is defined as IIMP, 'T ^ u X (1) where x t = number of individuals of taxon z' in scatj; X = total number of individuals from all taxa found in scat J; and U = total number of samples with prey. The IIMP, developed for scat analysis (Garcfa-Rodriguez, 1999), was used to determine the importance of prey species, their spatial and temporal variation in the diet. 50 Fishery Bulletin 102(1) diversity of prey estimates, and measures of similarity among rookeries. Crustaceans were not incorporated into the IIMP index because it was not possible to quantify the number of individuals in the samples. We used the IIMP Index because it is less sensitive to changes in the number of prey in an individual scat com- pared to PN. For example, if a scat contains a single prey taxon, the IIMP does not change regardless of the number of individuals of that taxon, in that scat. However, as one increases the number of individuals of a given prey taxon in the scat, the PN will also increase for that prey. The IIMP allows each scat to contribute an equal amount of information, whereas PN can be dominated by a few scats with a large number of a single prey-taxon otoliths. In this manner the IIMP is similar to the split-sample frequency of ocurrence (SSFO) index, developed by Olesiuk (1993), where each scat is treated as a sampling unit and does not assume, as does PN, that the distribution of prey hard parts between scats is uniform. However, with the SSFO index, each prey taxon in a given scat is given an equal weight for that scat. If only one species occurs in a sample, its occurrence is scored as 1, if two species occur, each oc- currence is scored as 0.5, and so forth (Olesiuk, 1993). The IIMP index incorporates more information than the SSFO index, regardless of the number of individuals of each taxon in the scat. 4 Percent number (PN) was used only to show differences between broad prey groups (fishes and cephalopods) and PO was used to review the temporal and spatial changes from each main prey (those with average IIMP of at least 10% at any rookery). For all estimations, a single otolith (right or left) or single cephalopod beak (upper or lower) represented one individual prey. We tested the hypothesis that the occurrence of the main prey was independent of the rookery and of the date collection using contingency tables and an estimator of chi-square (x~) (Cortes, 1997). Total length of the otoliths (mm) and the linear equation obtained by Alvarado-Castillo 5 were used to estimate the length of the Pacific sardine (total length mm=7. 41+147. 24xotolith length mm); r=0.85, n=2740). Insufficient data did not allow estimating the size of speci- mens from May. All estimated lengths were transformed us- ing loglO, followed by an ANOVA among sampling periods. The size of Pacific sardine consumed by California sea lion was compared to those caught in the commercial fishery. We chose to estimate the size of Pacific sardines because of the broad information available concerning age and growth and other aspects about the fishery and because we found many sardine otoliths in good condition. Spatial and temporal correlation in composition of diet was compared by using the Spearman rank correlation co- 4 Garcfa-Rodriguez, F. J., and J. De la Cruz-Agiiero. In prep. An index to measure the specie prey importance of California sea lion ^Zalophus californianus) based on scat samples. 'Alvarado-Castillo, R. Unpubl. data. Departamento de Biologia y Pesquerias, Centro Interdisciplinary de Ciencias Marinas. Avenida IPN S/N Col. Palo Playa de Santa Rita, La Paz, Baja California Sur, Mexico 23070. efficient (R s ) (Fritz. 1974). Pairs of IIMP values were used for each prey taxon in a pair of sampling events (rookeries or sampling dates) to examine the correlation among them. This analysis was limited to prey that had an IIMP value of 10% or more. Cluster analysis of average IIMP data for the seven rookeries was used to assess the similarity of the diet among rookeries. The dendrogram for the cluster analysis was based on relative Euclidean distances and unweighted pair-grouping methods (UPGMA) strategy (Ludwig and Reynolds, 1988). We included only prey that, for at least one occasion, had IIMP values >10%. Trophic diversity was evaluated by using diversity curves (Hurtubia, 1973) developed from IIMP index data. For each date and colony, the cumulative diversity was calculated for increasing numbers of sequentially numbered (but we as- sumed randomly deposited and collected) scat samples. The diversity curves also allowed us to evaluate sample size (Hurtubia, 1973; Hoffman. 1978; Magurran, 1988, Cortes, 1997) by identifying the point at which the curve flattens. The diversity was estimated by using the Shannon index: H' -^P,\nPr (2) where H' = trophic diversity; S = total number of prey taxa; and P l = IIMP r and represents the relative abundance of taxon i obtained from each scat and pooled from scat 1 up to the total number of scats collected. The values of trophic diversity were then plotted against the number of pooled scats. Results Identification of prey The 1273 scat samples collected during June 1995 through May 1996 (Table 1) yielded fish remains in 97.4% of the samples, cephalopod remains in 11.2%, and crustacean remains in 12.7%. Fish and cephalopods represented 95.39; and 4.7%, respectively, of the 5242 individual prey (excluding crustaceans). The occurrence and number of these prey groups changed temporally and spatially (Fig. 3). We identified 92 prey taxa to the species level, 11 to the genus level, and 10 to family level from 851 scats (Table 2). Remaining scats had damaged prey structures in a condition that prevented us from identifying species to the genus or family level. We found nine main prey with IIMP average values a 10% (Table 3): the Pacific cutlassfish {THchiurus lepturus), the Pacific sardine (Sardinops eaeruleus), the plainfin mid- shipman (Porichthys spp.), myctophid no. 1, the northern anchovy iEngraulis mordax), Pacific mackerel {Scomber japonicus), the anchoveta (Cetengraulis mysticetus), jack mackerel iTrachurus symmetricus), and the lanternfish (unid. myctophid). Garcia-Rodriquez and Aurioles-Gamboa: Spatial and temporal variation in the diet of Zalophus californianus 51 Table 1 Number of scats collected at each rookery for each sampling period. June 1995 San Pedro Martir (SPM) SanEsteban(EST) ElRasito(RAS) Los Cantiles (CAN) IslaGranito(GRAl Los Machos (MAC) IslaLobos(LOB) Total 22 50 11 20 24 39 72 238 September 1995 January 1996 33 66 56 58 20 32 139 404 91 58 47 41 36 72 433 Mav 1996 29 67 25 35 19 23 198 Total 172 274 150 160 104 107 306 1273 Spatial and temporal variability of the main prey The importance (IIMP) of the Pacific cutlassfish was greater in Los Cantiles (28.4%), Isla Lobos (20.8%), and Isla Granito (48.5%) than at other sites (Fig. 4). The Pacific sardine was the dominant prey at Los Machos and to the south. There was a significant correlation across the sea- sons between Los Machos and El Rasito (r=0.998. P=0.04), but not between Los Machos and Isla Granito U-0.602, P=0.59). The IIMP of sardine was also correlated between El Rasito and San Esteban (r=0.95, P=0.04). The plainfin midshipman did not show a clear pattern, but its presence in the diet increased northeastward from Isla Angel de la Guarda. Lanternfishes, especially myctophid no. 1, were the dominant prey at San Pedro Martir, San Esteban, and El Rasito. The presence of Pacific mackerel was positively correlated with the presence of the Pacific sardine. The anchoveta was only found at Isla Lobos, and jack mackerel at El Rasito, San Pedro Martir, and Isla Granito. The changes in the PO of the main prey coincided with the variations of the IIMP. The occurrence of Pacific cut- lassfish. Pacific sardine, plainfin midshipman, northern anchovy, Pacific mackerel, and jack mackerel was signifi- cantly different (P<0.04) among rookeries. Myctophid no. 1 showed no significant difference in ocurrence 10% (Table 3) for a given collection. The Spearman rank correlation coefficient of IIMP between any pair of rookeries during June, September, January, and May was not significant (P>0.08). There was no positive correla- tion among any pair of sampling periods for any rookery (P>0.14), except between January and May at San Pedro Martir (P s =0.64, P<0.05) and El Rasito (P s =0.66, P<0.05) and between January and June as well as between Janu- ary and May at Isla Lobos (R s =0.56, P=0.05; and P s =0.59, P=0.05. respectively). The similarity in diet was related to the distance between rookeries. A clustering for the seven rookeries was obtained from these 25 prey taxa (Fig 6). We arbitrarily used a "cut- off" distance of 0.3 and 0.4 on the dendrogram as reference points for identifying clusters. The group obtained by us- ing the first distance (0.3) showed four feeding areas: one located in the south ( area I; San Pedro Martir, San Esteban, and El Rasito), another in Canal de Ballenas (area II: Los Machos) and two in the north (area III: Los Cantiles and Isla Lobos; and area IV: Isla Granito). When the second distance (0.4) was used, the seven rookeries grouped into two clusters: 1) the southern region and Canal de Ballenas, and 2) the region north of Angel de la Guarda. Spatial and temporal variability in trophic diversity Temporal variability in trophic diversity was evident between the rookeries (Fig. 7). In general, two patterns could be differentiated: one in which the diversity varied little throughout the year and the other in which diversity was high in January and low in September. The rookeries San Pedro Martir and Isla Lobos showed the first pattern and Los Machos and Isla Granito (and to a lesser extent, San Esteban and El Rasito) showed the second pattern. In September, when diversity was low, the dominant prey at 52 Fishery Bulletin 102(1) 100 80 60 40 20 100 T 80 60 40 20 0.- Percent number D Fishes Cephalopods JUNE 1995- MAY 1996 SPM EST RAS MAC CAN GRA LOB □ Fishes Cephalopods JUNE 1995 100 80 60 40 20 100 80 60 40 20 100 80 60 40 20 SPM EST RAS MAC CAN GRA LOB Fishes Cephalopods SEPTEMBER 1995 SPM EST RAS MAC CAN GRA LOB □ Fishes Cephalopods JANUARY 1996 SPM EST RAS MAC CAN GRA LOB □ Fishes Cephalopods MAY 1996 SPM EST RAS MAC CAN GRA LOB 100 80 1 60 40 1 20 100' 80 60 40' 20' 0. Percent occurrence Q Fishes Cephalopods □ Crustaceans JUNE 1995- MAY 1996 M XI Jl SPM EST RAS MAC CAN GRA LOB □ Fishes Cephalopods □ Crustaceans JUNE 1995 n n ^3*. SPM EST RAS MAC CAN GRA LOB □ Fishes Cephalopods D Crustaceans SEPTEMBER 1995 n Jl n 100, 80 60 1 40 1 20 SPM EST RAS MAC CAN GRA LOB O Fishes H Cephalopods D Crustaceans JANUARY 1996 SPM EST RAS MAC CAN GRA LOB D Fishes I Cephalopods D Crustaceans MAY 1996 n^Q SPM EST RAS MAC CAN GRA LOB Figure 3 Percent number (PNi and percent occurrence (POl index values for fishes, cephalopods, and crustaceans found in samples of California sea lion scats collected at seven rookeries in the Gulf of California, Mexico, for all sampling periods combined and for each sampling period. San Esteban, El Rasito, and Los Machos was Pacific sar- dine, whereas at Isla Granito, it was Pacific cutlassfish (Fig. 4 1. The curves obtained for Los Cantiles showed a clear pattern of diversity only in September, although the trend in the January curve would suggest a higher diver- sity in January than in September. Garcia-Rodriquez and Aurioles-Gamboa: Spatial and temporal variation in the diet of Zalophus califomianus 53 Table 2 Prey of California sea lion identified from scat samples collected at Isla San Pedro Martir, Isla San Esteban, Isla El Rasito, Los Cantiles, Isla Granito, Los Machos and Isla Lobos from June 1995 through May 1996. n ind. = = number of individuals in the sample; PN = percent number; n occurr = number of occurrences PO = percentage of occurrence; IIMP = index of importance. Scientific name Common name n Ind. PN n Occurr. PO IIMP Trichiurus lepturus Pacific cutlassfish 306 5.837 128 15.041 16.392 Sardinops caeruleus Pacific sardine 358 6.829 88 10.341 10.020 Porichthys spp. midshipman 456 8.699 95 11.163 9.297 Myctophid no. 1 lanternfish 714 13.621 119 13.984 7.901 Engraulis mordax northern anchovy 430 8.203 43 5.053 5.199 Scomber japonicus Pacific mackerel 103 1.965 42 4.935 3.403 Cetengraulis mysticetus anchoveta 410 7.821 15 1.763 2.404 Loliolopsis diomedeae squid 77 1.469 35 4.113 2.399 Trachurus symmetricus jack mackerel 111 2.118 41 4.818 2.273 Merluccius spp. Pacific whiting 55 1.049 25 2.938 2.206 Pontinus spp. scorpionfish 61 1.164 26 3.055 1.842 Enoploteuthid no. 1 squid 95 1.812 23 2.703 1.754 Caelorinchus scaphopsis shoulderspot 65 1.240 25 2.938 1.728 Octopus sp. no. 1 octopus 24 0.458 17 1.998 1.614 Sebastes macdonaldi Mexican rockfish 42 0.801 18 2.115 1.496 Citharichthys sp no. 1 sanddab 120 2.289 23 2.703 1.220 Fish species no. 1 — 49 0.935 25 2.938 1.153 Haemulopsis leuciscus white grunt 176 3.357 21 2.468 1.093 Peprilus snyderi salema butterfish 163 3.110 33 3.878 1.025 Prionotus spp. searobin 12 0.229 9 1.058 0.855 Prionotus stephanophrys lumptail searobin 53 1.011 14 1.645 0.814 Argentina sialis Pacific argentine 19 0.362 13 1.528 0.754 Fish species no. 2 — 55 1.049 27 3.173 0.737 Hemanthias peruanus splittail bass 60 1.145 22 2.585 0.602 Fish species no. 3 — 9 0.172 6 0.705 0.592 Micropogomas ectenes slender croaker 13 0.248 9 1.058 0.547 Lepophidium spp. cusk-eel 9 0.172 3 0.353 0.532 Fish species no. 4 — 10 0.191 3 0.353 0.511 Sebastes exsul buccanner rockfish 15 0.286 10 1.175 0.505 Cranchiid no. 2 Squid 20 0.382 12 1.410 0.501 Haemulon flaviguttatum yellowspotted grunt 11 0.210 3 0.353 0.468 Sela r cru men oph th aim us bigeye scad 24 0.458 12 1.410 0.431 Fish species no. 5 — 33 0.630 19 2.233 0.384 Paralabrax sp. no. 1 sea bass 9 0.172 5 0.588 0.373 Synodus sp. no. 3 lizardfish 10 0.191 3 0.353 0.341 Lepophidium prorates prowspine cusk-eel 5 0.095 4 0.470 0.335 Fish species no. 6 — 9 0.172 5 0.588 0.324 Synodus sp. no. 1 lizardfish 25 0.477 10 1.175 0.324 Octopus sp, no. 2 octopus 8 0.153 7 0.823 0.308 Gonatus berryi squid 5 0.095 5 0.588 0.274 Mugil cephalus striped mullet 1 0.019 1 0.118 0.265 Paranthias colonus Pacific creole-fish 1 0.019 1 0.118 0.265 Batistes polylepis finescale triggerfish 13 0.248 4 0.470 0.245 Physiculus nematopus charcoal mora 30 0.572 12 1.410 0.244 Hemanthias spp. sea bass 9 0.172 6 0.705 0.234 Fish species no. 7 — 10 0.191 8 0.940 0.233 Uroconger varidens conger eel 8 0.153 5 0.588 0.189 Larimus spp. drum 8 0.153 6 0.705 0.174 Apogon retrosella barspot cardinalfish 5 0.095 4 0.470 0.173 Dosidicus gigas squid 8 0.153 5 0.588 0.171 continued 54 Fishery Bulletin 102(1) Table 2 (continued) Scientific name Common name n Ind. PN n Occurr. PO IIMP Merluccius productus Pacific whiting 1 0.019 1 0.118 0.167 Fish species no. 8 — 2 0.038 2 0.235 0.159 Synodus sp. no. 2 lizardfish 12 0.229 5 0.588 0.132 Scorpaena sonorae Sonora scorpionfish 2 0.038 1 0.118 0.130 Eucinostomus spp. mojarra 13 0.248 5 0.588 0.129 Fish species no. 9 — 3 0.057 3 0.353 0.127 Cynoscion reticulatus striped weakfish 23 0.439 7 0.823 0.124 Fish species no. 10 — 10 0.191 1 0.118 0.122 Caulolatilus affinis bighead tilefish 4 0.076 3 0.353 0.114 Paralabrax auroguttatus goldspotted sand bass 18 0.343 4 0.470 0.110 Fish species no. 11 — 3 0.057 2 0.235 0.102 Cranchiid no. 5 squid 1 0.019 1 0.118 0.097 Bodianus diplotaenia mexican hogfish 1 0.019 1 0.118 0.087 Prionotus sp. no. 1 searonbin 2 0.038 2 0.235 0.087 Strongylura exilis California needlefish 1 0.019 1 0.118 0.083 Synodus spp. lizardfish 6 0114 5 0.588 0.146 Fish species no. 12 — 3 0.057 3 0.353 0.074 Fish species no. 13 — 2 0.038 1 0.118 0.065 Fish species no. 14 — 3 0.057 1 0.118 0.060 Fish species no. 15 — 2 0.038 1 0.118 0.058 Fish species no. 16 2 0.038 2 0.235 0.056 Porichthys sp. 1 midshipman 1 0.019 1 0.118 0.052 Fish species no. 17 — 5 0.095 3 0.353 0.049 Calamus brachysomus Pacific porgy 5 0.095 2 0.235 0.043 Fish species no. 18 — 1 0.019 1 0.118 0.042 Fish species no. 19 — 5 0.095 2 0.235 0.041 Ophididae no. 1 — 1 0.019 1 0.118 0.040 Fish species no. 20 — 5 0.095 3 0.353 0.039 Sebastes sinesis blackmouth rockfish 2 0.038 1 0.118 0.039 Symphurus spp. tonguefish 3 0.057 1 0.118 0.038 Fish species no. 21 — 2 0.038 1 0.118 0.036 Pronotogrammus multifasciatus threadfin bass 8 0.153 2 0.235 0.029 Fish species no. 22 — 2 0.038 2 0.235 0.027 Fish species no. 23 — 2 0.038 1 0.118 0.021 Orthopristis reddingi Bronze-striped grunt 16 0.305 1 0.118 0.020 Fish species no. 24 — 2 0.038 1 0.118 0.020 Fish species no. 25 — 1 0.019 1 0.118 0.016 Cranchiidae no. 4 squid 2 0.038 2 0.235 0.014 Fish species no. 26 — 2 0.038 2 0.235 0.014 Histioteuthis heteropsis squid 0.019 1 0.118 0.014 Scorpaenidae no. 1 — 0.019 1 0.118 0.011 Fish species no. 27 — 0.057 2 0.235 0.011 Fish species no. 28 — 0.019 1 0.118 0.010 Fish species no. 29 — 0.019 1 0.118 0.008 Cranchiidae no. 3 squid 0.019 1 0.118 0.006 Bollmannia spp. goby 0.019 1 0.118 0.006 Fish species no. 30 — 0.019 1 0.118 0.005 Cranchiidae no. 1 squid 0.019 1 0.118 0.004 Paralabrax maculatofasciatus spotted sand bass 0.019 1 0.118 0.003 Ophidian scrippsae basketweave cusk-eel 0.019 1 0.118 0.003 Physiculus spp. cod. codling, mora 2 0.038 1 0.118 0.003 Ophididae no. 2 — 4 0.076 1 0.118 0.002 Unid. Carangidae jacks 8 0.153 3 0.353 0.141 continued Garcia-Rodriquez and Aurioles-Gamboa: Spatial and temporal variation in the diet of Za/ophus californianus 55 Table 2 (continued) Scientific name Common name n Ind. PN n Occurr. PO IIMP Unid. Engraulidae anchovies 1 0.019 1 0.118 0.248 Unid. Haemulidae grunts 13 0.248 11 1.293 0.509 Unid. Labridae wrasses 1 0.019 1 0.118 0.005 Unid. Mycthophidae lanternifishes 216 4.121 71 8.343 4.895 Unid. Ophididae cusk-eel 2 0.038 1 0.118 0.098 Unid. Scianidae drums 13 0.248 9 1.058 0.643 Unid. Scorpaenidae scorpionfishes 30 0.572 18 2.115 1.078 Unid. Serranidae sea bass 13 0.248 6 0.705 0.176 Unid. Triglidae searobins 1 0.019 1 0.118 0.002 Unid. fishes 39 0.744 16 1.880 1.819 Unid. cephalopod 4 0.076 4 0.470 0.373 Unid. fishes (very eroded ) 381 7.268 231 27.145 Remains of cephalopods 14 1.645 Remains of crustaceans 162 19.036 Discussion Stomach acids attack otoliths, affecting their size and number and consequently the estimate of prey occurrence and importance. Erosion of otoliths during digestion has been analyzed in studies of pinnipeds in captivity. Bowen (2000) reviewed nine studies that estimated the propor- tion of otoliths recovered in scat samples to obtain a prey-number correction factor (NCF). He found that NCF is greater than 1.0 because many prey species are not recovered in the scat samples. Additionally, the erosion level can be significantly different among prey species (Bowen, 2000) because of differences in the shape and microstructure of otoliths. Therefore, estimates of biomass based on scat analysis should be carefully interpreted because the consumption of some prey species can be under- or overestimated. Correction factors are needed to compensate for differential erosion for the prey species of each pinniped. In this study the most important prey of California sea lions were pelagic fish with small, thin, and fragile otoliths (Nolf, 1993). The lanternfish also have small otoliths — perhaps smaller than those of any other prey taxa found in the scats. Their true importance in California sea lion feeding may be underestimated because of erosion caused by stomach acids (Da Silva and Neilson, 1985; Murie and Lavigne, 1985; Jobling and Breiby, 1986; Jobling, 1987; Toll- it et al., 1997). Similarly, the presence of cephalopods may have been underestimated because their jaws are composed of chitin, which is harder to digest, and frequently are re- gurgitated (Pitcher, 1980; Hawes, 1983). However, the high resistence to digestion of cephalopod beaks allows recovery of them in good shape. Thus they are a good choice to use in such diet analyses (Lowry and Carretta, 1999). A numerical index of prey species importance may over- or underestimate the dominance of prey species in the diet because it does not consider the weight of the prey. For IIMP, a numerical index that assumes a similar weight for all prey species, the true importance of the individual large prey in the diet can be underestimated and the importance of individual small prey can be overestimated. This prob- lem is also present when the PO, PN, and the SSFO index are used because these are all based only upon the number and occurrence of otoliths and cephalopods beaks. As when using PN. and the SSFO, the IIMP does not work for species that cannot be enumerated, such as crustaceans. Given the tendencies of the trophic diversity curves, the sample size was suitable in almost all cases. However, at San Pedro Martir a few more samples would have been useful to fully depict the diet. At Los Cantiles, except during September 1995, the samplings should have been more intense because the flattened portion of the diversity curves are not clear. The information, therefore, that comes from those samples could be biased. However, the number of scats that we analyzed contained a high percentage of the consumed species, especially the main prey. The results of this study indicate that the California sea lion consumed mainly fish and some crustaceans and cephalopods. According to the PN index, fish were more important than cephalopods in the diet of sea lions. In ad- dition, fish were more frequent (PO) than crustacean and cephalopods. Crustaceans were represented in a similar manner in scats from all rookeries. Cephalopods, however, were more important at San Pedro Martir and San Esteban, prob- ably because they are more common towards the southern gulf. Species of the suborder Oegopsida, which includes oceanic species (Roper and Young, 1975), were most com- monly found in scats from these rookeries. Orta-Davila (1988) and Sanchez-Arias (1992) have also noted the low consumption of cephalopods at the northern rookeries. Fish were the most diverse and commonly eaten prey. In contrast to cephalopods, fish were slightly less important in the southern region. The availability and abundance of the various prey resources influenced the diet of the sea lions in the Gulf 56 Fishery Bulletin 102(1) Table 3 Prey of California sea lions having IIMP index values alO^ in at leas t one sampling period for seven rookeries in the Gulf of Cali- fornia, Mexico Blank indicate that species were not recorded in diet; ' — " means unavailable data. Prey species June 1995 September 1995 January 1996 May 1996 Average San Pedro Engraulis mordax 29.7 2.1 0.5 8.1 Marti r myctophid no. 1 29.0 10.5 9.0 20.5 17.3 Porichthys spp. 11.2 2.0 6.8 15.5 8.9 Prionotus stephanophrys 0.6 3.3 3.3 10.9 4.5 enopleoteuthid no.l 27.3 0.8 7.0 Sebastes macdonaldi 10.4 2.6 Haeumulopsis leuciscus 16.7 6.0 5.7 San Esteban Trichiurus lepturus 24.9 3.4 3.0 7.8 Sardinops caeruleus 10.0 34.1 4.2 12.1 unid. Myctophidae 13.79 3.4 4.3 10.9 8.1 myctophid no. 1 2.8 11.8 8.9 18.8 10.6 enopleoteuthid no. 1 16.9 4.2 Sebastes macdonaldi 2.1 9.7 1.4 3.3 fish species no. 1 1.7 11.0 3.2 El Rasito Porichthys spp. 26.2 4.0 2.3 8.1 unid. Myctophidae 16.4 1.5 8.1 16.4 10.6 Scomber japonicus 13.8 3.2 3.7 2.5 5.8 Pontinus spp. 11.5 5.1 4.1 10.9 7.9 Octopus sp. no. 1 11.5 2.9 7.7 5.5 myctophid no. 1 6.6 5.1 21.4 6.8 10.0 Sardinops caeruleus 1.6 40.1 0.9 7.3 12.5 Trachurus symmetricus 22.0 5.0 23.4 12.6 Caelorinchus scaphopsis 3.6 13.5 10.5 6.9 Los Machos Sardinops caeruleus 21.0 64.1 16.8 — 34.0 Scomber japonicus 19.0 10.9 — 10.0 Merluccius spp. 15.4 8.2 — 7.9 Trichiurus lepturus 11.7 5.4 — 5.7 Sebastes macdonaldi 1.8 11.3 — 4.4 Los Cantiles Porichthys spp. 66.7 15.5 20.6 Trichiurus lepturus 22.2 38.2 53.1 28.4 Engraulis mordax 3.7 0.4 14.3 4.6 myctophid no. 1 17.6 4.8 5.6 Sardinops caeruleus 6.8 19.0 6.5 fish species no. 3 0.9 14.3 3.8 unid. fishes 0.9 19.0 5.0 unid. Scianidae 14.3 3.6 Lepophidium spp. 14. 3.5 Lo/iolopsis diomedcav 21.1 5.3 Isla Granito Engraulis mordax 49.3 7.8 14.3 Trichiurus lepturus 22.0 70.1 2.0 100.0 48.5 unid. myctophidae 1.7 1.1 12.6 3.9 Sardinops caeruleus 0.9 18.7 4.9 Porichthys spp. 0.5 18.2 4.6 5.8 Citharichthys sp. no. 1 21.7 5.4 Isla Lobos Cetengraulis mysticetus 32.7 0.1 6.8 27.8 16.9 Trichiurus lepturus 25.2 27.7 15.8 14.3 20.8 Porichthys spp. 9.0 10.3 23.2 35.5 19.5 Loliolopsis diomedeae 4.9 2.2 11.6 3.5 5.6 Peprilus snyderi 23.5 5.2 7.2 Garcia-Rodriquez and Aurioles-Gamboa: Spatial and temporal variation in the diet of Zalophus califomianus 57 100 80 60 SPM EST RAS MAC CAN GRA LOB 11111 Ml H l l i 1 ^_ ^B Trichiurus lepturus 20 « hJI L^l h^^^m. I a 5 fe'i a i fell a i fell Si ? fell & i fell & 5 fe'i & i | n 10 * SI 3 $ t SH to n Sl=5 to t Sin (0 t Sin to n 5 1 => to -> S 100 80 1 1 1 1 1 1 40 20 \_m i J - _« : _ i Sardinops caeruleus ■7 Q. ;r >- 1 Z Q_ Z >- 1 2 Q. z >- 1 z 0- Z >-'Z 0- Z >;! Z 0- Z >r'Z 0- z ^ 3 W * S't W 3 5 ' => co =5 5 ' =^ w> ^ 5 I= 3 « ^ 5 l= i W ^ 5' =5 w -> 5 100, 80 1 I 1 1 1 1 1 I 1 1 I 1 60 40 I ! - Porichthys spp 20 - | P- ' - ' — ^ iMI;ilil;iill;ili l;l ft i £;5 M 1;5 8l 1 100 80 60 40 20 Myctophidae no. 1 Z Cl Z >'Z 0- Z >"'z Q- Z V'z Q- Z i ' Z CL Z >' Z 0- Z b'z CL Z £ D 111 < (0 -» S -> CO ->5 CD C_> c a o Q. 1 CD CD ro c 100 80 60 40 20 Myctophidae z cl z >-'z n z v'zcl z v'z cl z >'z 0- z b'z cl z i'z cl z > i 8 1 1;1 8 1 i;l 8 1 S;i 8 1 I;3 8 1 3;3 8 1 I;r 8 1 i 100 80 60 Scomber japonicus o 20 __)■ Q_ z o. z v'z 0- z >-'z Q. z bz Q- z i'z Q. z >: ' z 0. z >: ' z Q- z >; TWn5TU)nS=50)-)S-iV)->S->WnS->W-)S->W-iS 100 80 60 40 20 ■_ Engraulis mordax Z 0. Z >-'z 0- Z >-'z D- z >-'z 0. Z i'z Q- z £ ' Z 0- Z £: Z 0. Z >: t CO n S =) CO * S ' =j 0) n So CO n S =3 CO n S =5 CO n S =i CO =3 5 100 80 40 20 -m Cetengraulis mysticetus i & i fell a s s!i a ? si? & s fell a i fell a i fell a ? | T CO n 5 n CO * S n CO n St » n S n (0 n St 0) n 5 ( => to -, S 100 80 40 20 ^_ _L ^_ _L _^ -L Trachurus symmetricus Z 0- Z >".Z tL Z >,Z D- Z >-.Z 0- Z >ZtZ 0- Z ^,Z 0- Z £,Z Q- Z 5j D S tf -t'D QJ < D Ul < to * S|=i CO t S,=5 to n S,n to t S,=i to n S r n W n S spm : est : ras : mac : can : GRA : LOB Figure 4 Index of importance (IIMP) for nine prey species identified from samples of California at seven rookeries in the Gulf of California, Mexico, during June and September 1995 sea lions scats collected . and January and May 1996. of California. The distribution pattern of Pacific sardine closely agrees with its importance in the sea lions diet. The Pacific sardine occurred in high concentrations around Angel de la Guarda and Isla Tiburon during the summer and along the coast of southern Sonora during the winter, where spawning occurs (Cisneros-Mata et al. 3 ). Sardines 58 Fishery Bulletin 102(1] were consumed in the Canal de Ballenas region during the summer (September), when they are very abundant. Larger size Pacific sardines were consumed by sea lions most frequently during the summer when adult sardines occur more frequently in the Canal de Ballenas. As adult sardine left Canal de Ballenas ( Cisneros-Mata et al., 1997 ), the proportion of young individuals in the diet of sea lions increased. The fish eaten by sea lions were apparently smaller than those captured by the commercial fisher- ies. The average estimated size of the sardines consumed was 150.4 mm, whereas the average size of commercially caught fish during the 1995-96 season was 162.4 mm (Cis- neros-Mata et al. 3 ). This 7% difference in size may have been caused by an underestimation of otolith size because of digestive erosion ( Jobling and Breiby, 1986). If this is so, then the size of Pacific sardines consumed by sea lions is similar to the size of those captured by the fishery. Isla Lobos was the only rookery where Pacific sardine was not consumed. This finding differs from those of Cisneros- Mata et al. 3 which show the Pacific sardines present as far north as Isla Lobos. However, their study period was during the 1991-92 El Nino episode, whereas our study occurred during normal oceanographic conditios in 1995-96. Less is known about the spatial and temporal availability of other important prey. As with commercial captures (Arvizu-Martinez, 1987), Pacific mackerel occurred together with Pacific sardine. Similar varia- tions in occurrence for both species have been noticed from stomach content analyses of the giant squid (Dosidicus gigas) (Ehrhardt, 1991). Lanternfishes were abundant north of Isla Angel de la Guarda (Robison, 1972); however they were not im- portant in the diet of the California sea lion in this region. Their greater importance in the diet at southern rookeries was probably due to the absence of more preferred prey such as Pacific sardine, Pacific cutlass- fish, or anchoveta. The consump- tion of northern anchovy tended to be less important towards Canal de Ballenas, where Pacific sardine reached its maximum importance. The low spatial overlap of these two species has also been noted in other studies. The anchoveta was present only at Isla Lobos. This is an estuarine-lagoon species, typical of coastal lagoons of northern Sinaloa and Sonora (Castro-Aguirre et al., 1995). The presence of this prey in Isla Lobos is possibly due to the sandy coast (Walker, 1960), which is similar to that of the Sinaloa-Sonora coast. The diet of California sea lions differed among rooker- ies, probably due to differences in feeding sites and prey availability. Antonelis et al. (1990) studied the foraging characteristics of the northern fur seal (Callorhinus ur- sinus) and the California sea lion at San Miguel Island and found differences between foraging areas among 0.15 200-i 180- 160- 140- | 120- •£_ 100- £ 80- _J 60- 40- 20- n=121 JUN95 SEP95 JAN95 Figure 5 Size of Pacific sardine iSardinops caeruleus) estimated from otoliths found in California sea lions scats collected in Isla San Esteban, El Rasito, Granito, Los Cantiles, and Los Machos. One standard deviation is indicated from each mean. 0.2 0.25 0.3 0.35 0.4 0.45 Figure 6 Dendrogram of cluster analysis of seven rookeries determined with Euclidean dis- tance (computed from the IIMP of the 25 prey that had on at least one occasion a value >10%) and the UPGMA (unweighted pair-grouping methods) strategy. The vertical lines represent the points of references to delimit the groups. species. The northern fur seal was found most frequently foraging in oceanic water within 72.4 km from the island, whereas Califorinia sea lions forgaged more often in the shallower neritic zone, within 54.2 km from the island. Different foraging distances in California sea lions from San Miguel Island were found by Melin and DeLong ( 1999). During the nonbreeding season a higher percent- age of foraging locations occurred at distances less than 100 km, whereas during the breeding season most of the foraging locations occurred at distances greater than 100 km. These differences are probably due to the in- creased California sea lion population in San Miguel; this increase in population forces sea lions to exploit new areas as a density-dependent response to population Garcia-Rodriquez and Aurioles-Gamboa: Spatial and temporal variation in the diet of Zalophus californianus 59 SPM ■Jun95 »Sep96 ■4 I I I I I I I I I I I I I I I I I I I I I I t I 2 4 6 8 10 G M 16 18 2022242628303234 36 384042'! EST 2 4 6 8 10 12 2022 24 26283032 34 36 384042444648 50 RAS 2 4 6 8 10 12 14 16 18 202224262830323436384042444648 50 3 50 MAC 3 00 . * " * 2 50 . t „ / 2 00 . 1 50 . */ i - - - Jan t 00 . 50 . 1 t 1 1 1 1 1 1 1 1 * I I l l l l I I l ■t-f H- ■h-i 2 A 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50 Sample size CAN I'l I I I i I i i i I I I I I I I I I i I I I I l l 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50 GRA I ' l i i i i i i i i i i i i i i i i i i i 0246610121416 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50 3 50 - LOB 3 00 . 2 50 . _, _. - -J—v 2 00 . r v J C^y 1 50 . 100 . . A /• - - - Jan96 0.50 •_i/ v - - May9 /, i -t-t- Mill i i i i i i i 0246810121416 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 40 50 Sample size Figure 7 Trophic diversity curves for California sea lions determined from scat samples collected at seven rookeries in the Gulf of California, Mexico. SPM = San Pedro Martir; EST = San Esteban; RAS = Isla Rasito; MAC = Los Machos; CAN = Los Cantiles; GRA = Isla Granito; LOB = Isla Lobos. 60 Fishery Bulletin 102(1) growth. Although, these differences could also be due to variability in the distribution of prey (Melin and DeLong, 1999), as suggested by Antonelis and Fiscus (1980), forag- ing areas might change with season and annual variations in prey availability and abundance. Foraging areas in the Gulf of California could lie closer to rookeries than those recorded for San Miguel Island sea lions because the diet was different among rookeries in spite of the shorter distance between them (54.2 km). At Los Islotes, Baja California Sur, adult females fed within 20 km of the colony (Duran-Lizarraga. 1998). Kooyman and Trillmich (1986a, 1986b) reported similar data in sea lion colonies of the Galapagos Islands. In the northern region of the Gulf of California, feeding range could be shorter than that at Los Islotes because of the higher concentration of food at high nutrient concentrations (phosphate, nitrate, nitrite, and silicate) in Canal de Ballenas that is associated with strong tidal mixing (Alvarez-Borrego, 1983). Four foraging zones were discerned from dietary differ- ences in sea lions from the seven rookeries studied. Zone I, which included San Pedro Martir. San Esteban. and El Rasito, was characterized by the consumption of lantern- fish; zone II, which included Los Machos was characterized by the consumption of Pacific sardine and Pacific mackerel; zone III, which included Isla Granito, by the consumption of Pacific cutlassfish and the northern anchovy; and zone IV, Los Cantiles and Isla Lobos, was characterized by the consumption of the plainfin midshipman and the Pacific cutlassfish. These four zones may indicate differences in habits used by sea lions or may indicate different oceano- graphic conditions exploited by sea lions. The eastern coast of the Gulf of California displays high photosyn- thetic pigment concentrations, associated with upwelling induced by winds from the northwest in the winter. These conditions may make Canal de Ballenas one of the most important for the distribution of Pacific sardine during the summer. Trophic diversity varied spatially and temporally. San Pedro Martir and Isla lobos sea lions seem to depend on a more stable feeding areas compared to sea lions at rook- eries on Isla Granito and Los Machos, where changes in diversity of consumed species indicated that sea lions feed on fewer species during certain times of the year. Similar results in relation to the changes in diversity were also noticed in the rookeries of the Channel Islands and Faral- lon Islands, California (Bailey and Ainley, 1982; Antonelis et al., 1984; Lowry et al., 1990; Lowry et al., 1991 ). Perhaps the tendency to have the highest values of diversity and little seasonal variation at San Pedro Martir is the result of this rookery being located in a zone of transition between two biogeographical areas. This geographical position con- fers greater environmental heterogeneity and greater ecological diversity (Walker, 1960). California sea lions in the upper region of the Gulf of California obtain the main portion of their diet from a relatively small number of species. The decrease in abun- dance of any of these food resources can seriously affect the population, particularly at Isla Granito and Los Machos because sea lions from these rookeries depend on a few species. Acknowledgments We wish to thank Secretaria de Marina, Armada de Mexico, for its great support during the field activities, and the Consejo Nacional de Ciencia y Tecnologia (CONACYT) for funding this study under grant number 26430-N. The Secretaria de Medio Ambiente, Recursos Naturales y Pesca (SEMARNAP) provided permits for field work (DOO.-700- (2)01104 and DOO.-700(2).-1917). We would like to thank Robert Lavenberg and Jeff Siegel for allowing us the use of otoliths from the collection at the Natural Museum His- tory of Los Angeles County and also Lawrence Barnes for his logistical support during the stay of first author at Los Angeles; we also thank Manuel Nava for allowing us the use of otoliths from the collection in Tecnologico de Monterrey, Campus Guaymas. We are also grateful to Unai Markaida for his assistance in prey identification based on the examination of cephalopods beaks. 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Universidad Autonoma de Baja California. Ensenada, B.C. Pitcher, K. W. 1980. Stomach contents and feces as indicators of harbour seal, Phoca vitulina, foods in the Gulf of Alaska. Fish. Bull. 78:797-798. 62 Fishery Bulletin 102(1 Robison. B. H. 1972. Distribution of the midwater fishes of the Gulf of California. Copeia (19721:449-61. Roper. C. F. E., and R. E. Young. 1975. Vertical distribution of pelagic cephalopods. Smith- sonian Contribution to Zoology 209(51 1:31. Sanchez-Arias, M. 1992. Contribucion al conocimiento de los habitos alimen- tarios del lobo marino de California Zalophus califomianus en las Islas Angel de la Guarda y Granito, Golfo de Cali- fornia, Mexico. Tesis de Licenciatura, 63 p. Universidad Nacional Autonoma de Mexico. Mexico, D.F. Tollit, D. J., M. J. Steward, P. M. Thompson. G. J. Pierce, M. B. Santos, and S. Hughes. 1997. Species and size differences in the digestion of oto- liths and beaks: implications for estimates of pinniped diet composition. Can. J. Fish. Aquat. Sci. 54:105-119. Walker, B. W. 1960. The distribution and affinities of the marine fish fauna of the Gulf of California. System. Zool. 9(3):123-133. Wolff, G A. 1984. Identification and estimation of size from the beaks of 18 species of cephalopods from the Pacific Ocean. NOAA Tech. Rep. NMFS 17, 49 p. 63 Abstract— Recruitment of bay anchovy {Anchoa mitchilli) in Chesapeake is related to variability in hydrologi- cal conditions and to abundance and spatial distribution of spawning stock biomass (SSB I. Midwater-trawl surveys conducted for six years, over the entire 320-km length of the bay, provided information on anchovy SSB, annual spatial patterns of recruitment, and their relationships to variability in the estuarine environment. SSB of anchovy varied sixfold in 1995-2000; it alone explained little variability in young-of-the-year (YOY) recruitment level in October, which varied ninefold. Recruitments were low in 1995 and 1996 (47 and 31xl0 9 ) but higher in 1997-2000 (100 to 265 xlO 9 ). During the recruitment process the YOY popu- lation migrated upbay before a subse- quent fall-winter downbay migration. The extent of the downbay migration by maturing recruits was greatest in years of high freshwater input to the bay. Mean dissolved oxygen (DO) was more important than freshwater input in controlling distribution of SSB and shifts in SSB location between April- May (prespawningl and June-August (spawning) periods. Recruitments of bay anchovy were higher when mean DO was lowest in the downbay region during the spawning season. It is hypothesized that anchovy recruit- ment level is inversely related to mean DO concentration because low DO is associated with high plankton produc- tivity in Chesapeake Bay. Additionally, low DO conditions may confine most bay anchovy spawners to the downbay region, where production of larvae and juveniles is enhanced. A modified Ricker stock-recruitment model indicated den- sity-compensatory recruitment with respect to SSB and demonstrated the importance of spring-summer DO levels and spatial distribution of SSB as con- trollers of bay anchovy recruitment. Recruitment and spawning-stock biomass distribution of bay anchovy (Anchoa mitchilli) in Chesapeake Bay* Sukgeun Jung Edward D. Houde University of Maryland Center for Environmental Science Chesapeake Biological Laboratory 1 Williams St., P.O. Box 38 Solomons, Maryland 20688 E-mail address (for S Jung): iung@cbl.umces.edu Manuscript approved for publication 30 September 2003 by Scientific Editor. Manuscript received 20 October 2003 at NMFS Scientific Publications Office. Fish. Bull. 102:63-77 (20041. Recruitment for marine fishes is vari- able and is regulated or controlled by a combination of density-dependent and density-independent processes. It has been hypothesized that density-inde- pendent processes dominate from the egg to larval stages whereas density- dependent control by predation may be more important in the juvenile stage (Sissenwine, 1984; Houde, 1987). Den- sity-dependent processes may be stock dependent, regulated by adult abun- dances, or dependent on abundances of the early-life stages (Ricker, 1975). In estuarine systems, where hydrological conditions (e.g. dissolved oxygen, tem- perature, and circulation) vary widely, the roles of density-independent physi- cal factors on fish recruitments may be dominant, making it difficult, but still important, to partition density- dependent and density-independent processes, particularly for short-lived small pelagic fishes such as anchovies and sardines. Bay anchovy {Anchoa mitchilli) (En- graulidae) is a coastal species distrib- uted broadly in the western Atlantic from Maine to Mexico. This small fish is the most abundant and ubiquitous fish in Chesapeake Bay, the largest estu- ary on the east coast of North America (Houde and Zastrow, 1991; Able and Fahay, 1998). It is not fished, yet there is evidence that recruitment is variable (Newberger and Houde, 1995). It feeds on zooplankton — primarily copepods and other small Crustacea — and is a major prey of piscivores, including several eco- nomically important fishes (Baird and Ulanowicz, 1989; Luo and Brandt, 1993; Hartman and Brandt, 1995). Male and female bay anchovy in Chesapeake Bay mature at 40^15 mm fork length (44-50 mm total length) at about 10 months of age, and peak spawning occurs in July (Zastrow et al.. 1991). Most eggs are produced by age-1 individuals (Luo and Musick, 1991; Zastrow et al., 1991). Bay anchovy may survive to age 3+ and reach approximately 100 mm length and 5 g wet weight ( Newberger and Houde, 1995; Wang and Houde, 1995). Newberger and Houde (1995) noted large differences in annual survey abundances of bay anchovy that appar- ently resulted from variability in an- nual recruitments. In Chesapeake Bay, abundance, growth, and mortality rates of bay anchovy eggs and larvae vary temporally and spatially (Dorsey et al, 1996; MacGregor and Houde, 1996; Rilling and Houde, 1999a, 1999b). Indi- vidual-based models were developed to test the hypothesis that recruitment of bay anchovy is determined by variable growth and mortality during early-life stages that are regulated by density-de- pendent processes (Wang et al., 1997; Cowan et al., 1999; Rose et al„ 1999). In previous research, there was little knowledge of levels of spawning stock biomass or density-independent envi- ronmental factors that may control re- cruitment through their effects on spa- tial and temporal variability in growth and mortality of prerecruit anchovy. * Contribution 3696 of the University of Maryland Center for Environmental Sci- ence, Chesapeake Biological Laboratory, Solomons, MD 20688. 64 Fishery Bulletin 102(1) 39°N 38°N ^vt^w N 37°N gi quehanna Upper — Middle Lower Atlantic Ocean 77°W 76°W Figure 1 Chesapeake Bay and stations sampled by the midwater trawl in the 1995-2000 surveys. Horizontal lines indicate boundaries of three designated regions. We evaluated environmental factors, spatial distribution of spawning stock biomass (SSB), and possible ontogenetic migrations of prerecruits (Dovel, 1971; Loos and Perry. 1991; Wang and Houde, 1995; Kimura et al, 2000) with respect to bay anchovy recruitment variability. Our objec- tives were 1) to estimate annual and regional variability in bay anchovy recruitment. 2) to evaluate effects of hy- drological conditions (mainly, freshwater input, and dis- solved oxygen concentration) on stage-specific distribution, ontogenetic migration, and recruitment, and 3) to identify mechanisms and describe patterns or trends in the bay anchovy recruitment process. Data were obtained in a six-year, multidisciplinary research program conducted throughout Chesapeake Bay. Materials and methods Study area Chesapeake Bay is a coastal plain estuary of partially mixed fresh water and sea water. Its 320-km mainstem varies in width from about 6 to 50 km (Fig. 1 ). The Bay is shallow; less than 10' r of its area is >18 m deep and approximately 50' i is <6 m deep. More than 809& of the freshwater entering the bay is from tributaries on its northern and western sides (Chesapeake Bay Program 1 ). Salinity grades from near-full seawater at the mouth of the bay to freshwater near its head. Water temperatures reach 28-30°C in mid summer, and fall to 1^°C in late winter (Murdy et al, 1997 ). Despite shallow depth, the bay usually has a strongly developed pycnocline, and has seasonally strong vertical gradients in temperature, salinity, and dissolved oxygen. Surveys Trawl surveys were conducted three times annually over the entire bay (April-May, June-August, and October). 1995-2000 (Table l.Fig. 1). Midwater-trawl (MWT) fish col- lections 2 were made on transects in three regions: the lower bay (37°05'N-37°55'N), middle bay (37°55'N-38°45'N I, and upper bay (38°45'N-39°25'N). As defined, the lower bay contains 51% of water volume, the middle bay 32^ .and the upper bay 17^ (Fig. 1). The number of midwater trawl sta- Chesapeake Bay Program. 2000. Chesapeake Bay: Introduc- tion to an ecosystem. U.S. Environmental Protection Agency, publ. EPA 903-R-00-001. 30 p. EPA. 410 Severn Ave, Suite 109, Annapolis. MD 21403. Trophic interactions in estuarine systems, midwater trawl sur- vey. University of Maryland Center for Environmental Sci- ence, Chesapeake Biological Laboratory, http://www.ch.esa peake.org/ ties/mwt laccessed 15 October 20031. Jung and Houde: Recruitment and spawning-stock biomass distribution of Anchoa mitchilli 65 Table 1 Cruise dates, mean standard errors for temperatures (°C) individual cruises. salinities (psul, and dissolved oxygen (mg/L). ir years, seasons, and regions of Chesapeake Bay, tegrated from surface to bottom, and pooled 1995-2000. CV = coefficient of variation for annual means. Temperature SE Salinity SE Oxygen SE Cruise date ( depart 28 Apr 95 ure) 13.88 0.11 15.01 0.42 8.53 0.1.3 23 Jul 95 28.13 0.12 15.48 0.44 6.50 0.14 28 Oct 95 17.26 0.12 17.39 0.45 7.59 0.14 28 Apr 96 13.87 0.10 10.84 0.36 10.21 0.11 17 Jul 96 24.66 0.11 11.80 0.41 7.43 0.13 22 Oct 96 16.10 0.10 11.26 0.36 8.55 0.11 20 Apr 97 10.93 0.13 11.41 0.50 10.01 0.16 11 Jul 97 25.28 0.13 13.59 0.51 7.10 0.16 29 Oct 97 14.64 0.13 18.19 0.51 8.01 0.16 11 Apr 98 12.26 0.12 8.90 0.44 9.95 0.14 04 Aug 98 26.15 0.12 12.89 0.46 7.01 0.15 19 Oct 98 18.60 0.13 16.64 0.49 8.64 0.15 19 Apr 99 11.97 0.13 13.51 0.49 10.04 0.16 26 Jun 99 23.52 0.15 16.02 0.56 5.75 0.18 23 Oct 99 16.30 0.14 17.38 0.53 8.87 0.17 29 Apr 00 12.95 0.17 12.51 0.64 8.98 0.20 25 Jul 00 24.26 0.14 14.06 0.53 5.17 0.17 17 Oct 00 17.89 0.15 16.73 0.56 7.63 0.18 Year 1995 19.76 0.07 15.96 0.25 7.54 0.08 1996 18.21 0.06 11.30 0.22 8.73 0.07 1997 16.95 0.08 14.40 0.29 8.37 0.09 1998 19.00 0.07 12.81 0.27 8.53 0.08 1999 17.26 0.08 15.64 0.30 8.22 0.10 2000 18.36 0.09 14.43 0.33 7.26 0.11 CV 5.8% 12.5% 1.2% Season April-May 12.64 0.05 12.03 0.20 9.62 0.06 June-August 25.33 0.05 13.97 0.20 6.49 0.06 October 16.80 0.05 16.27 0.20 8.22 0.06 Region of bay Lower 18.40 0.04 21.19 0.16 8.15 0.05 Middle 18.33 0.05 14.06 0.19 8.33 0.06 Upper 18.04 0.06 7.02 0.23 7.85 0.07 tions per survey ranged from 24 to 52 (six-year total=597). Additional baywide surveys (August 1997 and September 1998) and partial surveys (June 1997, July 1998, and July 1999) also provided data (total stations =146). An 18-m 2 mouth-opening midwater trawl (MWT), with 3-mm codend mesh was deployed from the stern of the 37-m research vessel Cape Henlopen. All trawling was conducted at night. Standardized tows of 20-min dura- tion were conducted and the trawl was deployed at graded depth intervals from surface to bottom ( 2 minutes at each depth interval ) in order to provide a sample of fish from the entire water column. Fish catches (or subsamples) were counted, measured (to the nearest 1.0 mm), and weighed on deck immediately after a tow. Abundance and biomass of bay anchovy recruits and spawners We separated bay anchovy catches into YOY and spawn- ers based on total length (TL). The minimum length of bay anchovy retained by the MWT was 21 mm TL, which we also defined as the minimum TL for recruited YOY bay 66 Fishery Bulletin 102(1) anchovy. Modal lengths of young-of-the-year (YOY) bay anchovy cohorts were determined from length-frequency distributions in MWT catches and a modal analysis (Bhat- tacharya, 1967; King, 1995). Based on the modal analysis of summer and fall survey data, the maximum TL of YOY bay anchovy and, therefore, the minimum TL of spawners, were estimated (Table 2). Length-dependent gear selectivity for bay anchovy was adjusted by comparing catches of the MWT and a 2-m 2 Tucker trawl with catches from 707-iim meshes at the same stations during a September 1998 baywide survey. The length-specific MWT:Tucker-trawl catch ratios (N^^j/ iVj^catch per unit of effort MWT 4- catch per volume of water Tucker trawl) for anchovies 21-70 mm TL indicated that both gears fished with a consistent selectivity for bay anchovy of 30-48 mm TL, and with a slight decrease in N TT for 48-70 mm TL. However, the values ofN MWT IN TT were lower by factors of 1-7 for 21-30 mm TL fish, indicating that small anchovies were collected less efficiently by the MWT. We concluded that length classes of anchovies >30 mm TL were equally vulnerable to the MWT and those >48 mm TL were less vulnerable to the Tucker trawl. Accord- ingly, we adjusted MWT catches of ^30 mm TL anchovy by multiplying them by a weighting factor estimated from the regression of values of iV MH , T /./V. r7 . for 21-30 mm TL bay anchovy. ( Weighting factor) = -0.59 TL + 19.08, (r 2 =0.96) where TL = total length. The weighting factor equals 1.0 for anchovy >30 mm TL because MWT selectivity is constant for anchovy >30 mm TL. To estimate water sampled in a 20-min MWT tow, and where D« d n = n mwt/ v mwt = ( 1/s ' x Nt/Vtt MWT — ^ x ^-^ MWT TT x TT bay N, MWT N 77' the concentration of 31-48 mm TL anchovy at a station (i.e. number/m 3 ); the number of 31-48 mm TL bay anchovy collected per 20-min MWT tow at a station; V MWT = the effective water volume sampled by a 20-min MWT tow (m :! ); the number of 3 1-48 mm TL bay anchovy col- lected by the 2-m- Tucker trawl at the same station; vulnerability to the Tucker trawl (s=l if all bay anchovies in water volume, V^, are col- lected); and V TT is the volume filtered by the Tucker trawl (m 3 ) estimated from a flowme- ter in its mouth. The mean of Af WHT /./V 7T for 30-48 mm TL bay anchovy during the September 1998 survey indicated that V' WUT = 4961 m\ if 30-48 mm TL bay anchovy did not significantly avoid the mouth of the 2-m 2 Tucker trawl (i.e. s=l). Assum- ing s=l (i.e. V MVVT =4961 m 3 ), we estimated "relative" bay- Table 2 Estimated maximum total lengths of young-of-the-year bay anchov y (mm ) from Chesapeake Bay, based on analy- sis of length-frequency distributions. Year Date Length (mm) 1995 23 Jul 28 Oct 52 69 1996 17 Jul 22 Oct 57 68 1997 11 Jul 2 Aug 29 Oct 30 56 66 1998 4 Aug 7 Sep 19 Oct 50 62 69 1999 26 Jun 23 Oct 30 65 2000 25 Jul 17 Oct 52 67 wide abundance and biomass of YOY and spawners for the 18 surveys from 1995 to 2000. To coarsely estimate a typical value of s. "absolute" bay- wide spawner biomasses in June— August were estimated for 1995-2000 according to an egg production method (Parker, 1985; Rilling and Houde, 1999a). Bay anchovy eggs had been collected in a 1-m 2 Tucker trawl during the same surveys and provided estimates of egg abundance. The coverage of stations and sampling design for the Tucker trawl was comparable to that of the MWT, but the Tucker trawl was deployed during both day and night. We presumed that all eggs collected between 00:00 and 20:00 h had been spawned near a midnight peak 1 00:00 h) (Za- strow et al., 1991) and decreased in abundance at a mean instantaneous mortality (reported for bay anchovy eggs in Chesapeake Bay as M = 0.066/h; Dorsey et al., 1996). Based on the estimated number of eggs spawned at 00:00 h for each station, the regional mean weight of individual spawners (defined by the minimum TL in Table 2) in MWT catches, and the reported fecundity-weight relationship for females (Zastrow et al., 1991), we were able to coarsely estimate "absolute" baywide spawner biomass. We as- sumed that the spawning fraction of adult females per day- was essentially 1.0 (i.e. all adult females participated in spawning, Zastrow et al., 1991) and the fecundity-weight relationship was constant over years. Comparison of the baywide estimates of spawner bio- mass in June-August based on the egg production method ("absolute" biomass) with estimates based on the MWT catch-per-unit-of-effort ("relative" biomass) indicated that. on average, for 1995 to 2000, s is equal to 0.20. Therefore, the mean effective water volume fished by a 20-min MWT tow was 4961x0.20 = 989 m 3 . Jung and Houde: Recruitment and spawning-stock biomass distribution of Anchoa mitchilli 67 Because N mvT of bay anchovy was highly variable, even at stations on the same sampling transect, and a mixed model (SAS version 6.12, SAS Inst. Inc., Cary, NC) includ- ing spatial covariance ( variogram ) did not significantly im- prove precision in annual, seasonal, and regional means or differences of N MWT , a stratified sampling design ( Steel and Torrie, 1980), i.e. stratum = region, was adopted. Based on the mean effective water volume (=sxV MWJ , ), we estimated regional "absolute" abundance and biomass (number and wet weight) and related standard errors of the linear com- bination by regional subvolumes (Samuels, 1989) of bay anchovy >21 mm TL for all MWT surveys from 1995 to 2000 by multiplying regional mean MWT catch by V r /989, where V r represents the water volume (m 3 ) in each bay region (Cronin, 1971): N !olal =(N^V l+ N n V,„ + N. Vj/(sxV MWT )xV lotal SE N =Sc N jVr/n,+V*/n n +v:?/n„ where N lotal v„ v m , v u SE X Sc N = baywide absolute abundance; mean values of N mvT for the lower (1), middle (m), and upper (u) bay; bay subvolumes for the lower (1), middle (m), and upper (u) bay (from Cronin, 1971), V, = 26.7 x 10 9 m 3 , V m = 16.8 x 10 9 m 3 , V„ = 8.7 x 10 9 m 3 , V„„„, = V, + V m + V„ =52.1 x 10 9 m 3 ; standard error of N lolal ; number of midwater trawl stations for the lower (1), middle (m), and upper (u) bay; pooled standard deviation of N MWT = square root of mean squares within groups in analysis of variance table = t/< SS, + SS m + SS„ ) / ( n, lMl -3i, where SS,, SS m , SS tl = sum of squares of N MWT for the lower (1), middle (m), and upper (u) bay, and "total = n l + n m + n u- Environmental factors Depth profiles of temperature, salinity, and dissolved oxygen ( DO ) concentration were determined from conduc- tivity-temperature-depth ( CTD ) casts at sampling stations. DO data were adjusted by calibrating against Winkler titration data from water samples collected in Niskin bot- tles deployed with the CTD cast. However, DO data from the CTD could not be adjusted for the 1999 summer and all calendar year 2000 cruises because Winkler titrations were not conducted. To estimate regional means for the water column, we averaged temperature, salinity, and DO values by integrating the observed values with respect to depth, after dividing the water column into "above pycnocline" and "subpycnocline" layers. Ontogenetic migration We analyzed length-frequency distributions along the south-north axis of the bay (i.e. by latitude) to delineate possible ontogenetic migrations of YOY and adult bay anchovy. To parameterize the distribution of YOY and adult abundance and biomass, we estimated the biomass- weighted mean latitudes of occurrence for each length class (3-mm interval). l b.i = 2_, B kjL k /2jB tl , where L B , = biomass-weighted mean latitude of a length class, /; L k = latitude of the station, k; and B = biomass (g, wet weight) per 20-min tow. We devised a metric to parameterize the location of bay anchovy SSB. We assumed that the baseline boundary for SSB distribution during the spring was at the mouth of the bay (37°00'N). Then, the upbay difference between biomass-weighted mean latitude of SSB (in decimal units) in Jun-August and the baseline for SSB during the spring lAL i was calculated: SL biomass-weighted mean latitude of SSB in June - August -37.00. Recruitment model As an exploratory step, a correlation analysis was under- taken to examine the relationships between bay anchovy SSB, migration patterns, and recruitment levels with respect to regional and depth-layer-specific mean tempera- ture, mean salinity, mean DO, their gradients, and monthly mean freshwater flow from the Susquehanna River. Cross- correlations revealed that SSB migration pattern {AD, regional mean DO concentrations, and October YOY recruitment level were closely correlated. Regional mean DO concentration provided the best fit to YOY recruitment level in October when baywide SSB also was included as an explanatory variable in multiple regressions. However, because there is uncertainty in the uncalibrated DO measurements in 1999 and 2000. we did not use regional mean DO in our recruitment model. Instead, we developed a modified Ricker-type stock-recruitment model (Ricker, 1975) that included AL as an explanatory variable: R x = a S exp (-/3j S - /i, AL) + e (modified Ricker model ) where R, recruitment level = October YOY abun- dance in each year ( 1995-2000); y; a, l\ and p.-, = regression coefficients; S = estimated baywide SSB (male-i- female) in metric tons for April-May; and £ = the error term. In this model, if AL is held constant, R s . is maximum at S = l//3j. Although no abiotic factor was included explicitly in the model, AL is strongly correlated with regional mean DO and serves as a proxy for it. For the modified Ricker model, collinearity, and jackknife influence diagnostic tools were 68 Fishery Bulletin 102(1) Table 3 Seasonal mean freshwater flow entering Chesapeake chesbay/RIMP/adaps.html. Bay ft' Dm the Susqu ehanna River ( m 3 /s ). Data source : http://va. water. usgs.gov/ Period 1995 1996 1997 1998 1999 2000 Jan-Mar 1289 2495 1474 2563 1325 1379 Apr-Jun 728 1702 920 1625 791 1627 Jul-Sep 238 768 239 334 294 393 Oct-Dec 923 2230 746 194 642 504 Annual mean 795 1799 845 1179 763 976 applied to evaluate reliability of the regression model (Belsley et al„ 1980; SAS, 1989). Results Environmental factors Stream flows from the Susquehanna River (Table 3) varied annually and seasonally. Freshwater stream flows were higher in 1996 and 1998 than in other years. Baywide mean values of water temperature, salinity, and DO concentration, averaged from surface to bottom, varied annually, seasonally, and regionally (Table 1 ). Annually, mean temperature was highest in 1995 and lowest in 1997. Mean salinity was highest in 1995 and lowest in 1996. Mean DO concentration was highest in 1996 and lowest in 2000. Regionally, salinity was more variable than temperature and DO concentration. Seasonally, temperature and DO concentration were more variable than salinity. Tem- perature was highest in the June-August period, the spawning season of bay anchovy. Seasonally, salinity increased progressively from April-May to October. Mean DO concentration was consistently lowest in June-August. Trends in abundance and recruitment Estimates of bay anchovy abundance reported in our study are for the entire mainstem of Chesapeake Bay. The estimated recruitment levels (baywide abundance of YOY bay anchovy >30 mm TL in October) varied ninefold and were low in 1995 and 1996 (47.5 ±16.6 and 30.6 ±8.6xl0 9 individuals) but much higher in 1997-2000 (99.6 ±12.4 to 264.8 ±32.6xl0 9 ). Baywide estimates of bay anchovy biomass for individuals >30 mm TL increased from April to October in each year (Table 4). October baywide biomass varied sevenfold from 27.1 ±5.5 x 10 3 to 192.9 ±20.4 x 10 3 tons and was highest in 1998 and lowest in 1996. Estimated spawning stock biomass (SSB) in April-May was lowest in 1995 (3.3 ±1.1 x 10 3 tons), and highest in 1997 (20.1 ±5.3 x 10 3 tons), indicating sixfold variability. SSB in June-August was lowest in 1996 (2.4 ±0.2 x 10 3 tons), and highest in 1997 (21.1 ±2.3 x 10 3 tons). The SSBs in April-May and June-August did not show any obvious relationship to YOY abundance (recruitment) in October. Ontogenetic migration The length-specific mean locations (latitudes of occur- rence ) of bay anchovy revealed an apparent ontogenetic migration. Small juveniles of bay anchovy tended to move upbay and were located primarily upbay until they were approximately 45 mm TL, after which they began to move downbay (Fig. 2). In April-May, age-1 bay anchovy <60 mm TL, consisting of individuals recruited from the previous year, varied annually in their mean latitude of occurrence, whereas large (sage 1, a60 mm TL) bay anchovy had relatively stable locations near the boundary between the lower and middle bay regions, centered at latitude 37°40'N (Fig. 2A). Compared to April-May, age-l+ bay anchovy in June-August were more variable in their annual mean locations, but both YOY and adult bay anchovy tended to occur upbay of latitude 38°00'N, except in year 2000 (Fig. 2B). In 1997 and 1999, when annual mean temperatures were lowest (Table 1), YOY bay anchovy were too small to be sampled by the MWT in June-August and are not represented in Figure 2B. In October, mean latitudes of occurrence (Fig. 2C) indicated a consistent distribution pattern and an apparent ontogenetic migration by YOY anchovy. The most probable explanation for the observed latitudinal distributions was that small YOY bay anchovy tended to move upbay initially, but then downbay at about 45 mm TL. Distribution of age-l-t- individuals in October was variable. The SSB of bay anchovy (excludes YOY) from 1995 to 2000 was centered near 38°00'N in April-August except in June-August of 1995 and 1996, when the SSB was centered farther upbay (Fig. 3A). In 2000, the migration pattern differed from other years. Spawning bay anchovy in 2000 were located farther downbay in July than in April (Fig. 3A). The April-May location of prespawning SSB was mostly explained by the mean flow of the Susquehanna River from June of the previous year to February of the current year (r 2 =0.94, P=0.0012; Fig. 3B ). But, in June-Au- gust, the mean location of spawning fish was more strongly and significantly related to the subpycnocline-layer mean Jung and Houde: Recruitment and spawning-stock biomass distribution of Anchoa mitchilli 69 Table 4 Baywide abundance and biomass estimates for bay anchovy >30 mm TL (young-of-the-year + adult). SE = = standard error. Year Period Abundance I xlO 9 ) Biomass xlO 3 metric tons) Estimate SE Estimate SE 1995 April-May 2.1 0.7 3.3 1.1 June-August 57.8 28.1 32.6 17.5 October 47.5 16.6 51.9 21.0 1996 April-May 4.9 1.1 8.9 2.0 June-August 5.3 1.6 3.7 1.3 October 30.6 8.6 27.1 5.5 1997 April-May 11.8 3.3 20.1 5.3 June-August 9.4 2.3 21.1 5.0 October 99.6 12.4 85.6 10.8 1998 April-May 3.5 0.7 6.1 1.3 June-August 14.4 4.5 17.0 7.9 October 264.8 32.6 192.9 20.4 1999 April-May 6.9 1.4 10.6 2.2 June-August 5.5 1.2 10.6 2.4 October 124.5 28.3 115.3 25.0 2000 April-May 6.2 4.1 13.0 6.6 June-August 144.6 51.2 56.0 17.0 October 169.1 43.7 152.9 40.0 DO during that same period in the middle bay (/•-=(). 75, P=0.02;Fig. 3C). Correlations Correlation analyses suggested that regional mean DO concentrations are the most important environmental correlate associated with spatial distribution of SSB and recruitment processes of bay anchovy. The mean locations (latitudes of occurrence), abundances, and biomasses for YOY and adult bay anchovy were analyzed with respect to environmental variables (Table 5). Recruitment levels (YOY abundance) in October were consistently inversely correlated with DO concentrations in the lower and middle bay in June-August (/-=-0.13 to -0.89). Biomass- weighted mean latitude of SSB (age 1+) in April-May was consistently and positively correlated with regional salini- ties in April-May (r=0.30 to 0.88). On the other hand, in June-August, surface-layer mean salinity in the lower Bay and subpycnocline-layer mean DO in the lower and middle bay were significantly and positively correlated with mean latitude of SSB or AL (r=0.82 to 0.91). Baywide SSB in April-May and June-August tended to be negatively cor- related with water temperature in April-May (r=-0.45 to -0.90). Recruitment model Although SSB alone did not correlate significantly with recruitment level, mean DO in June-August was signifi- cantly related to the mean latitude of SSB in June-August (or AL) and bay anchovy recruitment level in October (Figs. 3C and 4). AL was selected as the explanatory variable, rather than DO, because DO data were uncalibrated in 1999 and 2000. The correlation observed between AL and DO ( Fig 3C ) suggested that AL can serve as a proxy for DO in the stock-recruitment model. Including AL and SSB for April-May in a modified Ricker model provided a good fit to bay anchovy recruitment levels observed from 1995 to 2000 (Fig. 5). The model is R v = 365 S exp (-0.19 S 1.35 AL) (modified Ricker model). In the model, if AL is held constant, predicted recruitment level of bay anchovy is maximum when baywide SSB in April-May is approximately 5.3 x 10 3 tons. Collinearity and influence diagnostic statistics did not indicate collinearity between the two independent variables (S and AL), or that an observation in any year had a dominating influence on parameter estimates. Discussion Complex environmental processes and biological interac- tions control bay anchovy recruitment in Chesapeake Bay. Dissolved oxygen (DO), freshwater flow, salinity, and tem- perature acting on prerecruits and adults are important factors affecting bay anchovy distribution and levels of recruitment. Spawning stock size also is related to recruit- 70 Fishery Bulletin 102(1) ment level. Our results have demonstrated that there is a strong spatial component in the recruitment dynamics of bay anchovy. Although fish recruitment processes his- torically have been difficult to understand, our six-year, spatially extensive research has provided new insights into processes that control bay anchovy recruitment. Ontogenetic migration pattern It is apparent that ontogenetic migration plays a role in the spatial and temporal patterns in abundance, biomass, and production of bay anchovy. There are several lines of evidence. Rilling and Houde (1999a), in a baywide analy- sis, reported that mean density of eggs and larvae in June and July 1993 was very high in the lower Chesapeake Bay compared to more upbay sites. Dovel (1971) and Loos and Perry (1991) reported possible upbay or upriver migra- tion of bay anchovy larvae and juveniles in the mainstem and tributaries of the Bay. Recent otolith microchemical analyses have strongly supported the hypothesis that an upbay ontogenetic migration by small YOY anchovy (>25 mm, late larvae and small juveniles) occurs (Kimura et al., 2000). In the middle Hudson River estuary (Schultz April-May 39°00' £ 38°00 37°00 39°00 38°00 37°00' 30 40 50 60 70 80 90 100 TL (mm) 1995 1996 1997 1998 1999 2000 Figure 2 Abundance-weighted mean latitude of occurrence of bay anchovy (Am hoa mitchilli) in Chesapeake Bay, 1995-2000. et al., 2000) and Chesapeake Bay (North and Houde, in press), selective tidal-stream transport was suggested as a mechanism for up-estuary movements of bay anchovy larvae. Our conceptual model of the bay anchovy life cycle includes migration patterns in the bay based on available knowledge and evidence (Fig. 6). It is uncertain what benefits YOY bay anchovy derives from upbay migration in summer and whether the migra- tion is passive or active before a subsequent reverse migra- tion in the fall. To explain upbay movements of estuarine fishes, Dovel ( 1971 ) proposed that there is a "critical zone" of low salinity and high prey production in the upper bay, which is important as a nursery for bay anchovy and other fish species. In late spring and early summer, age-1 and age-l+ bay anchovy mature and move upbay while spawning, although the year 2000, when mean freshwater streamflow during the previous fall-winter was lowest, was an exception. Recruited YOY bay anchovy apparently over- winter primarily, but not entirely, downbay until spring. There remains a possibility of significant immigration to the bay by adult bay anchovy in some years from the coastal ocean or tidal tributaries of the bay. Without such immigration, baywide adult abundance would decrease continuously during the April-October period through natural mortality However, in two years of our six-year study, 1995 and 1998, estimated adult abundance in- creased substantially from April to July, and in 1999 adult abundance increased from June to October, implying significant immigration to the bay in those years (Jung, 2002). Recruitment control and regulation The modified Ricker recruitment model that included SSB and AL as explanatory variables provided a good fit to bay anchovy recruitments. Although the model fitted well, there were only six years of data, and the underlying mechanisms explaining relationships between the distribution and level of SSB, hydro- logical conditions, and density-dependent regulatory processes in recruitment of bay anchovy are not yet clear. Nevertheless, correlations and the recruitment model clearly indicated a density-dependent effect of SSB level and also implicated environmental factors (at the mesoscale) that are related to mean DO concen- tration, latitudinal distribution of SSB (AL), and the recruitment level of bay anchovy (Fig. 4). The modified Ricker model for bay anchovy < Fig. 5) indicates a density-compensatory stock-recruitment relationship (Ricker, 1975). although we do not know at what life stages density-dependent processes are most important. Without accounting for the control- ling effect of AL and mean DO on a regional scale, the density-dependence might have gone undetected (Fig. 4 1. Recent individual-based models suggest that density-dependent processes during early-life stages could stabilize bay anchovy recruitments (Wang et al., 1997; Cowan et al., 1999; Rose et al, 1999). At the small scales of several meters modeled by Wang et al. (1997) and Cowan et al. (1999), larval-stage feeding Jung and Houde: Recruitment and spawning-stock biomass distribution of Anchoa mitchilli 71 Zl 39°00' 38°00' CO CO CO 37°00' April-May June-August 1995 1996 1997 1998 1999 2000 2000 38°00' 1999^ 1=38.30 - 0.00087 X r-=0.94(/)=0.0012) 37045' 1995 --4?^- 1998 B 1996_ 37°30' i , 300 < 39°00' c C CO CO c 38°00' 400 500 600 700 Mean river flow from June to Feb (m 3 /sec) 1995 1996^ 1999 1998 37°00' 2000 1997 Y= 35.78 + 0.53 A' r 2 =0.75(p=0.02) 3.0 3.5 4.0 4.5 5.0 Dissolved oxygen (mg/L) 5.5 Figure 3 Mean location (latitude) of adult bay anchovy {Anchoa mitchilli) spawn- ing stock biomass (SSB) in Chesapeake Bay. (A) Mean latitude and standard deviation in April-May and in June-August. The upper verti- cal bar represents mean + standard deviation for June-August, and the lower vertical bar represents mean-standard deviation for April-May, I B l Mean latitude in April-May and mean Susquehanna River flow from June of the previous year to February of the current year. (C) Mean lati- tude in June-August and mean dissolved oxygen in the subpycnocline layer of the middle bay in June-August. processes were important and high adult SSB could pro- duce abundant first-feeding larvae with subsequent den- sity-dependent food competition. In Tampa Bay, Florida, Peebles et al. ( 1996) hypothesized that bay anchovy's size- specific fecundity is directly related to prey availability for adults. Modeled results of Rose et al. (1999) suggested that density-dependent growth of bay anchovy larvae and juveniles in Chesapeake Bay would lead to density-depen- dent survival of these stages. Hunter and Kimbrell (1980) and Alheit (1987) proposed that cannibalism by adults on eggs and larvae provides a degree of density-dependent regulation in anchovies of the genus Engraulis. Analyses of feeding by adult bay anchovy did not indicate that pe- lagic fish eggs were a significant part of bay anchovy diet (Vazquez-Rojas, 1989; Klebasko, 1991), although no specific study of cannibalism has been undertaken. We propose three hypotheses that may explain the rela- tionships among regional DO concentration, the latitudi- nal shift in SSB distribution during the spawning season (AL), and recruitment levels of bay anchovy in October. The 72 Fishery Bulletin 102(1) hypotheses are the following: 1) averaged DO concentra- tion is inversely related to levels of plankton productivity in a region and high plankton productivity favors high re- cruitments of planktivorous bay anchovy; 2 ) low dissolved oxygen concentrations can restrict spatial distribution of bay anchovy SSB to the lower bay insuring high egg and Table 5 Cross-correlation coefficients for bay anchovy distribution and abundance with respect to region- and layer-specific means of tem- perature, salinity, and dissolved oxygen from 1995 to 2000. Mean latitude is biomass-weighted mean latitude of occurrence of bay anchovy. Abundance and biomass are baywide total estimates. AL = (mean latitude in June-August) -37.00. Abbreviations are as follows: SAL = salinity, TEM = water temperature, OXY = dissolved oxygen; the fourth and fifth digits: 04 = April-May, 07 = June-August; the sixth character: L = lower bay, M = middle bay, U = upper bay; The last character: S = layer above the pycnocline. B = layer below the pycnocline. * = significant at a = 0.05. Young-of-the-year Adult Mean latitude Abundance Mean latitude Biomass April-May June-August (orAL) October October April-May June-August SAL04LS 0.29 -0.43 0.74 0.26 -0.17 -0.52 SAL04MS 0.45 -0.63 0.30 0.71 -0.41 -0.22 SAL04US 0.27 -0.60 0.42 0.53 -0.18 -0.02 SAL04LB -0.24 0.01 0.88* -0.16 -0.14 -0.31 SAL04MB 0.08 -0.17 0.59 0.33 -0.39 -0.05 SAL04UB 0.29 -0.61 0.45 0.46 -0.03 0.05 SAL07LS 0.83* -0.75 0.91* -0.46 SAL07MS -0.12 0.06 0.14 0.31 SAL07US 0.06 -0.03 -0.04 -0.33 SAL07LB 0.70 -0.75 0.64 -0.11 SAL07MB -0.41 0.60 -0.31 0.19 SAL07UB 0.15 -0.20 0.01 -0.42 TEM04LS 0.16 -0.25 -0.03 0.65 -0.90* -0.48 TEM04MS 0.50 -0.46 0.14 0.65 -0.71 -0.85* TEM04US 0.53 -0.32 -0.36 0.52 -0.56 -0.85* TEM04LB 0.29 -0.49 0.19 0.71 -0.72 -0.45 TEM04MB 0.22 -0.42 0.39 0.47 -0.55 -0.62 TEM04UB 0.40 -0.26 -0.39 0.48 -0.60 -0.77 TEM07LS -0.49 -0.04 0.11 0.45 TEM07MS -0.16 -0.21 0.47 0.14 TEM07US -0.29 -0.08 0.39 0.38 TEM07LB -0.68 0.24 -0.11 0.38 TEM07MB -0.24 -0.10 0.37 -0.04 TEM07UB -0.45 0.16 0.2] 0.46 OXY04LS 0.63 -0.22 -0.80 0.39 -0.10 -0.30 OXY04MS -0.27 0.56 0.23 -0.81 0.55 -0.04 OXY04US -0.43 0.41 -0.30 -0.30 0.30 0.88* OXY04LB 0.93** -0.68 -0.59 0.63 0.04 -0.38 OXY04MB 0.47 -0.35 -0.31 -0.09 0.70 -0.12 OXY04UB -0.57 0.65 -0.32 -0.46 0.21 0.78 OXY07LS 0.18 -0.30 0.29 0.32 OXY07MS 0.01 -0.13 0.29 0.56 OXY07US 0.23 -0.32 0.50 0.10 OXY07LB 0.67 -0.48 0.82* -0.28 OXY07MB 0.72 (l,SH 0.87* -0.04 OXY07TJB 0.01 0.16 0.21 0.37 Jung and Houde: Recruitment and spawning-stock biomass distribution of Anchoa mitchilli 73 larval production there; and 3) density-depensatory predator satiation occurs when concentrations of bay anchovy larvae and juveniles at the mesoscale ( 10-100 km ) are high in relation to satiation potential of preda- tors, which favors larval production and high anchovy recruitments. First, averaged DO level in the bay or its regions may be an indicator of ecosystem metabolism and sec- ondary production. DO level in the subeuphotic layer is an indicator of respiration and secondary produc- tion by planktonic and benthic communities (Kemp and Boynton, 1980; Kemp et al., 1992). Recruitment levels of bay anchovy increased substantially in 1997 and in subsequent years. We speculate that enhanced detrital production potentially increased zooplankton prey abundances in the subsequent year and that asso- ciated elevated levels of respiration by detrital micro- organisms and zooplankton contributed to low mean DO. Increased zooplankton prey abundances, in turn, may have promoted production of larval and juvenile bay anchovy in 1997 and 1998. Thus, increased prey availability, associated with low mean DO concentra- tion, could have enhanced recruitment (Fig. 4). The second hypothesis proposes that spatial restric- tion of SSB by low DO is a factor controlling bay anchovy recruitment. Based on our results, hypoxic conditions in the bay appear to define the distribution and potential for upbay migration of bay anchovy SSB (Fig. 3C). In years 300 1998 7= -88 .V+ 5 10 C 200 o 1 00 cr r-=0.79P=0.01S 2000 ^~"-\1999 ^^19,97 ~"\J995 1W(, 3.0 3.5 4.0 4.5 5.0 Dissolved oxygen (mg/L) Figure 4 Relationship between mean dissolved oxygen below the pycno- cline in the middle Chesapeake Bay during the June-August period and recruitment level of bay anchovy in October, r 2 = coefficient of determination. when the baywide subpycnocline mean DO level was low, spawning bay anchovy tended to be most concentrated in the lower bay (Table 5, Fig. 3, A and C), possibly because hypoxia in deeper waters of the mid-bay region discouraged upbay migration. The region selected by adult anchovy as the predominant spawning area and its variability played R = 365 Sexpf-O.l - S - 1.354Z.) r 2-- 2.0 Figure 5 Stock-recruitment model (modified Ricker model). R = baywide number of recruits in October (xlO 9 ). AL = location of bay anchovy iA?iclioa mitchilli) spawning stock biomass in June-August in relation to the baseline latitude at the mouth of the bay, 37°00'N. S = baywide spawning stock biomass (SSB xlO 3 metric tons for April-May 1. Balloon symbols are observed data from 1995 to 2000. 74 Fishery Bulletin 102(1) a strong role in controlling YOY recruitment levels. The four highest recruitment years in our series had the lowest mean subpycnocline DO levels and had distribution pat- terns of SSB that differed little between the prespawning April-May and spawning June-August periods (Fig. 4). Al- though we do not fully understand how DO, and possibly hypoxic conditions, affect migratory behavior and distribu- tion patterns of bay anchovy, hypoxia in Chesapeake Bay has been demonstrated in other research to affect spatial and temporal patterns of fish abundance, including bay anchovy (Breitburg, 1992; Keister et al., 2000). Our third hypothesis proposes that predation is an im- portant regulator of fish recruitment in early-life stages (Sissenwine, 1984; Bailey and Houde, 1989). We hypoth- esize that abundant and spatially concentrated larval or juvenile anchovy, as observed in the lower bay, could promote early-life survival by satiating predators, even if some predators migrate to areas where larval and juvenile anchovy are abundant. At mesoscale distances of 10-100 km, distribution of predators (e.g. YOY and age-1 weakfish [Cynoscion regalis] ) may be important. If the maximum number of prey that can be eaten by predators is reason- ably constant, the effect of predation can be density-depen- satory (Hilborn and Walters, 1992), i.e. predation mortality rate decreases as prey density increases. In support of the third hypothesis, a correspondence analysis on fish species assemblages by year, season, re- gion, and life stage (Jung and Houde, 2003) indicated that distributions and abundances of YOY weakfish, a major predator of bay anchovy in Chesapeake Bay (Hartman and Brandt, 1995), and YOY bay anchovy were closely as- sociated spatially, seasonally, and annually in our six-year study. The major spawning area of bay anchovy is spatially restricted. If predator migration to the area is limited, then as the supply of larvae and juveniles increases, it may satu- rate predator demand, the condition necessary for depensa- tion to be important. It may seem contradictory to propose that density-com- pensation with respect to SSB (the negative sign of j\) and density-depensation with respect to AL (the second or third hypothesis ) can act simultaneously during larval and juvenile stages. Under this circumstance, the number of surviving postlarval anchovies is hypothesized to decrease because of food limitation when larval abundance is high, reducing subsequent predation-related mortality rate on postlarvae and small juveniles. Low abundance of anchovy early-life stages will lead to the opposite effect (Fig. 7). The proposed opposing responses of the early-larval and late- larval-juvenile stages are explained by differences in the spatial scales of distribution and densities of life stages of bay anchovy (Fig. 7). The spatial scale of processes that affect distributions of late-stage larvae and juveniles is large compared to that for early-stage larvae because of the increased dispersal and swimming ability of juveniles. Comparing early-larval and late-larval-juvenile stages of bay anchovy, we propose that effects of prey concentration (the first hypothesis) and SSB level (density-compensa- tion) act primarily on the dynamics of early-larval stages, whereas predation mortality and the inhibitory effects of low DO (density-depensation; the second and third hy- Nursery Ground (3) Fall YOY recruits, adults Late-stage larvae, juveniles, some adults Eggs and larvae Overwintering Recruited anchovy Adult Immigration from tributaries'? Major Spawning Mature adults. / eggs, larvae ground (1) Spring Adult Immigration from ocean? Figure 6 Conceptual model representing bay anchovy (Anchoa mitchilli) life cycle and ontogenetic migration within Chesapeake Bay, and possible immigration of adults from tributaries and coastal ocean. potheses) are more important regulators and controllers, respectively, during late-larval and juvenile stages. The three hypotheses that relate DO, SSB distribution, and recruitment of bay anchovy are not mutually exclusive. If low mean DO level is an indicator of enhanced prey pro- duction and availability to larvae and juveniles, increased prey productivity in the lower bay could enhance bay anchovy recruitment potential by supplying enough zoo- plankton prey to spawning adults, larvae, and juveniles. At the same time, low mean DO in the mid-Bay could confine most spawning bay anchovy to the lower bay. thus increas- ing spawning and larval production there, and possibly enhancing survival of juveniles by predator satiation. Ul- timately, other hypotheses may provide better explanations of the relationships between regional mean DO. latitudinal shifts in distribution of spawners, abundances of spawners. and recruitment of bay anchovy. For example, abundant gelatinous organisms, such as the scyphomedusa (Chn'sa- ora quinquecirra) and the lobate ctenophore \Mnemiopsis leidyi), can be important predators on early-stage anchovy and competitors with juveniles and adults (Purcell et al., Jung and Houde: Recruitment and spawning-stock biomass distribution of Anchoa mitchil/i 75 Early-stage and larvae Density-compensatory Prey is smaller Small scale (1 m-10 km) Densiy of early-stage larvae (1 m-10 m scale) Late-stage larvae and juveniles Density-depensatory Predator is bigger Mesoscale(IO-lOOkm) Recruits Ontogenetic migration Densiy of late-stage larvae (10-100 km scale) SSB Figure 7 Hypotheses and conceptual model of the bay anchovy {Anchoa mitchilli) recruitment process in Chesapeake Bay. The density-compensatory process acts at a small spatial scale during the early- larval stages, whereas the density-depensatory process acts at a broader spatial scale during late-stage larval and juvenile stages. The ontogenetic migration is controlled by dissolved oxygen levels and other hydrological factors. 1994), but their potential role with respect to bay anchovy recruitment could not be defined in our study. For the present, it is clear that most spawning occurs in the lower and mid Chesapeake Bay, from which larval and juvenile anchovies disperse upbay. We hypothesize that food avail- ability is the major factor controlling production of bay anchovy early-larval stages whereas predation becomes more important during late-larval and juvenile stages. Our results and hypotheses implicate density-related pro- cesses, operating at different spatial scales, as regulators of recruitment of bay anchovy in Chesapeake Bay. Acknowledgments We thank S. Leach, E. North, J. Hagy, C. Rilling, J. Cleve- land, A. Madden, D. O'Brien, B. Pearson, D. Craige, T. Auth, and the able crew of RV Cape Henlopen for assistance in field surveys. T. Miller and E. 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Predation mortality of bay anchovy Anchoa mitchilli eggs and larvae due to scyphomedusae and ctenophores in Chesapeake Bay. Mar. Ecol. Prog. Ser. 1 14 :47-58. Ricker, W. E. 1975. Computation and interpretation of biological statis- tics of fish population. Bull. Fish. Res. Board Can. 191: 1-382. Rilling, G. C, and E. D. Houde. 1999a. Regional and temporal variability in distribution and abundance of bay anchovy (Anchoa mitchilli i eggs, larvae, and adult biomass in the Chesapeake Bay. Estuaries 22: 1096-1109. 1999b. Regional and temporal variability in growth and mortality of bay anchovy. Anchoa mitchilli. larvae in Chesa- peake Bay. Fish. Bull. 97:555-569. Rose, K. A.. J. H. Cowan, M. E. Clark. E. D. Houde. and S. B. Wang. 1999. An individual-based model of bay anchovy population dynamics in the mesohaline region of Chesapeake Bay. Mar. Ecol. Prog. Ser. 185:113-132. SAS Institute Inc. 1989. SAS/STAT user's guide, version 6, 4th ed., 1686 p. SAS Institute Inc.. Gary, NC. Jung and Houde: Recruitment and spawning-stock biomass distribution of Anchoa mitchilli 77 Samuels, M. L. 1989. Statistics for the life sciences, p. 409-42. Prentice- Hall. Inc., Upper Saddle River, NJ. Schultz. E. T., R. K. Cowen, K. M. M. Lwiza. and A. M. Gospodarek. 2000. Explaining advection: Do larval bay anchovy lAnchoa mitchilli) show selective tidal-stream transport? ICES J. Mar. Sci. 57:360-371. Sissenwine, M. P. 1984. Why do fish populations vary? In Exploitation of marine communities (R. M. May, ed.l, p. 59-94. Springer- Verlad, Berlin. Smith, E. M., and W. M. Kemp. 2001. Size structure and the production/respiration balance in a coastal plankton community. Limnol. Oceanogr. 46: 473-485. Steel, R. G. D., and J. H. Torrie. 1980. Principles and procedures of statistics. A biometrical approach. 2 nd ed., 633 p. McGraw-Hill Inc. New York, NY. Vazquez-Rojas, A. V. 1989. Energetics, trophic relationships and chemical compo- sition of bay anchovy, Anchoa mitchilli in the Chesapeake Bay. M.S. thesis, 166 p. Univ. Maryland, College Park, MD. Wang, S. B., J. H. Cowan, K. A. Rose, and E. D. Houde. 1997. Individual-based modelling of recruitment variability and biomass production of bay anchovy in mid-Chesapeake Bay. J. Fish Biol. 51 (suppl. A):121-134. Wang, S. B., and E. D. Houde. 1995. Distribution, relative abundance, biomass and produc- tion of bay anchovy Anchoa mitchilli in the Chesapeake Bay. Mar. Ecol. Prog. Ser. 121:27-38. Zastrow, C. E., E. D. Houde, and L. G. Morin. 1991. Spawning, fecundity, hatch-date frequency and young- of-the-year growth of bay anchovy Anchoa mitchilli in mid- Chesapeake Bay. Mar. Ecol. Prog. Ser. 73:161-171. 78 Abstract— Increasing interest in the use of stock enhancement as a man- agement tool necessitates a better understanding of the relative costs and benefits of alternative release strate- gies. We present a relatively simple model coupling ecology and economic costs to make inferences about optimal release scenarios for summer flounder (Paralichthys dentatus), a subject of stock enhancement interest in North Carolina. The model, parameterized from mark-recapture experiments, predicts optimal release scenarios from both survival and economic standpoints for varyious dates-of-release, sizes-at- release, and numbers of fish released. Although most stock enhancement efforts involve the release of relatively small fish, the model suggests that optimal results (maximum survival and minimum costs) will be obtained when relatively large fish (75-80 mm total length! are released early in the nursery season (April). We investigated the sensitivity of model predictions to violations of the assumption of den- sity-independent mortality by includ- ing density-mortality relationships based on weak and strong type-2 and type-3 predator functional responses (resulting in depensatory mortality at elevated densities). Depending on postrelease density, density-mortality relationships included in the model con- siderably affect predicted postrelease survival and economic costs associated with enhancement efforts, but do not alter the release scenario (i.e. combina- tion of release variables ) that produces optimal results. Predicted (from model output) declines in flounder over time most closely match declines observed in replicate field sites when mortality in the model is density-independent or governed by a weak type-3 func- tional response. The model provides an example of a relatively easy-to-develop predictive tool with which to make inferences about the ecological and economic potential of stock enhance- ment of summer flounder and provides a template for model creation for addi- tional species that are subjects of stock enhancement interest, but for which limited empirical data exist. Manuscript approved for publication 17 July 2003 by Scientific Editor. Manuscript received 20 October 2003 at NMFS Scientific Publications Office. Fish. Bull. 102:78-93 (2004). Coupling ecology and economy: modeling optimal release scenarios for summer flounder (Paralichthys dentatus) stock enhancement G. Todd Kellison David B. Eggleston Department ol Marine, Earth, and Atmospheric Sciences, North Carolina State University Raleigh, North Carolina 27695-8208 Present address (for G T. Kellison, contact author): National Park Service/ Biscayne National Park 9700 SW 328 th St, Homestead, Florida 33033 E-mail address (for G T Kellison) todd_kellison 5 nps gov Commercially important marine fish and invertebrate populations are declining worldwide in response to overexploitation and habitat degrada- tion (Rosenberg et al„ 1993; FAO 1998). This reduction in harvestable fishery resources has stimulated increasing interest in the use of hatchery-reared (HR) animals to enhance wild stocks (Munro and Bell, 1997; Travis et al., 1998; Cowx, 1999; Kent and Draw- bridge, 1999). Unfortunately, many stock enhancement programs proceed before ecological concerns are adequately addressed (Blankenship and Leber, 1996), and without the identification of goals or the evaluation of the success of enhancement efforts (Cowx, 1999). If fishery managers can satisfactorily determine that enhancement efforts will have no ecologically significant negative ramifications, then managers should establish specific, quantifiable goals and objectives of enhancement efforts as part of a responsible approach to stock enhancement (Blankenship and Leber, 1996; Heppell and Crowder, 1998). Once such goals have been established, managers should identify stocking approaches that will lead to the most cost-efficient realization of enhancement goals — a process that can be accomplished with the aid of coupled ecological and economic models. Although numerous (advanced) models (conceptual and species-specific) exist to predict the biological and ecological impact of alternative enhancement scenarios (e.g. Botsford and Hobbs, 1984; Salvanes et al„ 1992; Barbeau and Caswell, 1999; Sutton et al., 2000), there are few models ( of which we are aware) that have attempted to link the biological and ecological results of stock- ing efforts (e.g. addition of biomass to a stocked population) with the economic costs associated with various release scenarios (e.g. Botsford and Hobbs, 1984; Hobbs et al., 1990; Hernandez-Llamas, 1997; Kent and Drawbridge, 1999). Such a link is critical to the responsible use of funding to rebuild or manage fisher- ies, and for the comparison of predicted costs of enhancement versus alternative management techniques. In North Carolina, there has been recent interest in stock enhancement with summer flounder (Paralichthys dentatus) (Waters, 1996; Rickards, 1998; Waters and Mosher, 1999; Burke et al., 2000; Copeland et al. ' ) because of a combination of heavy commercial and recreational exploitation, established techniques for mass hatchery-rearing (Burke et al., 1999), and considerable knowledge of summer flounder life his- tory (Powell and Schwartz, 1977; Burke et al., 1991; Burke, 1995). Nevertheless, there have been no large-scale release experiments ( and subsequent collection of data) by which to make empirical inferences about stock enhancement potential for this species. We present a compartmental model, parameterized from mark-recapture field experiments, Copeland, B. J., J. M. Miller, and E. B. Waters. 1998. The potential for flounder and red drum stock enhancement in North Carolina. Summary of workshop, 30-31 March. 1998, 22 p. ' (Available from North Carolina State Univ, Raleigh. NC 27695.] Kellison and Eggleston: Modeling release scenarios for Paralichthys dentatus 79 Table 1 Range of numbers of summer flounder (Paralichthys dentatus) released (and resulting postrelease densities), sizes-at-release, and dates of release simulated in the model. Number released Postrelease density Size-at-release Dates of release 100-400,000 0.001-4.0 30-80 mm 1 April-15 July that incorporates size of fish released, date-of-release, and number offish released to calculate 1) predicted numbers of survivors and 2 ) economic costs associated with varying re- lease scenarios under density-independent mortality. We in- vestigated the sensitivity of model predictions to violations of the assumption of density-independent mortality because there is abundant evidence that mortality rates, or processes underlying mortality rates (e.g. growth), are affected by den- sity-dependent relationships in the wild ( see, for recent ex- amples. Bucket et al., 1999; Bystroem and Garcia-Berthou. 1999; Jenkins et al, 1999; Kimmerer et al., 2000). We did so by repeating model simulations under varying density- mortality relationships (depensatory in nature at elevated densities ), using experimental evidence from our own field studies and published observations for similar species to parameterize density-mortality relationships. Additionally, we used a scenario in which the density-mortality relation- ship changed over time to make inferences about the effect of more complex density-mortality relationships on postrelease mortality of juvenile summer flounder. Finally, we generated predicted temporal patterns of field densities under vary- ing density-mortality relationships and compared them with observed (in the field) patterns to determine whether model output under the considered density-mortality relationships matched actual patterns in the field. The model provides an example of a relatively easy-to-develop predictive tool with which to make inferences about the ecological and economic potential of stock enhancement with summer flounder and provides a template for model creation for additional species that are subjects of stock enhancement interest, but for which limited empirical data exist. Materials and methods Background In North Carolina, wild summer flounder recruit to shal- low-water estuarine nursery habitats from February to May, after which small juvenile (20-35 mm total length [TL] ) densities range from -0.1 to 1.0 fish/m 2 (Burke et al., 1991; Kellison and Taylor 2 ). Juveniles subsequently make an ontogenetic habitat shift to deeper waters ( Powell and Schwartz, 1977), apparently after reaching a total length 2 Kellison, G. T., and J. C. Taylor. 2000. Unpubl. data. De- partment of Marine, Earth, and Atmospheric Sciences, North Carolina State University, Raleigh, NC 27695-8208. of -80 mm (Kellison and Taylor 2 ). By mid-July, densities of juvenile summer flounder in the shallow water nursery habitats are near zero (Kellison and Taylor 2 ). Model pathway Our compartmental model simulated the daily mortality and growth of different-size hatchery-reared (HR) fish released in the field over a 105-day period ( 1 April to 15 July, based on observed field abundances) in a hypotheti- cal release habitat of 10 hectares. The model predicted the percentage of released fish surviving and economic cost- per-survivor under 2730 release scenarios for a specified number offish released (see below). To begin the model, a value of number offish released (NFR) ranging from 100 to 400,000 (Table 1) was chosen (Fig. 1), resulting in postre- lease densities (assuming even postrelease distribution) of 0.001-4.0 fish/m 2 . These values included a range of densi- ties of juvenile summer flounder observed in wild nursery habitats ( -0-1 fish/m 2 ; mean -0.05 fish/m 2 ; Kellison and Taylor 2 ), but also included unusually high densities (>1 fish/m 2 ) in order to examine how such release strategies would affect model output (we did not examine densities >4 fish/m 2 because of a lack of data on fish response to resource limitation likely to occur as densities increased past values for which we had empirical growth data). Each group of NFR was initially assigned a "size-(TL) at-release" of 30 mm (the smallest size-at-release simulated in the model), after which a size-dependent economic cost associ- ated with the release of the 30-mm-TL fish was calculated (see below). The release group was then assigned a mini- mum Julian "day of release" of 92 (corresponding to 1 April, the earliest release date simulated in the model). A range of Julian days of release was included in the model because field-estimated growth rates were dependent on Julian day (Kellison, 2000), and growth rates are potentially impor- tant to the determination of mortality rates (Rice et al. 1993). With this model, we then calculated daily mortality and growth (described below) in the hypothetical release habitat over the number of days at large (DAL), where DAL = 197 (the Julian day corresponding to 15 July) - 92 (Julian release day), and output a number of survivors and a calculated cost- per-survivor (CPS), where CPS = cost associated with release -f predicted number of survivors, 80 Fishery Bulletin 102(1 I Input number released (NR) ' assign size-at-release (SAR) * calculate cost of release (COR) <— Size-at-release N Density- independent Julian day ' assign date of release (DOR) < I ' determine number of survivors (NOS) DAL at the beginning of the day (= «\ initial # of fish or # surviving from previous day) / / 1 da ly mortality ^ da ly growth *M * calculate number of survivors and total length (TL) at the end of the day 1 I I * output - number of survivors - cost per survivor (CPS) \ / Figure 1 Model flowchart. Dashed arrows represent model "backloops" to the indicated compartment where simulations continue with the next value of the arrow-labeled variable. Side graphs indicate the three relationships between density and mortality (number offish consumed) that were considered, and the general relationship between growth and Julian day. for the initial release scenario of fish size = 30 mm TL. Julian day = 92, and an NFR input determined by the mod- eler). The model then looped back to the "date-of-release" step and simulated the release of the 30-mm-TL fish for Julian release days 93-197, outputting a predicted number of survivors and cost-per-survivor for each release date. The model then repeated all previous steps under sequentially larger size-at-release scenarios, looping back to the "size- at-release" step and simulating the release of fish ranging in size from 32-80 mm TL fish in steps of 2 mm TL. The model output was a predicted number of survivors and economic cost-per-survivor for each release day (92-197) for each size-at-release (Fig. 1). Thus, for each input NFR, there were 26 size-at-release possibilities x 105 Julian days of release possibilities, which resulted in 2730 simulations, each of which resulted in a predicted number of survivors and cost-per-survivor for that particular release scenario. For each input NFR, the results from the 2730 simulations were plotted on two response surfaces, with an .v-axis of size-at-release, a y-axis of date-of-release, and a 2-axis of either 1) predicted number of survivors (NOS), or 2) cost- per-survivor ( CPS ), to identify release scenarios resulting in the maximum predicted number of survivors and minimum cost-per-survivor, respectively. The scenarios resulting in the maximum predicted number of survivors and minimum cost-per-survivor were not necessarily identical. Calculation of mortality, growth, survival, and economic costs associated with release During each day at large (DAL), released fish were sub- jected to a density-independent daily mortality rate of 0.02153, derived from postrelease mark-recapture data of HR summer flounder (Kellison et al., 2003b). In deriv- ing this value, mean postrelease densities were used to estimate a total number of survivors from experimental releases. Daily survival was then calculated with the equation Kellison and Eggleston: Modeling release scenarios for Paraltchthys dentatus 81 NFR x S D DAL = NOS, where NFR = number released; S D = daily survival; DAL - days at large (from release date until Julian day 197); and NOS = estimated number of survivors. Daily mortality (M D ) was then calculated from the equation M r 1-Sr At the end of each simulated day, all fish that were alive increased in growth according to the equation G D = -0.0061 x Julian day + 1.2487, which was derived from mark-recapture data (Kellison, 2000), and in which G D is daily growth in millimeters. Fish reaching 80 mm TL during the model (i.e. by 15 July) were considered to make an ontogenetic hab- itat shift to deeper waters. These fish were then subjected to one half year of natural mortality to simulate mortality- related losses from deeper-water habitats (M=0.28; Froese and Pauley, 2001). Remaining fish, now having survived -one year of natural mortality, were considered to be sur- vivors (available to the commercial fishery), which is a con- servative assumption because 1-yr-old summer flounder are only partially recruited to the commercial fishery. All fish not reaching a total length of 80 mm were assumed to perish. To determine size-dependent economic costs offish pro- duction, we used the following regression equation derived for Japanese flounder (Paralichthys olivaceus) by Sproul and Tominaga ( 1992 ) because equivalent economic data for summer flounder were unavailable: C PF = 14.24 + 1.234 x TL, where C PF = the cost per fish in Japanese yen (¥); and TL = the total length of the HR fish. Costs were then converted into US$ by using an exchange rate of 106. 7¥ per 1 US$ (universal currency converter). We feel use of this cost-of-fish-production equation is appro- priate because the Japanese flounder is closely related and similar in life history traits to the summer flounder (Tanakaet al., 1989; Burke etal., 1991 ), resulting in similar optimal rearing practices for hatchery-reared Japanese and summer flounder (Burke et al., 1999), and thus likely simi- lar rearing costs. Additionally, the scale of Japanese floun- der hatchery production is similar to, or greater than, other government subsidized hatchery production programs (e.g. red drum in Texas, cod in Norway [Svasand, 1998] ). Density-mortality relationships We tested the sensitivity of the model results (optimal predicted number of survivors and cost-per-survivor esti- mates under varying NFRs) to violations of the assumption 0.50 -i ~ 0.40 * Type 2 - weak k * Type 2 - strong E 0.30 - * ^—^-^ d Type 3 - weak ra k f ^^^^ Type 3 - strong o t 0.20 o Q. O *# ^^^^ o- 0.10 -j |^»W °°OOnnn„ 12 3 4 Density (number of fish/m 2 ) Figure 2 Proportional mortality curves for juvenile summer flounder corre- sponding to weak and strong type-2 and type-3 mortality responses. of density-independent mortality by incorporating varying types and strengths of density-dependent mortality (depen- satory in nature at elevated densities; see below) into the model. As a basis for these sensitivity analyses, we assumed that predation was the driving mechanism underlying the postrelease mortality of HR summer flounder under the densities examined (Kellison et al., 2000; Kellison et al., 2003b). Thus, we made daily mortality rates correspond to either a type-2 or type-3 predator functional response (Holling, 1959; see Lindholm et al., 2001 for example), in which proportional mortality due to predation decreases with increasing density (type-2 response) or increases ini- tially with increasing density, reaches a zenith, and then decreases with increasing density (type-3 response) (Fig. 2). Both type-2 and type-3 responses result in decreasing (depensatory) mortality at elevated prey densities due to predator satiation. We did not include scenarios in which mortality increased at elevated densities (as would be expected when densities reached those likely to result in resource limitation ) because we did not include in the model elevated release densities likely to result in resource limita- tion. We parameterized the daily mortality curves so that each response (type 2 or 3) incorporated the daily mortality rate of 0.02153. These mortality curves contain mortality values that are within ranges reported in the literature for other species of juvenile marine fishes (Bax, 1983; Houde, 1987; Nash, 1998; Rose et al, 1999). To make further infer- ences about the importance of density-dependent mortal- ity to model results, we included a 1) weak and 2) strong form of each functional response (types 2 and 3) (Fig. 2), as well as scenarios in which the response shifted temporally from 3) type 2 to 3, and 4) type 3 to 2 at the midpoint of the nursery season (Julian day 145). We included both the weak and strong forms of the type-2 and type-3 functional responses to determine the extent to which variation in the strength of the functional response would affect model pre- dictions. The strength of the functional response could vary because of annual variation in the presence or abundance of prey or because predators could affect the density-mor- tality relationship (see, for example, Hansen et al., 1998). 82 Fishery Bulletin 102(1) For example, a strong positive (compensatory) density- mortality relationship driven by predators might become weaker in years when predator abundance was lower than average. We included the temporally shifting functional response scenarios to determine the extent to which tem- poral variation in the form of the functional response would affect model predictions. Temporal variation in the form of the functional response might occur because of temporal changes in the predator community, or because of changing predator-prey size dynamics (e.g. Stoner, 1980; Black and Hairston, 1988). For example, as the nursery season for summer flounder progresses, proportionately greater num- bers of juveniles grow to sizes at which they are capable of preying on smaller juveniles (Kellison, personal obs. ). If cannibalistic summer flounder exhibit a different predatory functional response from that of the predator guild commu- nity predominating earlier in the season, then the density- mortality relationship may change seasonally. We replicated all model simulations over each of the six density-mortality relationships (weak and strong types 2 and 3, and shifting patterns [type 2 to 3 and type 3 to 2] ) to determine optimal release scenarios (maximum num- ber of survivors, minimum cost-per-survivor) under each relationship. We then compared results to those obtained under density-independent mortality to make inferences about the importance of density-mortality relationships to model results. Correspondence between predicted and observed temporal abundance patterns Different density-mortality relationships may result in distinct temporal patterns of abundance (e.g. rapid versus more gradual declines in abundance) depending on initial densities. We generated predicted patterns of temporal field abundance of juvenile summer flounder under den- sity-independent mortality and four additional density- mortality relationships (governed by weak and strong type 2 and 3 functional responses) and under varying initial densities (0.1, 0.3, and 0.5 fish/m 2 ) to examine whether the different density-mortality relationships would result in distinct temporal patterns of abundance. We used 1998-99 field data and logarithmic or polynomial regression models to generate curves that best fitted (based on r 2 values) observed (from natural nursery sites) temporal declines in abundance under varying initial densities. We compared the best-fit curves to those predicted by the model under density-independent and four additional density-mortal- ity relationships. These comparisons allowed us to make qualitative inferences about which density-mortality relationship* s) resulted in the best match between pre- dicted and observed temporal patterns of abundance. Model assumptions The assumptions of the model are the following: 1 Daily mortality is independent of size. Although there is strong evidence that mortality of fishes in the wild is size-dependent (Lorenzen, 2000 ), particularly in regard to the importance of size to susceptibility to predation (see, for example, Elis and Gibson, 1995; Furuta, 1999; Manderson et al., 1999), we found no evidence (from recaptures of released hatchery-reared fish ) of size- selective daily mortality for juvenile summer flounder ranging in size from -30-80 mm TL in shallow-water nursery areas (Kellison et al., 2003a). Implications for violations of this assumption are addressed in the "Dis- cussion" section. 2 Daily growth is independent of fish density. We based this assumption on field experiments that indicated no growth limitation at densities roughly equal to the maximum densities explored in the model (Kellison et al., 2003b). Similar findings (i.e. no food-limitation or density-dependent growth) have been reported for similar-size plaice in shallow-water nursery habitats (van der Veer and Witte, 1993). 3 Economic cost per fish (C PF ) is independent of the number of fish acquired for release (i.e. within the range of numbers offish released in model simulations, there is no decrease in cost per fish as the number of fish acquired from the production hatchery for release increases). This assumption is likely to be valid over changes in numbers of fish released common to stock enhancement programs (Sproul and Tominaga, 1992) but may not be valid as numbers released change over orders of magnitude because of economy of scale (Adams and Pomeroy 1991; Garcia et al., 1999). 4 There is no emigration from the release habitat until fish exhibit an ontogenetic shift in habitat at 80 mm TL. Although pre-ontogenetic habitat shift emigration may not truly be zero, we feel that it is also unlikely that pre- ontogenetic habitat-shift emigration accounts for more than a minimal amount of loss of released fish from the habitat of release, as supported by several points. First, rates of pre-ontogenetic shift emigration in wild juveniles are apparently low (Kellison and Taylor 2 ), suggesting that large-scale spatial migrations may not be part of the behavioral repertoire of early juvenile summer flounder. Second, irregular temporally repli- cated sampling outside of experimental release sites resulted in zero captures of emigrating hatchery-reared fish (Kellison et al., 2003b). Third, emigration rates of closely related HR Japanese flounder {Paralichthys olivaceus) are reported to be very low (Tominaga and Watanabe, 1998). In combination, these points suggest that our zero emigration assumption is appropriate. 5 Fish that do not grow to 80 mm TL during the model period (i.e. by 15 July) do not survive. Although this assumption cannot be examined with our field data, data do show that juvenile summer flounder are absent from shallow-water nursery habitats by mid to late July (Kellison et al. 3 ). Thus, all fish have either perished or made ontogenetic habitat shifts to deeper habitats by this time. Our field observations suggest that the deeper habitats to which larger flounder :t Kellison, G. T., J. C. Taylor, and J. S. Burke. 2000. Unpubl. data. Department of Marine, Earth, and Atmospheric Sciences, North Carolina State Univ., Raleigh, NC 27695-8208. Kellison and Eggleston: Modeling release scenarios for Paralichthys dentatus 83 make ontogenetic habitat shifts are inhabited by relatively high densities of potential predators (e.g. blue crabs, age 1+ flounders, red drum [Sciaenops ocellatus], searobin [Prionotus sp.], and lizardfish [Synodus sp.] ), which may be considerably less abundant in shallow-water habitats. These relatively large and abundant predators would presumably expose small migrating fish to high rates of predation (see, for example, Elis and Gibson, 1995; Furuta, 1999; Manderson et al„ 1999). This assumption is supported by research with the congener Japanese flounder (Paralich- thys olivaceus). Although a range of sizes of hatchery-reared Japanese flounder may survive within relatively shallow nursery habitats, fishes less than 90 mm TL moving into relatively deep waters are poorly rep- resented in subsequent age classes, most likely due to predation-induced mortality (Yamashita et al., 1994; Furuta, 1999). There is no relationship between length of rearing period (time spent in the hatchery environment) and probability of postrelease mortality related to behavioral deficits (Olla et al., 1998). Hatchery-specific selection pressures may result in HR fish that are behaviorally selected to survive in the hatchery and not in the wild (see Olla et al., 1998; Kellison et al., 2000; for discus- sion). We assume that behavioral deficits are not exacerbated with time spent in the hatchery (i.e. behavioral deficits are equal for all sizes-at-release). Results The most important factor affecting the number of survivors (and therefore percent survival) was size-at-release because the greatest numbers and percentages of survi- vors were always produced by releasing the largest fish possible (80 mm TL in the model). Number of survivors decreased with decreas- ing size-at-release and with increasing Julian day of release (Fig. 3A). The cost-per-survivor ( CPS ) was also most affected by size-at-release, such that CPS decreased with increasing size- at-release (Fig. 3B). CPS generally increased with increasing Julian day of release (Fig. 3B), although this effect was less important than the effect of size-at- release. Because mortality was originally assumed to be density-independent, the optimal cost-per-survivor did not vary with the number offish released (Fig. 4), and the relationship between number offish released and number of survivors was linear (Fig. 4), such that the maximum number of survivors were generated from the greatest number offish released (NFR=400,000). 220 20 80 90 220 Figure 3 Response surfaces of iAi number offish survivors (summer flounder I and (Bi cost-per-survivor (CPS) as a function of date of release and size at release at number released (NR) = 5000 (postrelease density=0.05) under density-independent mortality. CPS values greater than $10 were set equal to $10 for ease of presentation. Sensitivity of model predictions to violations of density-independent mortality assumption Model results varied considerably under the various den- sity-mortality relationships (Fig. 5, A and B), indicating the importance of knowledge of the relationship between numbers of fish released (density) and mortality in the wild to predicting optimal release scenarios. Variation in model output was dependent on the type and strength of Fishery Bulletin 102(1) the density-mortality relationship. For example, at postre- lease densities of 0.5 fish/m 2 (NFR=50,000), survival of released flounder under density-independent mortality was ~28% higher than that predicted under strong type-3 mortality, but only -2% higher than that predicted under weak type-2 mortality (Fig. 5A). At postrelease densities of 0.001 fish/m 2 (NFR=100), survival of released flounder under density-independent mortality was ~41% higher 450000 -I m 400000 • § 350000 • £ 300000 • « 250000 ; ° 200000 E 150000 | 100000 z 50000 — — optimal number of survivors : — o— optimal CPS ^^^" r 1 60 : 1 50 O 1.40 g 1 30 -g -1,20 5 [110 <§ - 1 00 g ■0.90 < ■0 80 - 0.70 C 0-60 W 50000 10000 15000 20000 25000 30000 35000 40000 Number released Figure 4 Optimal number of fish survivors and cost-per-survivor as a function of varying numbers of summer flounder released under density-indepen- dent mortality. 12 3 4 5 Density (number of fish/m 2 ) Figure 5 l A i Optimal percent survival and iBi optimal cost-per-survival (US$) as a func- tion of postrelease density undci density-independent and varying density- dependent, mortality relationships for summer flounder. than that predicted under strong type-2 mortality, but -2% less than that predicted under strong type-3 mortality ( Fig. 5A). In contrast, when postrelease densities were relatively high, there was less of an impact of density-mortality rela- tionship on postrelease survival and costs associated with stock enhancement. For example, at postrelease densities of three fish/m 2 (NFR=300,000), survival of released floun- der differed by less than 4% between density-independent, weak or strong type-2, and weak type-3 mor- tality, although survival under strong type-3 mortality was ~99c less than that predicted under density-independent mortality and -11% less than that predicted under strong type-2 mortality (Fig. 5A). Thus, the model results were most sensitive to violations of the assumption of density-independent mortality at low densities offish released in the field. Type-2 mortality As with density-indepen- dent mortality, the most important factor affecting number of survivors and cost per survivor under type-2 mortality was size-at- release (Fig. 6, A and B). In all simulations, the greatest number of survivors was pro- duced by releasing the largest fish possible. Number of survivors decreased with increas- ing Julian day of release (Fig. 6A). There was a considerable interaction between size- at-release and number of fish released, such that low postrelease densities were subjected to relatively high proportional mortality. Thus, when fish were released in low numbers and at small sizes, the fish were subjected to relatively high proportional mortality rates for long periods of time (while they grew towards the 80-mm-TL ontogenetic shift size) and consequently produced few or no survi- vors (Fig. 6A). Optimal release scenarios under strong type-2 mortality produced substantially lower (>40% in some cases) percent survival (and therefore substantially higher cost-per-survivor) estimates at low to moderate numbers released (NFR= 100-50,000; postrelease density=0.001-0.5 fish/m 2 ) than under density-independent mortality (Fig. 5, A and B). Differences in percent survival estimates (and thus cost-per-survivor estimates) between density-indepen- dent survival and weak or strong type-2 mortality declined to less than 5 r i when the numbers released increased to 25,000 (postrelease density=0.25 fish/m 2 ) under weak type-2 mortality and 75.000 (postrelease density=0.75 fish/m 2 ) under strong type-2 mortality (Fig. 5A). Thus, model predictions under density-inde- pendent mortality differed most from predictions under mortality governed by - density-independent -type 2 - weak - type 2 - strong -type 3 - weak ■type 3 - strong density-independent type 2 - weak type 2 - strong type 3 - weak type 3 - strong Kellison and Eggleston: Modeling release scenarios for Paralichthys dentatus 85 B a type-2 predator functional response when postrelease densities were relatively low. Type-3 mortality As in all other simulations, the most important factor affecting number of survivors under type-3 mortality was size- at-release, such that the greatest numbers of survivors were always produced by releasing the largest fish possible (Fig. 7A). Number of survivors decreased with increasing Julian day of release (Fig. 7A). Percent survival was considerably lower (>25% in some cases) under type-3 mortality than under density- independent mortality at moderate to high numbers released (NFR=10, 000-400, 000) (Fig. 5 A). In nearly all simulations, the lowest CPS values were produced by releasing the larg- est fish possible (Fig. 7B). The exceptions to the "large size = optimal CPS" rule occurred when postrelease densities were small (cor- responding to numbers released of 100, 500, and 1000) and the mortality curve was type 3 (weak or strong). In these instances, mortality was sufficiently low at low release densities ( Fig. 7B ) so that the difference in overall sur- vival between small- and large-released fish was small enough to be overridden by the in- creased cost of the larger fish, and the mini- mum CPS was obtained when small (42-44 mm TL) fish were released (e.g. Fig. 7B). At low numbers released (NFR=100-1000), optimal cost-per-survivor was considerably lower (>45% in some cases) under type-3 mortality than under density-independent mortality (Fig. 5A). As NFR increased, CPS under type-3 mortality became greater ( -40^ in some cases) than that achieved under den- sity-independent mortality (Fig. 5B). Temporal shift in functional response from type 2 to type 3, and from type 3 to type 2 The optimal numbers of survivors under varying numbers released were identical, and optimal CPS values nearly identical, when the form of the functional response changed from a type 2 to a type 3, and from a type 3 to a type 2, midway through the juvenile nurs- ery season (Fig. 8, A and B). The differences at low postrelease densities between optimal CPS values under shifting type 2 to type 3 and type 3 to type 2 scenarios (Fig. 8A) occurred because initial mortality under the type-3 functional response was sufficiently low that the difference in overall survival between small- and large-released fish was small enough to be overridden by the increased cost of the larger fish (Fig. 8A). The minimum CPS was obtained when small (42-44 mm TL) fish were released (in all other cases, optimal results were obtained when size-at-release was maximized) (Fig. 8A). The major difference between the two shifting scenarios is that the re/ease Figure 6 Response surfaces of (A) number offish (summer flounder I survivors and (B) cost-per-survivor (CPS) as a function of date of release and size at release at number released (NR) = 5000 (postrelease density=0.05l under a strong type-2 functional response. CPS values greater than $10 were set equal to $10 for ease of presentation. release dates producing optimal results for a given number of fish released varied depending on the direction of the shifting functional response. For example, when the func- tional response shifted from a type 2 to a type 3, a release of 100,000 HR organisms achieved optimal results when release occurred early in the season (Julian day <145) (Fig. 9A). When the functional response shifted from a type 3 to a type 2, a release of 100,000 HR summer floun- der achieved optimal results only when releases occurred later in the season (Julian day >145) (Fig. 9B). When the 86 Fishery Bulletin 102(1) functional response shifted from a type 3 to a type 2, releas- ing 100,000 HR organisms prior to Julian day 146 resulted in markedly decreased survival (and therefore increased CPS ) compared to results obtained from releases after day 146 (e.g. releasing on Julian day 92 resulted in a decrease in number of survivors and an increase in CPS of 22.8% and 29.7%, respectively) (Fig. 9B). Thus, date-of-release had a significant effect on the results (and therefore in determining optimal release strategies) when the relation- ship between density and mortality changed temporally, suggesting that the presence of a temporal shift in the func- 500 £ 400 300 200 E z 100 220 OaV' Size at re/ease Figure 7 Response surfaces of (A) number offish (summer flounder) survivors and (B) cost-per-survivor (CPS) as a function of date of release and size at release at number released (NR) = 500 (postrelease density=0.005) under a strong type-3 functional response. CPS values greater than $10 were set equal to $10 for ease of presentation. tional response of the predator guild would have consider- able effects on the number of survivors and CPS for stock enhancement efforts with juvenile summer flounder. Correspondence between predicted and observed temporal abundance patterns Under the assumption of a type-2 functional response, predicted declines in juvenile summer flounder density over time were rapid when initial density was relatively low (i.e. 0.1 fish/m 2 ) (Fig. 10, A and B). These predictions contrast with those observed in the field, in which declines at relatively low initial densities were gradual (compare Fig. 10A and 10B to Fig. 10F). Under the assumption of a type-3 functional response, predicted declines were rapid when initial density was relatively high (i.e. 0.5 fish/m 2 ) I Fig. 10, C and D). These results generally contrast with those observed in the field, in which declines at relatively high densities were much less rapid than those predicted under a strong type-3 functional response, and somewhat less rapid than those predicted under a weak type-3 functional response (Figs. 10F and 11). Under density-independent mortality, there was little difference in predicted declines in juvenile summer flounder density over time between the three initial density levels (0.1, 0.3, and 0.5 fish/m 2 ); in each case there was a gradual decrease in density over time (Fig. 10E). These results were similar to those observed in the field, although declines at rel- atively high densities in the field were some- what more rapid than those predicted under density-independent mortality ( compare Figs. 10E and 10F). Thus, a density-mortality rela- tionship lying between that generated under density-independence and that generated under the weak type-3 functional response in the model would most closely predict the temporal declines observed in the field. Discussion Implications for stock enhancement of summer flounder Regardless of the relationship between den- sity and mortality, size-at-release was the most important variable in the model affect- ing survival and costs associated with stock enhancement of summer flounder. The model predicts that under all release scenarios, 1) survival will be maximized and 2) costs asso- ciated with stock enhancement (i.e. cost per survivor) will be minimized when HR fish are released at the largest size possible. From a survival standpoint, these results are not Kellison and Eggleston: Modeling release scenarios for Paralichthys dentatus 87 surprising. Larger fish spend fewer days than smaller fish in the wild nursery habitats before making an ontogenetic habitat shift to deeper waters and thus are susceptible to daily natural mortality for fewer numbers of days than are smaller fish. Thus, total mortality of smaller fish is greater than that of larger fish. Additionally, although we chose to make mortality independent of size in the model, abundant literature suggests that natural mortality (especially due to predation ) may decrease with increasing size by mecha- nisms such as enhanced resistance to starvation, decreased vulnerability to predators, and better tolerance of environ- mental extremes (Sogard, 1997; Hurst and Conover, 1998; Lorenzen, 2000). Thus, the difference in predicted survival between 1 ) relatively large and relatively small fish and 2 ) fish released early versus late in the season in our model would be even greater if larger summer flounder suffered lower natural mortality than smaller fish. Furthermore, the daily mortality estimate used in the density-inde- pendent simulations and to parameterize the different types of density-mortality relationships may have been an underestimate of daily mortality (Kellison, 2000). If a greater estimate of daily mortality had been used, the dif- ference in predicted survival between relatively large and relatively small fish in our model would have been further exacerbated because smaller fish spend longer amounts of time in the model growing to the 80-mm-TL ontogenetic shift size. These conclusions are supported by empirical research demonstrating that relatively large released HR fish suffer lower mortality than relatively small HR fish released in the field (e.g. Yamashita et al., 1994; Leber, 1995; Willis et al., 1995; Tominaga and Watanabe, 1998; Svasandetal.,2000). Although the survival predictions of the model (total mortality decreases with increasing size-at-release) are not surprising, the economic (cost-per-survivor) predic- tions were unexpected. The paradigm for stock enhance- ment strategy is that the rearing of relatively large fish for release is cost prohibitive, so that mass releases of relatively small, inexpensive-to-rear fish are a better strategy than the release of larger, expensive-to-rear fish (Kellison, personal obs.). Thus, relatively small juveniles are released in virtually all current stock enhancement programs (e.g. Russell and Rimmer, 1997; Masuda and Tsukamoto, 1998; McEachron et al., 1998; Svasand, 1998; Serafy et al., 1999). Nevertheless, large-scale hatcheries and grow-out facilities are using ever-increasing technol- ogy to minimize the costs associated with the production of relatively large fishes (Sproul and Tominaga, 1992). Thus, for species for which 1) hatcheries are capable of producing relatively large fish at relatively low costs (as is likely for summer flounder), and 2) postrelease survival rates increase with release size, release scenarios utilizing the largest fish possible may maximize the potential (i.e. produce maximum survival at minimum costs ) of stock en- hancement efforts. In these cases, the "small fish maximize stock enhancement potential" paradigm might be replaced with a "large fish maximize potential" paradigm. As a ca- veat, this "large fish" strategy may be limited by spatial limitations of hatcheries in producing large numbers of relatively large fish. Because reared fish generally must 1 40 i */» ^_ 1.20- o 2 1 00- w 80- (1> Q. 60- If) O 40- O Type 2 to 3 Type 3 lo 2 20-1— -! , 1 r Postrelease density Figure 8 Optimal lA) economic cost-per-survivor and (B) per- cent survival of released hatchery-reared summer flounder under temporally shifting functional re- sponses of type 2 to type 3 and type 3 to type 2. be kept below critical densities in hatchery environments because of water quality and fish interaction issues (e.g. cannibalism), larger fish necessarily require more space than smaller fish for rearing. If the demand for space to rear large quantities of large fish can be realized, then the model simulations indicate that stock enhancement strat- egies in which size-at-release is maximized will produce the maximum number of survivors. Although not as important as size-at-release, Julian day of release had a significant effect on survival and cost-per- survivor in the model, such that enhancement efforts were always more successful (more survivors, lower costs) when fish were released at the earliest Julian day possible. These results occurred because growth in the model decreased with increasing Julian Day. Although the mechanisms un- derlying this decrease in growth with increasing Julian day are unknown, they may be related to decreased prey avail- ability or metabolic efficiency as temperatures increase with increasing Julian day (Malloy and Targett, 1994a, 1994b; Fujii and Noguchi, 1996; Howson, 2000). Thus, for a given size-at-release, fish released earlier in the season experienced greater growth rates than fish of the same size-at-release released later in the season and therefore reached the 80-mm-TL ontogenetic shift size faster (over a period of fewer days) than fish released later in the season. Thus, fish released earlier in the season were susceptible to natural mortality for fewer days than fish released later in the season and therefore suffered lower total mortality. These results emphasize the importance of knowledge of possible time-dependent growth in the field prior to stock enhancement efforts. Fishery Bulletin 102(1) Is density important? Effects of varying density-mortality relationships Our results suggest that the relationship between density and mortality has the potential to significantly affect opti- mal release scenarios associated with stock enhancement efforts. Because the original simulations were performed under density-independent mortality, the number of survivors originally increased linearly with the number B 1e+5 (/> 8e+4 o > > 6e+4 tfl n m 4e+4 a h 3 2e+4 z 80 released, resulting in a density-independent cost-per- survivor. Thus, when mortality is independent of density (over a given range of densities) for a target species for stock enhancement, managers will maximize the number of survivors produced by releasing the greatest number of fish possible within that range for a given size class. When mortality varied with density of released fish, the number of survivors and cost-per-survivor depended on the den- sity-mortality relationship. In some cases, optimal results (maximum survival and minimum cost) differed depending on whether the response variable was number of survivors or cost-per-survivor. Under the assumption of a strong type-3 functional response and under relatively low postrelease densities, survival was optimized (maximized) by releasing the largest fish ( 80 mm TL) possible; however, cost-per-survivor was optimized (mini- mized) by releasing smaller fish (42-44 mm TL). This result occurred because mortality at low postrelease densities was sufficiently low that the difference in total mortality attributed to the longer "susceptibility" period of the smaller fish was insufficient to override the economic advan- tage of releasing smaller fish. Simulations under shifting functional responses (type 2 to type 3 and type 3 to type 2) produced optimal results similar to those obtained when nonshifting type- 2 or type-3 functional responses were employed because densities were generally reduced to such low numbers by the time the shift occurred that the changing density-mortality relationship was inconsequential. Importantly, when functional responses shifted temporally, the predicted number of survivors and economic cost per survivor was at times very dependent on date of release, suggesting that identifying or ruling out shifting functional responses in the wild may be critical to accurate prediction of response vari- ables (survivors and economic costs) associated with stock enhancement. Although we are not aware of reports in the literature of shifting functional responses in the wild, we are also not aware of studies that have tested for such a phenomenon, possibly because of the logisti- cal difficulties inherent in identifying a shifting functional response. Correspondence between predicted and observed temporal abundance patterns Figure 9 (A) Response surface of optimal number of summer flounder survivors as a function of date of release and size at release at number released (NR) = 100,000 (postrelease density=1.0 fish/m 2 1 under the assumption of a temporally shifting functional responses from type 2 to type 3. Response surfaces of optimal number of survivors as a function of date of release and size at release at number released (NR) = 100. 000 (postrelease density=1.0 fish/m 2 > under the assumption of a temporally shifting functional responses from type 3 to type 2. Predictions of field abundance patterns of juve- nile flounder density over time were noticeably different under density-independent mortality and density-dependent mortality governed by type-2 and type-3 functional responses. For example, our simulations predict that fish den- sity should decrease rapidly under relatively low initial densities if the functional response is type 2, decrease rapidly at relatively high initial densities if the functional response is type 3, and Kellison and Eggleston: Modeling release scenarios for Parahchthys dentatus 89 OS- 04- 0.3 0.2 01 00 E Strong type 2 Strong type 3 150 Dl B Weak type 2 05 0.4 3 02 110 130 150 170 190 210 D Weak type 3 Julian day Figure 10 Predicted temporal trends in summer flounder abundance under initial densities of 0.5, 0.3, and 0.1 fish/m 2 under the assumption of a functional response that is a (A) strong type 2. IB) weak type 2, (C) strong type 3. i D i weak type 3. and under the assumption of (E) density-independent iDIl mortality. The curves in iFi are best fitted (highest r 2 value) to data collected in Duke Beach 1999 (curve a, r 2 =0.82). Haystacks Marsh 1999 (curve b, r 2 =0.73), Prytherch Marsh 1999 (curve c. ;- 2 =0.82), Towne Beach 1999 (curve d, r 2 =0.91). Radio Beach 1999 (curve e, r 2 = 0.27), Duke Beach 1998 (curve f, r 2 =0.31), and Prytherch 1998 (curve g, r 2 =0.16) (see Fig. 11 for data). gradually decrease regardless of initial density if mortal- ity is density independent. From examinations of tempo- ral abundance patterns from several nursery sites (see Kellison et al., 2003b, for site descriptions), it is evident that observed declines at relatively low initial densities are similar to predicted declines under both density-inde- pendent mortality and a weak type-3 functional response; whereas observed declines at relatively high initial densi- ties are somewhat less gradual than predicted under den- sity-independent mortality, but somewhat more gradual than predicted under the weak type-3 functional response. These results suggest that model predictions made under the assumption of a weak type-3 response may give rea- sonably accurate but conservative predictions of juvenile summer flounder mortality and economic costs associated with stock enhancement for comparison with alternative management methods. As a caveat, although we found no evidence of size-dependent daily mortality over the range of fish sizes examined in this study, it is very likely that such a relationship exists to some extent (Sogard, 1997; Lorenzen, 2000). Incorporating size-dependent mortality into the model would decrease the slopes of the predicted temporal abundance curves but should not change the conclusion that the observed data lie somewhere between values predicted under density-independent mortality and those governed by a weak type-3 functional response, respectively. Additionally, because the portions of the curves used to delineate between temporal abundances expected under density-independent versus varying den- sity-mortality relationships are from early in the growth season (later parts of the curve converge on very low den- sities) and because nearly all fish in these portions of the curves are at sizes well below that at which ontogenetic emigration occurs, the exclusion of emigration from these simulations should not affect the general conclusions reached. These issues could be clarified with further field trials to investigate the dependence of daily mortality rates on fish size. 90 Fishery Bulletin 102(1) E E Prytherch 1999 Radio 1999 003 Prytherch 1998 * r* = 0.1575 02 001 * _. 95 105 115 125 135 145 155 165 B 03 Duke 1999 2 • r = 8162 01 9* * ♦*4U** T M T *' •*♦ D Haystacks 1999 Towne 1999 r" i 9063 ^s^ • "" "Y — » '«W. W. LT» 95 115 135 155 175 195 Duke 1998 1 * r 2 = 03113 0.05 • * **> ♦. • ~~7 • 95 115 135 155 175 195 Julian day Julian day Figure 11 Temporal density patterns from (A) Duke Beach, 1999; (B) Haystacks Marsh, 1999; (C) Prytherch Marsh, 1999; (D) Towne Beach, 1999; (E) Radio Beach, 1999; (F) Duke Beach, 1998; and (G) Prytherch Marsh 1998. Densities are corrected for gear bias (see Kellison, 2000). Model utility and implications Although model results varied considerably under the various density-mortality relationships, the overall pre- dictions that survival would be maximized and economic costs minimized when relatively large fish were released early in the season were unaffected by the density- mortality relationship. These results suggest that manag- ers may use this model to make inferences about optimal release scenarios even if density-mortality relationships are unknown. Additionally, these results have important implications for the cost efficiency of stock enhancement programs. Managers can use the model to determine the release scenarios under which they can 1) maxi- mize the number of survivors, given a financial limit (e.g. given a budget of x dollars, what release scenario or scenarios will produce the greatest number of survi- vors?), and 2) minimize costs, given a goal of number-of- survivors-produced (e.g. given a goal of producing .v survivors, what release scenario or scenarios will be most cost efficient?). In conclusion, the compartmental model used in this study provides an example of a relatively easy-to-develop predictive tool with which to make inferences about the ecological and economic potential of stock enhancement, in relation to alternative management approaches, to rebuild depleted fisheries. Kellison and Eggleston: Modeling release scenarios for Paraltchthys dentatus 91 Acknowledgments We thank Brian Burke (NCSU) for tutelage in the use of Visual Basic. 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Kitigawa. 1994. Effects of release size on survival and growth of Japa- nese flounder Paralichthys olivaceus in coastal waters off Iwate Prefecture, northeastern Japan. Mar. Ecol. Prog. Ser. 105:269-276. 94 Abstract— Sex-specific demography and reproductive biology- of stripey bass [Lutjanus carponotatus l I also known as Spanish flag snapper. FAO ) were exam- ined at the Palm and Lizard island groups, Great Barrier Reef ( GBR). Total mortality rates were similar between the sexes. Males had larger L . at both island groups and Lizard Island group fish had larger overall L_,, Female:male sex ratios were 1.3 and 1.1 at the Palm and Lizard island groups, respectively. The former is statistically different from 1, but is unlikely significantly different in a biological sense. Females matured on average at 2 years of age and 190 mm fork length at both loca- tions. Female gonadal lipid body indices peaked from August through October, preceding peak gonadosomatic indices in October, November, and December that were twice as great as in any other month. However, ovarian stag- ing revealed 50^ or more ovaries were ripe from September through February, suggesting a more protracted spawning season and highlighting the different interpretations that can arise between gonad weight and gonad staging meth- ods. Gonadosomatic index increases slightly with body size and larger fish have a longer average spawning season, which suggests that larger fish produce greater relative reproductive output. Lizard Island group females had ovaries nearly twice as large as Palm Island group females at a given body size. However, it is unclear whether this reflects spatial differences akin to those observed in growth or effects of sampling Lizard Island group fish closer to their date of spawning. These results support an existing 250 mm minimum size limit for L. carponotatus on the GBR, as well as the timing of a proposed October through December spawning closure for the fishery. The results also caution against assessing reef-fish stocks without reference to sex-, size-, and location-specific biologi- cal traits. Sex-specific growth and mortality, spawning season, and female maturation of the stripey bass {Lutjanus carponotatus) on the Great Barrier Reef Jacob P. Kritzer School of Marine Biology & Aquaculture and CRC Reef Research Centre-Effects of Line Fishing Project James Cook University Townsville. Queensland 4811, Australia Present address: Department of Biological Sciences University of Windsor 401 Sunset Avenue Windsor, Ontario N9B 3P4, Canada E-mail address kntzenSuwindsorca Manuscript approved for publication 22 July 2003 by Scientific Editor. Manuscript received 22 July 2003 at NMFS Scientific Publications Office. Fish Bull. 102:94-107 (2004). Lutjanid snappers are among the most prominent species comprising the catch of hook-and-line fisheries on tropical reefs worldwide (Dalzell, 1996). A notable exception is the line fishery on Australia's Great Barrier Reef (GBR). There, the finfish catch, and therefore the majority of fisheries research, is dominated by coral trouts of the genus Plectropomus (Mapstone et al. 1 ). However, the GBR finfish harvest is diverse and the catch of many sec- ondary species has risen steadily since the early 1990s (Mapstone et al. 1 ). Furthermore, over the past decade, the GBR fishery has changed with the advent of the lucrative Asian live reef- fish market. At present, only a handful of the many species harvested on the GBR are exported to the live reef-fish market. However, continued expansion of the trade coupled with the depletion of fish stocks in other source nations (Bentley 2 ) has the potential to intro- duce demand for a wider range of spe- cies. Even in the absence of changes in the species composition of live reef-fish exports, increased demand for second- ary species due to changes in either domestic preferences or availability of primary species has the potential to elevate harvest of currently nontarget species (Kritzer, 2003). Effective multispecies management of the GBR fishery will ultimately re- quire understanding the biology of more than simply the primary target species. For example, spawning closures of the fishery have been proposed for nine-day periods around the new moon in Octo- ber, November, and December on the rationale that this will protect spawn- ing activity of a wide range of harvested species (Queensland Fisheries Manage- ment Authority 3 ). Yet, spawning season information for species beyond the com- mon coral trout {P. leopardus ) ( Ferreira, 1995; Samoilys. 1997 ) is nearly nonexis- tent. The GBR fishery is in a fortunate position with respect to management of many species for which exploitation is still at relatively low levels because baseline biological characteristics can be estimated before stock structure is drastically altered by fishing. These da- ta can then be used in both formulating management strategies and monitoring effects of fishing. 1 Mapstone. B. D.. J. P. MacKinlay, and C. R. Davies. 1996. A description of the com- mercial reef line fishery log book data held by the Queensland Fisheries Management Authority. Report to the Queensland Fisheries Management Authority. 480 p. Primary Industries Building, GPO Box 4(i. Brisbane. Queensland 4001. Australia. 2 Bentley. N. 1999. Fishing for solutions: can the live trade in wild groupers and wrasses from Southeast Asia be managed? TRAFFIC Southeast Asia report. 143 p. Unit 9-3A, 3rd Floor. Jalan SS23/11, Taman SEA. 47400 Petaling Java, Selan- gor, Malaysia. 3 Queensland Fisheries Management Auth- ority. 1999. Queensland coral reef fin fish fishery. Draft management plan and regulatory impact statement, 80 p. Pri- mary Industries Building. GPO Box 46, Brisbane, Queensland 4001, Australia. Kritzer: Sex-specific growth and mortality, spawning season, and female maturation of Lut/anus carponotatus 95 One of the most prominent secondary species in the GBR fishery is the stripey bass (Lutjanus carponotatus) (Spanish flag snapper. FAO). In relation to other large predators on the GBR, L. carponotatus is highly abundant on inshore reefs, common on mid-continental shelf reefs, and absent from outer-shelf reefs (Newman and Williams, 1996; Newman et al., 1997; Mapstone et al. 4 ). Although this affinity for inshore reefs has the potential to make the species more susceptible to recreational fishing, the limited available data do not suggest that it is heavily exploited by the recreational fleet (Higgs, 1993) in relation to the commercial fleet (Mapstone et al. 1 ). Lutjanus carponota- tus has a broad-based diet, consuming a wide variety of smaller reef fishes and invertebrates (Connell, 1998). Its role as a predator coupled with its abundance, particularly on inshore reefs, suggests that the species might have an important ecological function on the GBR in addition to its role as a fishery resource. Davies (1995) and Newman et al. (2000) have collected basic demographic data for L. carponotatus on the north- ern and central GBR, respectively. They both reported a pronounced asymptote in the growth trajectory and that most growth occurred over the first three to five years and little subsequent growth over a lifespan that can reach 15 to 20 years. Newman et al. (2000) also reported a heavily male-biased sample and larger body sizes among males. Unlike age and growth data, no information on reproduc- tion of L. carponotatus has been available despite that fact that existing (minimum size limits) and proposed (spawn- ing closures) fisheries regulations are based largely on reproductive traits (Queensland Fisheries Management Authority 3 ). Specific aims of this study were 1) to estimate sex ra- tios and sex-specific schedules of growth and mortality; 2) to estimate age- and size-specific schedules of female maturation; 3) to identify the spawning season; and 4) to determine whether reproductive output is proportional to body size by examining the ovary weight-body weight relationship and the average spawning duration of large and small fish. All traits were estimated at the Palm Island group on the central GBR. Additionally, sex-specific growth and female maturity schedules were also examined at the Lizard Island group on the northern GBR to develop spa- tial comparisons. Materials and methods Field methods Size, age, and reproductive data were obtained for 465 L. carponotatus collected by spear fishing on fringing reef slopes during monthly fishery independent sampling at 4 Mapstone, B. D., A.M. Ayling, and J. H.Choat. 1998. Habitat, cross shelf and regional patterns in the distributions and abun- dances of some coral reef organisms on the northern Great Bar- rier Reef. Great Barrier Reef Marine Park Authority research publication 48, 71 p. GPO Box 1379, Townsville, Queensland 4810, Australia. Pelorus, Orpheus, and Fantome Islands in the Palm Island group on the central GBR ( Fig. 1 ) from April 1997 through March 1998. No sampling took place in January 1998 because of severe flooding in the area. To develop spatial comparisons, samples of 118 and 18 fish were obtained in October 1997 and April 1999, respectively, by spear fishing at the Lizard Island group approximately 400 km north of the Palm Island group (Fig. 1). Fish were collected from depths of 2 to 15 m by teams of two to four scuba divers. Lutjanus carponotatus most commonly inhabits depths less than 15 m (Newman and Williams, 1996); therefore sam- pling efforts encountered the majority of the population. Fish were targeted as encountered, without preference based on size, in order to collect as representative a sample as possible. Fish <150 mm fork length (FL) were rare in the samples because they were infrequently observed on reef slopes (Kritzer, 2002). Therefore, supplemental spear fishing on reef flats targeting smaller fish was conducted at the Palm Island group (n=24) in April and December 1999 and at the Lizard Island group (n=25) in May 1999 to obtain growth data for size classes against which the primary sampling was biased. Total weight (TW, g) and FL (mm) of each specimen were recorded. Ovaries and testes of small lutjanids on the GBR are characterized by a lipid body running along the length of each lobe, akin to that found in tropical acanthurids (Fishelson et al., 1985). Gonads and these associated lipid bodies were removed and preserved in FAAC (formaldehyde 4%, acetic acid 5%, calcium chloride 1.3%). Sagittal otoliths were removed, cleaned, and stored for later analyses. Gonad processing and ovarian staging The lipid body was removed from each ovary or testis after fixation and the weight of the gonad (GW) and lipid body (LW) were measured to the nearest 0.01 g. A gonadoso- matic index (GSI) and lipidsomatic index (LSI; after Lobel, 1989) were calculated for each sample as the percentage of TW represented by GW and LW, respectively. Features of whole fixed ovaries including color, speckling, and surface texture were noted as potential criteria for macroscopic staging after comparison with samples processed histologi- cally. Sex of the April 1999 Lizard Island group samples was determined macroscopically only, and was therefore used in sex-specific growth analyses but not in analysis of maturity. Fish <150 mm FL had undeveloped gonads and sex of these specimens was not determined or assigned a reproductive stage. A subsample of 131 ovaries spanning the range of gonad sizes and external appearances were prepared for histo- logical examination. Samoilys and Roelofs (2000) found that medial gonad sections were adequate for determina- tion of reproductive status. Therefore, a medial section was removed from one gonad lobe, dehydrated, and embedded in paraffin. Embedded ovarian tissues were sectioned at 5 nm and stained with hematoxylin and eosin. Ovaries were staged on the basis of the most advanced oocyte stage pres- ent (West, 1990). Additional features used in histological staging included the presence of brown bodies and atretic 96 Fishery Bulletin 102(1 120° 130° N 4 Australia Great LG Barrier 15° Reef PG Queensland 35° Lizard Island group (LG) J\ Lizard Island <\ V-— V^" ,25km, Palfrey Q . ' ' Island _ Seabird Islet South Island Palm Island group (PG) Pelorus Island Brisk Island )). where L t = FL at age t\ L^= the mean asymptotic FL; A' = the Brody growth coefficient; and t = the age at which fish have theoretical FL of 0. Growth functions were fitted by nonlinear least-squares regression of FL on age by using samples for which sex was determined. Because VBGF parameter estimates can be sensitive to the range of ages and sizes used (see Ferreira and Russ. 1994, for an empirical example), a common t equivalent to the .v-intercept of the early growth estimates was used in all models (see "Results" section). Although the sex-specific sample sizes at the Lizard Island group were smaller (n=65 for females; n=62 for males), VBGF parameter estimates achieved high precision at sample sizes between 50 and 100 (Kritzer et al., 2001); therefore the Lizard Island group data were included in the analy- sis. Growth parameters were compared by plotting 959c confidence regions of the parameters K and L x (Kimura, 1980) for each sex from each location and assessing the degree of overlap. Sex-specific total mortality rates, Z, were estimated by using the age-based catch curve of Ricker (1975) as the slope of a linear regression of natural log-transformed fre- quency on age class. Everhart and Youngs ( 1981 ) proposed that catch curve analysis should exclude age classes with n<5 and Murphy ( 1997) proposed that age structures used in catch curves should be truncated at the first age class with n<5. Alternatively, Kritzer et al. (2001) proposed that a sample should contain an average of at least ten fish per age class irrespective of age class-specific sample sizes. Therefore catch curves were fitted by two different methods for each sex at the Palm Island group. The first catch curve began at the modal age class and stopped before the first age class with n < 5. The second catch curve likewise began at the modal age class but included all age classes that were thereafter represented in the data set. Sex-specific sample sizes for the Lizard Island group were too small by any of these criteria and this location was excluded. Mor- tality estimates for Palm Island group fish were compared between the fitting methods within each sex as well as between sexes by ANCOVA. Reproductive biology Maturation schedules of female fish were estimated for each island group by fitting a logistic model, P, = l/(l + exp(a-W)), where P- = the proportion of mature fish in age or 20-mm size class i; a adjusts the position of the curve along the abscissa; and r determines its steepness. Age- and size-specific maturity functions were used to estimate the mean age, r 50 , and size, L 50 , at which 50% of females are mature at each island group. Monthly mean LSI and GSI values of mature Palm Island group fish were plotted separately for males and females to determine seasonal patterns of energy storage and the peak spawning period of L. carponotatus. The pro- portion of specimens at each mature female reproductive stage in each month was also plotted to examine ovarian development patterns throughout the year and the degree of spawning activity occurring outside of peak months. To examine whether relative reproductive output in- creases with body size, GW and GSI for stage-IV ovaries collected during peak spawning months were regressed against TW. Residual plots were used to assess deviation from a linear relationship and to identify three outliers, which were removed from the regression analysis. Regres- sion slopes were compared between the two island groups by ANCOVA. Also, mean GSI values and the proportion of Palm Island group females with stage-IV ovaries during spawning months were compared between females <230 mm FL and those >230 mm FL to examine whether the duration of spawning varies between size classes (nota bene: 230 mm FL is approximately the mean size of mature Palm Island group females and splits each month's sample approximately in half). Results Ovarian staging Five female reproductive stages were identified through histological analysis (Table 1) and were based largely on the scheme of Samoilys and Roelofs (2000). Ovarian stages I (immature) and II (resting mature) have similar oocyte stages. These can be distinguished by the presence of brown bodies or atretic oocytes, which are typically prod- ucts of prior spawning (e.g. Ha and Kinzie, 1996; Adams et al., 2000) and are usually absent from stage-I ovaries. However, these structures will not necessarily persist in ovaries that have spawned, and in fact were rare among the samples; therefore identification of immature females was based primarily on structural organization of the ovary. Stage-I ovaries typically have a thin ovarian wall and more compacted oocytes, whereas ovaries that have previously spawned tend to have a thicker ovarian wall and a more disorganized arrangement of oocytes (Table 1). Also, there were distinct size differences between stage-I ovaries and other stages. The mean GW of stage-I ovaries was approximately one-third that of stage-II ovaries, and mean GSI was approximately one-half of that at stage II (Table 1), and the distribution of body sizes offish at stage I had much lower minimum, maximum, and modal size 98 Fishery Bulletin 102(1) Table 1 Description of histological and macroscopic features (after fixation in a formaldehyde, acetic acid, calcium chloride solution I of ovarian developmental stages of Lutjanus carponotatus. Stage definitions and descriptions are largely a modification of the scheme proposed by Samoilys and Roelofs (2000). Mean ovary weight (GW) and gonosomatic index (GSI) for the larger Palm Island group sample are provided. Stage Histological features Macroscopic features Inactive I Immature II Resting Active III Ripening IVa Ripe IVb Running ripe Relatively thin ovarian wall; lamellae well packed; only darkly purple staining previ- tellogenic oocyte stages (oogonia and peri- nucleolar stages) present. Relatively thick ovarian wall; spaces be- tween lamellae common; only previtellogenic oocyte stages and possibly brown bodies and few atretic vitellogenic oocytes present. Most advanced oocytes are at yolk globule or migratory nucleus stage; atretic oocytes or brown bodies possibly present. Most advanced oocytes at yolk vesicle stage; atretic oocytes or brown bodies possibly present. Similar to stage IVa but large, irregularly shaped, clear to lightly coloured hydrated oocytes are present. Always even white color over entire surface; smooth surface texture; lobes quite small (typi- cally <2 cm long) and thin (mean GW=0.33 g; meanGSI=0.24^). Even white to cream or tan color over gonad sur- face; surface may be smooth or somewhat convo- luted; small white stage II ovaries are difficult to distinguish from stage I without histology I mean GW=1.01 g; mean GSI=0.43%). Color sometimes white but more often cream to tan; surface is commonly convoluted; difficult to distinguish from stage II without histology (mean GW=1.18 g; mean GSI=0.53% I. Color tan to brown or mustard with opaque speck- les that become larger and more dense as late stage oocytes become more numerous; convoluted surface sometimes with prominent vasculariza- tion (mean GW=4.04 g; mean GSI=1.399S \. External appearance identical to stage IVa and can only be differentiated histologically (no sam- ples found at Palm Island group). classes compared with the distribution of body sizes offish at stage II (Fig. 2). Stage-Ill (ripening) ovaries contain oocytes at the yolk vesicle vesicle stage, which some authors classify as vitel- logenic (e.g. Samoilys and Roelofs, 2000) and others classify as previtellogenic (e.g. West 1990). Like stage-II ovaries, stage-Ill ovaries can, but do not necessarily, contain brown bodies or atretic oocytes as evidence of probable prior spawning. Although the fish might not have spawned pre- viously, stage III is considered to be a mature stage in the present study because the appearance of yolk vesicles is associated with the initial development of the yolk globule and represents advanced development of the oocyte beyond perinucleolar stages (West, 1990). Therefore, the fish is pre- paring for spawning and will soon be part of the mature population if it is not already. Mean age and size of stage-II (4.4. years and 219 mm FL), stage-Ill (5.0 years and 222 mm FL), and stage-IV (6.5 years and 261 mm FL) females were much more similar to one another than they were to stage-I females (1.9 years and 119 mm FL). Moreover, size-frequency distributions of fish at stages II, III, and IV showed considerable overlap and similarity with one another and were all quite distinct from the size-frequency distribution for stage-I females (Fig. 2). This suggests a division between immature fish and those that are spawn- ing or are nearly ready to do so. The pronounced difference in GW and GSI between stage-I and stage-Ill ovaries and similarity in these metrics between stage-II and stage-Ill fish (Table 1) further support this division. Most immature ovaries and all ripe ovaries could be identified macroscopically. Because certain macroscopic fea- tures were common to multiple ovarian stages, additional histological features was required to separate the largest immature from the smallest resting ovaries and all ripening from resting ovaries among the samples remaining after the initial comparison betw-een histological and macroscopic features. Only one ovary with fully hydrated oocytes, col- lected at the Lizard Island group, was found among the samples prepared for histological analysis; therefore stages IVa and IVb were treated as a single stage. Stage IV suf- ficiently represents final development toward spawning on the broad seasonal time scale adopted in this study but encompasses a wide range of ovarian characteristics and would need to be divided into more detailed stages for finer temporal scale studies of lunar or diel spawning patterns. No samples exhibited features of truly "spent" ovaries. Sex-specific demography Differences were not apparent in early growth of L. car- ponotatus between the island groups (ANCOVA: df=l, 46; F=1.07; P=0.301); therefore the data were pooled to Kntzer: Sex-specific growth and mortality, spawning season, and female maturation of Lut/anus carponotatus 99 80 70 60 50 H 40 30 H 20 10 rzL estimate an early growth rate of 0.76 mm/d, assuming daily period- icity of micro-increments (Fig. 3). This rate of growth represents quite rapid growth, given that fish are adding 100 mm of length in around 4 months, increasing from approxi- mately 20 to 120 mm FL (Fig. 3). The x-intercept of the early growth curve (=-17.98 d) was divided by 365 d/yr to estimate a common t (=-0.049 yr) for all VBGF models. Although size at age for both sexes at both island groups was character- ized by substantial individual vari- ability, different growth trajectories were evident for males and females (Fig. 4, A and B). Estimates (Table 2) and 95% joint confidence regions (Fig. 4C) for the VBGF parameters indicated that the primary differ- ences in these trajectories at each island group lay in L M (which indi- cated that males grow larger than females). In contrast, the common range of K values spanned by the sexes within each island group indicated similar curvature (Table 2, Fig. 4C). However, use of a common t restricts the range of possible fitted lvalues (Kritzer et al., 2001). In addition to the differences between the sexes, the data revealed a general pattern of larger body sizes at the Lizard Island group (Table 2, Fig. 4). Mortality estimates at the Palm Island group were slightly higher when all age classes beyond 1 year were included compared with exclusion of age classes with n < 5 (Fig. 5). These higher mortality estimates contrast with Murphy's (1997) finding that truncation of the age structure results in higher least-squares estimates of Z. The differ- ences between mortality rates estimated with and without age classes with n < 5 were minor for both males (ANCOVA: df=l, 20; F=0.009; P=0.92) and females (ANCOVA: df=l, 23; F=1.35; P=0.26). Therefore, for comparisons between the sexes, the estimates that included all age classes greater than 1 yr were used. In contrast to the sex- specific growth differences, Z estimates of 0.26/yr and 0.29/yr (Fig. 5) corresponding to annual survivorship of 77% and 75% for females and males, respectively, at the Palm Island group were similar between the sexes (ANCO- VA: df=l, 27; F=0.505; P=0.483). Murphy's (1997) results also suggested that least-squares mortality estimates are likely to be around 30% less than the true mortality rate when n = 200 and the true Z = 0.2/yr. Correcting these mor- tality estimates based upon this potential bias results in Z estimates up to 0.37/yr and 0.41/yr for females and males, respectively, with corresponding annual survivorship of 69% and 66%-. However, the catch curve estimates (Fig. 5) corresponded well with estimates based upon Hoenig's (1983) empirically derived relationship between Z and n In I I □ Stage I Stage II □ Stage III El Stage IV I Bfl 51 1 I i ' ' i ii, mi i m co ,, 3"ir>cor--ooa>o-<-OT- t-t-t-t-^t-t-CMJ(N(MCM and Lizard iBl island groups and estimated 959! joint confidence regions of the parameters A" and l. (C), Parameter estimates are presented in Table 2. Spawning season Mature female LSI values were highest in August through October with a maximum in September ( Fig. 7A). The peak in GSI lagged that of LSI by two months with the high- est values occurring from October through December and with a maximum in November (Fig. 7A>. The absence of a January sample unfortunately leaves some ambiguity as to whether GSI, and therefore presumably spawning activity, would still be high at this time or if it would have begun to decline. Male GSI values also exhibited a November maximum (Fig. 7B). Male LSI values, however, did not show any clear trend of increase and decline throughout the year and peaks in April, May, and August that did not correlate with future GSI values as clearly as seen in the female data (Fig. 7). Unlike LSI values for females, monthly mean male LSI values were always greater than the corresponding GSI values. The seasonal pattern of L. carponotatus spawning activity suggested by monthly trends in the proportions of mature ovarian stages can be interpreted as differ- ent from that suggested by GSI values. The lowest GSI values in the October-December peak period were close to twice as great as the next highest values in Septem- ber and February < Fig. 7A). However, the percentage of stage-IV ovaries in the September sample was greater than 50%. which is well over half the percentage of the October sample; whereas the February sample comprised approximately the same percentage of stage-rV ovaries as October (Fig. 8). Also, more than 50% of the March sample was stage-rV ovaries (Fig. 8). whereas its GSI value was close to that of the months with relatively few ripe ovaries (Fig. 7A). Furthermore, September and March had the highest proportions of ripening (stage-Ill I females and thus far fewer resting mature (stage-II) females than the April to August period of limited spawning activity I Fig. 8). Therefore, regardless of whether September, February, and March are defined as nonspawning months or months of limited spawning activity based upon GSI, analysis of ovarian stage frequencies suggests these to be periods of greater spawning activity than might be predicted with GSI. Clearly, the presence of advanced oocytes is a much better indication of imminent spawning than any measure of gonad size; therefore the reproductive stage- frequency data undoubtedly provide the more accurate picture of L. carponotatus spawning patterns. Of 59 ovaries staged from the October 1997 Lizard Island group sample, eight were at stage I, two were at stage II, and 49 (96% of mature females in the sample) were at stage PV. This finding suggests that the island groups share at least October as a common period of ac- tive spawning. Reproductive differences between locations and among size classes The variation in GW among females of like body sizes during peak spawning months increased to some degree with increasing TW, but there was a generally homoge- neous spread of data around the predicted regression Kntzer: Sex-specific growth and mortality, spawning season, and female maturation of Lut/anus carponotatus 101 male ages 2+: y = -0.289x + 4.319 r 2 = 0.896 male ages with n 0.844 female ages 2+: y = - 0.261 x + 4.557 r 2 = 0.872 4: female ages with n > 4: 0.272X + 4.282 y = - 0.203x + 4.289 0.879 6 8 10 12 Age class (years) 18 Figure 5 Age-based catch curves for female higher elevation lines i and male (♦. lower elevation lines) Lutjanus carponotatus at the Palm Island group fitted to all age classes >1 (solid lines I and age classes >1 with n >4 (dashed lines I. Open symbols represent age class 1, which was not used in the analysis. Table 2 Sex-specific von Bertalanffy growth parameters for Lu tja ms carpom tatus at the Palm and Lizard Island groups , Great Barrier Reef, n is sample size; L F is the mean fork length ( mm ) K is the Brody growth :oefficient per yr) L. is the mean asymptotic fork length (mm); a common t -, of -0.049 yr was used n all growth models. Standarc errors are provided below parameter estimates. n L F A" L. r 2 Palm Island group females 263 224.2 12.11) 0.77 (0.032) 246.3 (2.25) 0.515 males 202 224.7 (2.78) 0.69 (0.028) 264.3 (3.26) 0.629 sex ratio 1.3:1 Lizard Island group females 65 239.9 (4.76) 0.56 (0.043) 263.5 (4.24) 0.618 males 62 256.4 (4.77) 0.51 (0.032) 284.8 (4.03) 0.714 sex ratio 1.1:1 lines across body sizes (Fig. 9A). This suggests that on average GW at stage IV during peak spawning months is a linear function of TW. Lizard Island group fish generally had larger ovaries at a given size than did Palm Island group fish (Fig. 9A), a difference supported by ANCOVA (df=l, 125; F=34.7; P<0.001). In fact, regression slopes of 0.25 and 0.52 suggest relative ovary weights at the Lizard Island group were approximately twice as large as those at the Palm Island group. There were no differences in the GW-TW relationship among October, November, and December at the Palm Island group, and therefore the dif- ferences in this relationship between the island groups was consistent whether only the Palm Island group October data were used or whether the October through December data were used. Although GW is a linear function of TW, the nonzero regression constants (Fig. 9A) mean that GW is not a con- stant proportion of TW. Consequently, GSI increases with increasing TW ( Fig. 9B ). The relationship between TW and GSI is not strong, with regression slopes close to zero and low r 2 values at both island groups (Fig. 9B). Despite this, the relationship is statistically strong at both the Palm ( ANOVA: df=l,82; F=12.70; P=0.006) and Lizard (ANOVA: df= 1,42; F=22.95; P<0.0001) Island groups. Also, there is 102 Fishery Bulletin 102(1) some suggestion that, like the GW-TW relationship, the GSI-TW relationship varies between the island groups, although to a much lesser extent (ANCOVA: df= 1,125; F=7.44;P=0.007). o o A 40 34 22 19 12 16 18 12 4 5 2 1 1 4 1 1.0 - 8 33 6 29 5741 2 1 56 /o E'"B 0.8 - 5/ .' 0.6 - a ■* 0.4 - 15 /"-' 0.2 - 3/ 00 - There is some indication that larger fish spawn over a longer period at the Palm Island group. During the September-February spawning season, mean GSI values were always higher for mature Palm Island group females >230 mm FL compared with mature fe- males <230 mm FL at the same location (Fig. 10). This pattern is likely due in part to the higher relative gonad weights of larger fish (Fig. 9B) but also seems to be driven by greater proportions of stage-IV ovaries among larger mature females in September, October, and February com- pared with fish <230 mm FL (Fig. 10). During these months, 13%, 13% and 25% more large fish were at stage IV, respec- tively, than were small fish. 1 2 3 4 5 6 7 B 9 10 11 12 13 14 15 16 17 M Age class (years) 53 44 25 11 3 2 1.0 0.8 0.6 0.4 0.2 0.0 10 50 90 130 170 210 250 290 330 Size class midpoint (mm fork length) Figure 6 Proportion of mature female Lutjanus carponotatus and estimated age-spe- cific (A) and size-specific (B) logistic maturation schedules at the Palm solid lines) and Lizard (□, broken lines) island groups. Sample sizes for the Palm (top value) and Lizard (lower value) Island groups are presented above the data for each age or size class. Parameters of the maturity functions are provided in Table 3. Discussion Demography and reproduction of L. carponotatus Growth of L. carponotatus is rapid for the first two years of life, slows over the next two years, and nearly ceases by age 4. The slowing and cessation of growth coincide with the ages at 50% and 100% maturity, respectively, and support the argument of Day and Taylor (1997) that maturation represents a pivotal physiological trans- formation and consequently a fundamen- tal shift in the growth trajectory. Further supporting the idea that reproductive development occurs at the expense of somatic growth is the apparently longer average spawning season among larger fish that have ceased most somatic growth. The limited growth over much of the lifes- Table 3 Parameters of age- and size- specific logistic maturation schedules anc estimated ages and fork 1 engths at 50', maturity of female Lu tja n 11 s ca rpon otatus at the Palm and Lizar d Island gi oups, Great Barrier Reef. a adjusts th e posit on of the logi stic function along the abscissa; r determ ines the steepness of the logistic function. f i; n is the age at 50% maturity; L r is the fork length at 509S maturity. Standard errors are provided below parameter estimates. a r r 2 *S0 OI " £ 50 Age-specific Palm Island group 6.40 (1.42) 3.42 (0.12) 0.985 1.9 years Lizard Island group 4.16 (0.48) 1.73 (0.19) 0.990 2.4 years Size-specific Palm Island group 14.72 (1.49) 0.081 (0.008) 0.994 182 mm Lizard Island group 11.61 (3.84) 0.061 (0.020) 0.908 189 mm Kritzer: Sex-specific growth and mortality, spawning season, and female maturation of Lut/anus carponotatus 103 pan of L. carponotatus can explain the apparently constant mortality rate over many age classes (evidenced by high catch curve r 2 values) given that mortality is often largely a function of body size (Roff, 1992). The development and regression of visceral fat stores preceding increases in ovary weight is a pattern that has been observed in other reef fishes, in- cluding tropical surgeonfishes (Acan- thuridae: Fishelson et al., 1985) and groupers (Serranidae: Ferreira, 1995) and temperate rockfishes (Scorpaeni- dae: Guillemot et al., 1985). These pat- terns suggest that the stored lipid is fuelling the energetic costs of spawning. The lack of a similar pattern for males supports the idea that energetic costs associated with production of sperm are low in relation to eggs (Wootton, 1985) thus enabling male L. carponotatus to attain larger sizes, as also reported by Newman et al. (2000). Alternatively, males might spawn more frequently throughout the year than females and the lack of seasonal patterns in lipid storage among males might reflect a more regular energetic demand that precludes energy storage. In any case, these sex-specific growth patterns, coupled with similar mortality rates between the sexes and sex ratios that are at unity or that are at most only slightly female-biased (see below), sug- gest that females are limiting reproduction of this species. Therefore stock dynamics should be modeled in terms of female biology (Hilborn and Walters, 1992). The apparently female-biased sex ratio at the Palm Island group starkly contrasts with the heavily male-biased sex ratio reported for mid-shelf reefs of the central GBR by Newman et al. (2000). However, neither a male- nor fe- male-biased sex ratio would be expected from a nonhermaphrodite that is not known to possess a complex mating system such as defense of females or territories. It is possible that the spawning sex ratio (i.e. excluding juveniles) is closer to unity if males mature earlier than females, but this ratio is not possible to assess because male maturation has not yet been examined for this species. The difference between the sex ratio reported in this study and that by Newman et al. (2000) might be due to variation in mating systems across a cross- shelf density gradient (Newman and Williams, 1996). Alternatively, the sampling by traps and line fishing conducted by Newman et al. (2000) could be more heavily biased toward males than the sampling by spear fishing used in the present study because of larger % 25 to 8 2.0 1.5 1.0 0.5 0.0 Figure 7 Monthly mean gonadosomatic index IGSI ±SE; ■) and lipidsomatic index (LSI ±SE; □) values for mature female (A) and all male (Bl Lutjanus carponotatus at the Palm Island group. B -1.0 P CO - - 0.8 - 0.6 v -H" - 0.4 - 0.2 April June Aug Oct i i Dec Feb Month (1997-98) 100% 80% I" 60% - CD f 40°= 20% 0% li i i I D Stage II Stage III D Stage IV April June Aug Oct Dec Feb Month (1997-98) Figure 8 Monthly frequencies of ovarian stages of mature Lutjanus carpono- tatus at the Palm Island group. Stage descriptions are provided in Table 1. size, wider gape, or more aggressive behavior toward bait among males (Cappo and Brown, 1996). Furthermore, it is likely that a female-biased sex ratio as observed at the 104 Fishery Bulletin 102(1) 30 -i Lizard group: 25 - y = 0.052x -6.33 Ol £ 20 J 1 15 - .-'•" " r 2 = 0.711 5 10 - o 5 - ° -■" . °^^ 200 400 600 800 1000 6.0 - (J 5.0 - B Lizard group: _»--' y = 0.0071X + 0.64 « 4.0- ° a S ° a !-'' f2 = 0353 c g 3.0 - to o 2.0 - c/i o 13 1.0- c <§ 0.0- □ D* u m a £ . ' ° a ° ' ° •*!..■■'' - ^—~—~' n ^4 " D □ m ' • °~ " — m • ' <£J-z i ~*~^° ' Palm group: _*^*~""^° ' . y = 0.0029x + 1.02 ."^1 "■ " r 2 = 0.134 200 400 600 800 1000 Whole body weight (g) Figure 9 Fixed ovary weight (A) and gonadosomatic index iBi at fresh whole body weight for mature female Lutjanus carponotatus at ovarian stage IV (see Table 1) collected during peak spawning months (Oct-Dec) at the Palm solid lines) and Lizard (□, dashed lines) island groups. Sep Oct Nov Dec Jan Month (1997-98) Feb Mar Figure 10 Mean gonadosomatic index (GSI ±SE) for mature female Lutjanus carponotatus at the Palm Island group during the September through March spawning season for small (<230 mm fork length; ■> and large (<230 mm fork length; □) size classes. The percentage of fish at stage IV (see Table 1) is indicated above each data point. Palm Island group is not a prevalent feature of L. carponotatus populations. Rather, the strong statistical suggestion of a sex ratio quite different from unity might be due to the fact that sex ratios often show temporal variability (e.g. Stergiou et al., 1996) coupled with the propensity to achieve statistically significant differences when using large sample sizes (Johnson, 1999). Maturation schedules and sex-specific growth differences were consistent between the island groups, but overall growth pat- terns differed, with Lizard Island group fish reaching larger asymptotic body sizes. Given the vast distance between the island groups, these differences might be due to inherent genetic differences between the populations. Or, effects of temperature (the Palm Island group sits at a higher latitude), turbidity, freshwater run-off (the Palm Island group sits closer to a river mouth and has more developed mangrove systems), or other environmental factors could be driving the differences. Of course, these possibilities are not mutually exclusive. The larger ovaries observed among Liz- ard Island females might be due to further spatial differences or might be an effect of timing of sampling. The temporal resolution of sampling aimed to identify the extent of the spawning season but was too coarse to account for intramonth differences in ovar- ian development. Large changes in ovary size might occur within stage IV, and the final progression to immediate prespawning stages can be rapid (e.g. Davis and West, 1993). The Lizard Island group sample was collected from 17 to 23 October 1998, whereas the corresponding Palm Island group sample was collected from 11 to 12 October 1998. The October 1998 new moon was on the 20 th , and P. leopardus, the only GBR species for which lunar spawning patterns have been reported, spawns primarily around the new moon (Samoilys, 1997). If L. carponotatus spawning is also centered around the new moon, the spatial differences in ovary weight at body weight might be due to more advanced develop- ment toward full hydration within the Lizard Island group sample. In fact, the higher proportion of stage-FV ovaries within the October Lizard Island group sample (96%) compared with the October Palm Island group sample (78'i ), coupled with the higher relative ovary weights at the Lizard Island group in October, can be taken as preliminary evidence that L. carponotatus spawns at the new moon. Comparison with other reef fishes The growth differences between male and female L. carponotatus contrast with a general trend of larger body sizes among female lutjanids observed in Atlan- Kritzer: Sex-specific growth and mortality, spawning season, and female maturation of Lut/anus carponotatus 105 tic, Caribbean, and Hawaiian species (Grimes, 1987). However, the pattern observed in the present study seems common in the Indo-Pacific where males frequently ( Davis and West, 1992; McPherson and Squire, 1992; Newman et al., 1996, 2000). but not universally (Hilomen, 1997), are the larger sex. As noted above, these differences are consis- tent with predictions based on energetic costs of producing sperm and eggs. Lutjanus carponotatus spawning patterns identified by using both GSI and ovarian stage frequencies show pro- nounced seasonal differences: there are at least five months of very limited or no spawning activity from April through August. This finding supports Grimes's ( 1987) observation that continental lutjanid populations tend to have more restricted spawning seasons than populations associated with oceanic islands, which spawn more or less continu- ously throughout the year. Although seasonal patterns ex- ist, the prominence of ripe gonads over seven months from September through March suggests an extended spawning season and supports the general observation that tropical reef fishes spawn over longer periods within the year than do cooler water species (Lowe-McConnell, 1979). However, a study with finer temporal resolution is needed to verify that spawning actually occurs in months with a high pro- portion of stage-IV ovaries. Female L. carponotatus mature on average at approxi- mately 75% of their mean asymptotic size, 54% of their maximum observed size, and 119c of their maximum longevity. The relative size at maturity contrasts with Grimes's ( 1987) observations that shallow-water continen- tal lutjanid populations like those of L. carponotatus on the GBR typically mature at smaller relative sizes (=42% maxi- mum size) compared to deep-water populations associated with oceanic islands (=50% maximum size). Two sympatric shallow -water species, L. russelli (Sheaves, 1995) and L. fulviflamma (Hilomen, 1997), likewise contrast with the general familial trend and mature at approximately 50% and 75% of their maximum size, respectively. Hence, a general pattern of relative size at maturity might exist among shallow-water lutjanids in the GBR region that is different from those regions covered by Grimes's ( 1987 ) review. Lutjanids on the GBR are generally lightly fished (Mapstone et al. 1 ); therefore the geographic difference in sizes at maturity might be due to fishing pressure selecting for smaller sizes at maturity in other regions. The relative age at maturity of L. carponotatus cannot be as readily placed in a broader familial context given that ages at maturity were not widely estimated for lutjanids at the time of Grimes's (1987) review. However, an array of published studies suggests that many tropical and sub- tropical demersal fishes share the absolute, but not relative, ages of L. carponotatus at 50% and 100% maturity at 2 and 4 years, respectively. These include other small gonochores on the GBR (Sheaves, 1995; Hart and Russ, 1996; Hilomen, 1997), as well as a range of gonochores in other regions (Grimes and Huntsman, 1980; Davis and West, 199.3; Ross et al., 1995 ) and hermaphrodites on the GBR and elsewhere (Ferreira, 1993, 1995; Bullock and Murphy, 1994). The ubiquity of this maturity schedule, despite a wide array of maximum body sizes (160-1200 mm) and longevities (6-56 years) among these species, perhaps suggests a common physiological threshold toward which many species gravi- tate in order to maximize lifetime reproductive success. More comprehensive analysis of life history trade-offs (e.g. Roff, 1992) is needed to test this hypothesis. Fisheries management Harvest of L. carponotatus is currently restricted to fish greater than 250 mm total length ( approximately 233 mm FL) with the aim of allowing 50% offish to spawn at least once, and this regulation is proposed to remain after revi- sion by the GBR fishery management plan (Queensland Fisheries Management Authority 3 ). The estimated size at 50% maturity of 190 mm FL suggests that the regula- tion is meeting its objective. However, the objective itself might not adequately protect the reproductive potential of L. carponotatus and similar species if individuals require multiple spawning years to ensure sufficient replenish- ment of the stock. The extensive longevities of many reef fishes have been hypothesized to be a mechanism for coping with low and irregular recruitment rates through a process dubbed the "storage effect" (Warner and Chesson, 1985). The rationale behind the storage effect hypothesis is that fish must reproduce during many breeding seasons in order to endure poor recruitment years and realize high repro- ductive success during the unpredictable and intermittent good recruitment years. If this process is important for population dynamics of L. carponotatus and other species, management will need to protect an intact natural popula- tion structure in some areas within the fishery. Protecting older age classes cannot be achieved by using maximum size limits for species like L. carponotatus that have a pro- nounced asymptote in the growth trajectory because body sizes are similar over a broad range of age classes and size is therefore poorly correlated with age. Protecting natural age structure could be accomplished through a system of strategically designed marine protected areas that allow some populations to experience natural survival free of fishing mortality. Proposed closures of the GBR line fishery during nine- day periods around the new moon in October, November, and December are aimed at protecting spawning activity and particularly spawning aggregations of P. leopardus and other harvested species (Queensland Fisheries Man- agement Authority 3 ). Lutjanus carponotatus shares a peak spawning period during these months with P. leopardus (Ferreira, 1995; Samoilys 1997) and several other sym- patric exploited species (McPherson et al., 1992; Sheaves, 1995; Hilomen, 1997; Brown et al. 5 ). In addition, the larger ovaries of the Lizard Island group fish, which were collected closer to the new moon, may indicate that, like P. leopardus (Samoilys, 1997), L. carponotatus spawns at 5 Brown, I. W., P. J. Doherty, B. Ferreira, C. Keenan, G. McPher- son, G. Russ, M. Samoilys, and W. Sumpton. 1994. Growth, reproduction and recruitment of Great Barrier Reef food fish stocks. Final report to the Fisheries Research and Development Corporation, FRDC Project 90/18, Queensland Department of Primary Industries, 154 p. Southern Fisheries Centre, GPO Box 76. Deception Bay, Queensland 4508, Australia. 106 Fishery Bulletin 102(1 the new moon. Therefore, the timing of the proposed spawn- ing closures seems appropriate. However, it is not known whether L. carponotatus aggregate to spawn; therefore the goal of protecting spawning aggregations might not be rel- evant for this species. In fact, the prevalence and ecological importance of spawning aggregations for any species on the GBR is largely unknown; therefore the efficacy of the proposed closures is difficult to predict. Beyond the implications for management regulations, these data have implications for modeling L. carponotatus stock dynamics. In particular, the results suggest that reproductive output by a unit of L. carponotatus biomass cannot be predicted on the basis of that biomass alone. Relative ovary weight increases slightly with increasing body size and there is evidence that larger fish spawn more frequently. The greatest difference in the proportion of ripe ovaries between size classes occurred in February 1998 af- ter severe flooding in January. It is possible that the lower proportion of ripe ovaries among small fish in February was due to stresses caused by changes in salinity or increased run-off and is not a regular trait. However, increased resil- ience to environmental stresses that allows more frequent spawning would also increase the relative reproductive success of large fish. Therefore, a population comprising fewer larger fish is likely to show greater annual egg pro- duction than a population with equivalent biomass that comprises more numerous but smaller fish. Additionally, the sex-specific patterns reported in this study further suggest gross biomass might be an inadequate index of replenishment potential and that female biomass needs to be considered. Therefore, stock structure, in terms of sex ratio and the frequency of size classes, and not simply overall biomass needs to be considered when predicting reproductive potential. Acknowledgments I thank the numerous assistants who participated in fieldwork, as well as Sam Adams and Sue Reilly for assis- tance with histological examinations. The manuscript was greatly improved by comments from Howard Choat, Carl Walters, Tony Fowler, Campbell Davies, Sam Adams, Bruce Mapstone, an anonymous thesis examiner, and two anony- mous reviewers. This work was conducted while the author was supported by an international postgraduate research scholarship from the Commonwealth of Australia and a postgraduate stipend from the CRC Reef Research Centre. Final preparation of the manuscript took place while the author was supported by a postdoctoral fellowship funded jointly by the University of Windsor and the Canadian National Science and Engineering Research Council (col- laborative research opportunity grant no. 227965-00) to Peter Sale and others). Literature cited Adams, S., B. D. Mapstone, G. R. Russ, and C. R. Davies. 2000. 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Croom Helm, London. 108 Abstract— The increase in harbor seal (Phoca vitulina richardsi) abundance, concurrent with the decrease in sal- monid [Oncorhynehus spp.) and other fish stocks, raises concerns about the potential negative impact of seals on fish populations. Although harbor seals are found in rivers and estuaries, their presence is not necessarily indicative of exclusive or predominant feeding in these systems. We examined the diet of harbor seals in the Umpqua River, Oregon, during 1997 and 1998 to indi- rectly assess whether or not they were feeding in the river. Fish otoliths and other skeletal structures were recov- ered from 651 scats and used to identify seal prey. The use of all diagnostic prey structures, rather than just otoliths, increased our estimates of the number of taxa, the minimum number of indi- viduals and percent frequency of occur- rence C^FO) of prey consumed. The *7 f FO indicated that the most common prey were pleuronectids, Pacific hake (Merluccius produetus), Pacific stag- horn sculpin [Leptocottus armatus), osmerids. and shiner surfperch (Cyma- togaster aggregata ). The majority ( 76%) of prey were fish that inhabit marine waters exclusively and fish found in marine and estuarine areas (e.g. anad- romous spp. ) which would indicate that seals forage predominantly at sea and use the estuary for resting and opportu- nistic feeding. Salmonid remains were encountered in 39 samples (6%); two samples contained identifiable otoliths, which were determined to be from Chi- nook salmon (O. tshawytscha). Because of the complex salmonid composition in the Umpqua River, we used molecular genetic techniques on salmonid bones retrieved from scat to discern species that were rare from those that were abundant. Of the 37 scats with salmo- nid bones but no otoliths, bones were identified genetically as chinook or coho (O. kisutch) salmon, or steelhead trout (O. mykiss) in 90'? of the samples. Examination of the foraging habits of Pacific harbor seal (Phoca vitulina richardsi) to describe their use of the Umpqua River, Oregon, and their predation on salmonids Anthony J. Orr Adria S. Banks Steve Mellman Harriet R. Huber Robert L. DeLong National Marine Mammal Laboratory Alaska Fisheries Science Center, NMFS, NOAA 7600 Sand Point Way NE Seattle, Washington 98115 E-mail address (for A. J. Orr, contact author) tony.orr gnoaa.gov Robin F. Brown Oregon Department of Fish and Wildlife 2040 S E. Marine Science Drive Newport, Oregon 97365 Manuscript approved for publication 9 October 2003 by Scientific Editor. Manuscript received 20 October 2003 at NMFS Scientific Publications Office. Fish. Bull. 102:108-117 (2004). The Pacific harbor seal (Phoca vitulina richardsi) is found along the west coast of North America from the Aleutian Islands, Alaska, to the San Roque Islands. Baja California (King, 1983; Reeves et al., 1992). Before the pas- sage of the Marine Mammal Protection Act (MMPA) of 1972, harbor seals in Oregon were kept at relatively low numbers (fewer than 500 animals in 1968) because of bounties offered by the state and harassment from commercial and sport fishermen (Pearson and Verts, 1970). Since passage of protective leg- islation, harbor seals in Oregon have increased an average of 6^ to 7% annu- ally between 1978 and 1998, although, in recent years, numbers appear to be leveling at about 8000 individuals (Brown and Kohlmann. 1998). The rapid increase in harbor seal numbers has revived fishery-manag- ers' interest in seal diet because of the potential for increased consumption of commercial fish species. In addition, there has been a heightened concern about greater harbor seal abundance in rivers and estuaries during migra- tions of depressed salmonid popula- tions because of the potential negative impact on the recovery of these fishes (NMFS, 1997). Because of the tenuous status of many salmonid (Oncorhyn- ehus spp. I species along the west coast, the National Marine Fisheries Service ( NMFS ) recommended that the United States Congress modify the MMPA to allow lethal removal of seals from river mouths where they may prey on de- pressed salmonid populations (NMFS. 1997 ). Predation of salmonids by harbor seals in Oregon has been documented (Brown, 1980; Harvey. 1987; Brown et al., 1995; Riemer and Brown, 1997; Beach et al. 1 ). The proportion of salmo- nids in the diet of harbor seals varied from 1% to 30'r depending on area, season, and sampling method (NMFS, 1997). Pinniped prey consumption can be determined from direct observations in some systems, if prey is consumed at 1 Beach, R.. A. Geiger. S. Jefferies. S. Treacy, and B. Troutman. 1985. Marine mam- mals and their interactions with fisheries of the Columbia River and adjacent waters, 1980-1982. NWAFC (Northwest Alaska Fisheries Science Center) processed rep. NWAFC 85-04, 316 p. NWAFC, National Marine Fisheries Service, Seattle, WA, 98115. Orr et al.: Foraging habits of Phoca vitulma richardsi in the Umpqua River, Oregon 109 Pacific Ocean A N the surface (Bigg et al., 1990); however, consumption is typically determined by examining scat (fecal) samples. In the past, species-specific sagittal otoliths found in scats were used exclusively to determine the identification of prey taxa. However, because otoliths can be partially or completely digested, or are not present in scats (because the head of the prey was not consumed ), they are not always an adequate representation of di- et. Recently, investigators have begun to use additional structures (e.g. cranial el- ements, vertebrae) recovered from scats to identify prey (e.g. Olesiuk et al., 1990; Cottrell et al., 1996; Riemer and Brown, 1997; Browne et al., 2002; Lance et al. 2 ). These structures usually are more com- mon than otoliths and frequently can be identified to species; however, bones of some species can be identified to family only (e.g. salmonids). Consequently, the National Marine Mammal Laboratory (NMML) collaborated with the Conser- vation Biology Molecular Genetics Laboratory (CBMGL; Northwest Fish- eries Science Center, Seattle, WA) to develop molecular genetic identification of salmonid species (Purcell et al., 2004). Because of the complex salmonid species composition in the Umpqua River, genetic identification was vital to distinguish species that were rare from those that were abundant. The original impetus of this study was to assess the impact of harbor seal predation on the recovery of the Umpqua River sea-run cutthroat trout (O. clarkii) that were listed as endangered under the Endangered Species Act (ESA) during 1996 (Johnson et al., 1999). Umpqua River cutthroat trout were removed from the ESA in 2000 because they were identified to be part of the larger Oregon Coast evolutionary significant unit (U.S. Fish and Wildlife Service, 2000). The present study was continued despite the "delisting" of cutthroat trout because the Umpqua is inhabited year-round by harbor seals that haul out sev- eral kilometers upriver and is, thus, ideal for determining whether the presence of a pinniped species within a sys- tem is indicative of substantial feeding on fish species of concern within that environment. In addition, the Umpqua River contains several other salmonid species whose status is precarious (NMFS, 1997). Therefore, the development of genetic identification techniques was considered valuable for this system, as well as for future foraging studies in which species-specific identification may be desirable but impossible by way of conventional identification methods. Oregon L mpquu River hauiouts 2 Lance, M., A. Orr, S. Riemer, M. Weise, and J. Laake. 2001. Pinniped food habits and prev identification techniques pro- tocol. AFSC Proc. Rep. 2001-04, 36 p. AFSC, NMFS, NOAA. 7600 Sand Point Way NE, Seattle. WA 98115. Figure 1 Map of the lower section of the Umpqua River, Oregon, where scat samples were collected at two haulout sites during 1997 and 1998. The objectives of this study were 1 ) to determine by an examination of diet if harbor seals that haul out in the Umpqua River feed primarily in the river or elsewhere, and 2) to apply genetic techniques to identify salmonid prey species. Materials and methods Study area The Umpqua River, located in southern Oregon ( Fig. 1 ). is a natal river for sea-run cutthroat trout, as well as chinook (O. tshawytscha), coho (O. kisutch) salmon, and steelhead trout (O. mykiss). The Umpqua estuary is also inhabited year-round by approximately 600-1000 harbor seals and has been designated as an area where pinnipeds and sal- monids significantly co-occur (NMFS, 1997). Scat samples for this study were collected from two hauiouts located within 4.8 km of the river's mouth and within 1.6 km of each other (Fig. 1). Scat collection and analysis Samples were collected during two seasons: "spring" (March through June) and "fall" (August to December). "Spring" corresponded to the migration of anadromous cutthroat trout adults and some juveniles to the ocean and "fall" coincided approximately with the freshwater return of spawning anadromous adults. The migratory and spawn- 110 Fishery Bulletin 102(1) Table 1 Collection dates of harbor seal scats and numbers of scats wi th identifiable prey remains, without identifiable remains and without remains from the Umpqua River, Oregon, during 1997 and 1998 Fall and spring periods correspond to timing of cutthi oat trout runs on the Umpqua River. Collection dates With identifiable remains Without dentifiable remains Without remains Total Fall, 1997 16-23 Sep 26 1 2 29 27 Sep-6 Oct 5 3 8 12-24 Oct 31 7 38 31 Oct-lONov 21 6 27 12-25 Nov 36 10 46 Total 119 1 28 148 Spring 1998 24-25 Mar 27 5 2 34 13-15 Apr 59 5 7 71 26-27 Apr 45 4 4 53 13-14 May 41 4 45 27-28 May 12 1 13 11-12 Jun 35 2 1 38 Total 219 16 19 254 Fall 1998 5-6 Aug 142 1 1 144 19-20 Aug 111 1 3 115 6-9 Sep 28 3 3 34 19-21 Sep 13 13 7-8 Oct 19 1 20 Total 313 5 8 326 ing periods of chinook and coho salmon, and steelhead trout also occur during these times. During fall 1997, all harbor seal scats present at the haulouts were collected every other day during the day- time low tide, weather permitting (Table 1). In 1998. bi- weekly attempts were made to pick a minimum of 50 scats during low tides at the haulout sites (Table 1). Scats were collected, placed in individual plastic bags, and frozen for later processing. At the laboratory samples were thawed and rinsed in nested sieves (1.0 mm, 0.71 mm, and 0.5 mm in 1997; 1.4 mm, 1.0 mm, and 0.5 mm in 1998). Fish struc- tures were dried and stored in glass vials and cephalopod remains were stored in vials with 70"* isopropyl or ethyl alcohol. Prey were identified to the lowest possible taxon by using sagittal otoliths, skeletal, and cartilaginous remains from fish and beaks and statoliths from cephalopods. Other in- vertebrate remains were discarded from analysis because of the uncertainty of identifying them as primary or sec- ondary prey. Unknown prey were categorized as "unidenti- fied" and "unidentifiable" (Browne et al., 2002). Items that were categorized as "unidentifiable" were excluded from analyses because they could not be distinguished from prey already identified in the sample. Otoliths, beaks, and diagnostic bones were identified by using an extensive ref- erence collection at the NMML and voucher samples veri- fied by Pacific Identifications (Victoria, British Columbia). After identification, otoliths were separated by side (left, right, or unknown ) and enumerated to determine minimum number of specific prey. Unique diagnostic structures (e.g. quadrates, angulars, basioccipitals, vomers) were used for identification and enumeration offish. Non-unique skeletal structures such as gillrakers and teeth were used to iden- tify but not enumerate taxa (i.e. their presence indicated only a single individual) unless the structures were from different size classes. Vertebrae were treated like other non-unique structures; however, for salmon, if the number of vertebrae reflected more than one individual, then they were used for enumeration. Cephalopod beaks were sepa- rated by side (upper, lower, or unknown) and enumerated to determine number of prey. To discern where harbor seals were feeding, identified prey were categorized as those exclusively found in rivers or estuaries (e.g. gobiids, cyprinids), those found exclu- sively in marine waters (e.g. gadids, mvxinids), and those that could potentially be found in either environment (e.g. anadromous species, osmerids, petromyzontids) by using Eschmeyer et al. (1983). A seal was considered to feed in the river-estuary system if all the prey taxa identified in the scat were definitely or could potentially be found in the system. For example, a sample containing remains of pea- mouth chub iMylocheilus caurinus), threespine stickleback ( Gasterosteus aculeatus ), river lamprey iLampetra ayresii ), and chinook salmon would be classified as a riverine- Orr et al.: Foraging habits of Phoca vitulina richardsi in the Umpqua River, Oregon 111 estuarine species because these prey items could feasibly be consumed in the river. It was assumed that the seal was feeding in the marine environment if a sample contained exclusively marine prey, such as Pacific hagfish (Eptatretus stoutti). Pacific hake (Merluceius productus), and rockfish (Sebastes spp. ). If a scat comprised prey taxa that poten- tially could be found in a riverine-estuarine system or marine waters (e.g. salmonids, osmerids), as well as those found exclusively in marine waters, then it was assumed that the feeding environment was marine or mixed. Salmonid skeletal remains were sent to the CBMGL for species identification. Remains to be analyzed genetically were selected by number or size (or both) to represent dif- ferent species or individuals present in each scat. For ex- ample, if a scat had 95 approximately equal-size vertebrae (a salmonid has approximately 65 vertebrae; Butler, 1990). then at least two vertebrae (potentially representing at least two individuals) were sent for genetic identification. Also, if a sample had a very large gillraker and three small vertebrae, then the gillraker and one vertebra were sent for genetic identification. The size of diagnostic structures was also used to categorize salmon remains as juvenile or adult, when possible. The CBMGL identified salmonid spe- cies by direct sequencing of mitochondrial DNA or analysis of restriction fragment length polymorphism (Purcell et al., 2004). The abundance of prey taxa in harbor seal diet for each period was described by using the minimum number of individuals (MNI) and percent frequency of occurrence (%FO). We compared the effect of including bone on the number of prey consumed by estimating MNI using the greater number of right or left otoliths and then again using all diagnostic skeletal remains. Cephalopod MNI was estimated from the greater number of upper or lower beaks. The % FO of prey taxon i was defined as I°" %FO, x 100, where O ll; = absence (0) or presence (1) of taxon i in scat k\ and s = the total number of scats that contained identifiable prey remains. The presence of taxon ;' in scat k was determined by using otoliths and then again using all structures. To account for variability in diet, point estimates of %FO for a prey taxon were determined during each sampling period and then averaged for each season. Results Scats Over 725 scats were collected during all periods. The number of scats collected with identifiable remains was 119 (99%; n=148) in fall 1997, 219 (93%; ?z=254) in spring 1998, and 313 (98%; n=326) in fall 1998 (Table 1). Of the 651 samples with identifiable prey remains, 605 (93%) con- tained fish bones, 347 (53%) had fish otoliths, 231 (36%) contained remains from cartilaginous fish, and 41 (6% ) had cephalopod beaks. A majority (65% fall 1997, 65% spring 1998, 63% fall 1998) of scats with identifiable remains had one to three prey taxa present and less than 4% contained more than ten taxa. Approximately 40 prey taxa, repre- senting at least 25 families, were identified throughout the study (Tables 2 and 3). For nearly all prey taxa, MNI was greater when all skel- etal remains were identified than when otoliths were used exclusively (Table 2). For several species, such as Pacific hake. Pacific herring (Clupea pallasii), and Pacific sardine {Sardinops sagax), MNI at least tripled when all structures were used for enumeration (Table 2). For most salmonids, cartilaginous fishes, three-spine stickleback, Irish lords (Hemilepidotus spp.), and Pacific mackerel {Scomber ja- ponicus), no otoliths were recovered; therefore other skel- etal elements had to be used for identification (Table 2). For a few prey, such as cyprinids, gobiids, and butter sole (Isopsetta isolepis), only otoliths were recovered (Table 2). Foraging habits The %FO for most prey taxa was greater when all struc- tures were used than when j ust otoliths were used ( Table 3 ). The %FO indicated that the prey most frequently con- sumed were pleuronectids. Pacific hake. Pacific staghorn sculpin {Leptocottus armatus), osmerids, and shiner surf- perch (Cymatogaster aggregata). Prey frequently found in scats included those that were exclusively marine (e.g. Pacific hake, rex sole (Glyptocephalus zachirus), English sole (Parophiys vetulus), and myxinids), and those that occur in both marine and estuarine waters (e.g. Pacific staghorn sculpin. and shiner surfperch (Table 3] ). Only 24% of scats were composed entirely of prey taxa that could be found in riverine-estuarine systems (Fig. 2). Consequently, a majority of the scats contained prey species that were exclusively marine (.v=25.3%) or were a mixture of marine and potentially marine species (x=50.8%\ Fig. 2). Salmonids Salmonid remains were found in only 6% (39/651) of the samples. Five chinook smolts were identified from otoliths in two samples collected during fall 1997; in the remaining 37 samples, salmonid bones were unidentifiable to species with conventional techniques. With the cooperation of CBMGL, we examined 116 salmonid bones using molecular genetic techniques. Species identification was successful for 67% (78/116) of the bones and teeth from 90% (35/39) of the scat samples that contained salmonid structures. In the four samples that remained unidentified, three con- tained only a single salmonid bone that failed to produce any DNA. Most of the other bones where DNA could not be extracted were small or fragmented and highly digested. Seventeen of the samples contained chinook salmon bones (including the two samples with chinook salmon otoliths); 11 contained coho salmon bones, four contained steelhead trout bones, and three contained bones from two salmonid 112 Fishery Bulletin 102(1) Table 2 Minimum number of individuals ( MNI ) offish prey derived from sagittal otoliths and all structures retrieved from harbor seal scats collected at the Umpqua River during 1997 and 1998. s represents the number of scats with identifiable remains, na indicates taxon did not have sagittal otoliths to be used for identification. Fall 1997(s=119i Spring 1998(s=219i Fall 1998(s=313) MNI MNI MNI MNI MNI MNI Family Species otoliths all structures otoliths all structures otoliths all structures Ammodytidae Pacific sand lance 205 208 317 321 3 7 Bothidae Pacific sanddab 12 13 9 9 1 2 Clupeidae American shad 1 2 4 11 1 15 Pacific herring 6 22 3 10 121 345 Pacific sardine 50 235 39 185 Cottidae Pacific staghorn sculpin 44 65 25 48 30 85 unidentified cottid 8 Cyprinidae peamouth chub 1 1 4 4 4 4 Embiotocidae shiner surfperch 104 109 209 274 23 104 Engraulididae northern anchovy 1 3 1 2 Gadidae Pacific hake 1 35 10 44 58 199 Pacific tomcod 9 21 19 52 8 26 Gasterosteidae threespine stickleback 1 Gobiidae unidentified gobiid 2 2 1 1 Hexagrammidae lingcod 1 1 1 Myxinidae Pacific hagfish 20 13 61 Ophidiidae spotted cusk-eel 4 4 2 2 Osmeridae unidentified osmerid 42 54 14 41 105 132 Petromyzontidae Pacific lamprey na 5 na 89 na 41 river lamprey na 2 na 1 na Pholididae saddleback gunnel 3 7 1 3 1 Pleuronectidae English sole 38 41 37 39 75 84 Dover sole 1 4 5 6 27 51 slender sole 1 1 18 24 28 42 butter sole 1 1 15 15 2 2 rex sole 19 44 44 53 96 125 petrale sole 1 1 starry flounder 10 17 8 12 6 31 Rajidae unidentified rajid na 1 na 7 na 4 Scombridae Pacific mackerel 2 3 2 Scorpaenidae Sebastes spp. 15 6 19 2 3 Trichodontidae Pacific sandfish 1 2 3 Zoarcidae unidentified zoarcid 2 2 Salmonidae coho salmon unknown 4 juvenile 1 4 2 adult 1 3 Steelhead or rainbow trou t unknown 2 2 juvenile 1 chinook salmon unknown 5 6 3 juvenile 5 2 5 adult 1 unidentified salmonid unknown 2 1 2 juvenile 1 1 Orr et al.: Foraging habits of Phoca vitulina richardsi in the Umpqua River, Oregon 113 Table 3 Mean percent frequency of occurrence (%FO) of common prey recovered from harbor seal scat samples collected at haulout sites in the Umpqua River, Oregon, during 1997 and 1998. SD indicates standard deviation. Family Species Fall 1997 Spring 1997 Fall 1998 Mean(±SD) Mean(±SD) Mean(±SDl Ammodytidae Pacific sand lance 12.5 ±8.3 12.6 ±8.3 9.1 ±8.9 Bothidae Pacific sanddab 11.4 ±7.5 4.1 ±2.5 3.0 ±3.2 Clupeidae American shad 4.3 ±0.6 13.0 ±2.3 5.3 ±3.1 Pacific herring 16.9 ±13.7 7.3 ±6.9 35.9 ±21.8 Pacific sardine 16.1 ±12.2 17.9 ±9.1 Cottidae Pacific staghorn sculpin 23.9 ±8.5 21.0 ±19.0 11.8 ±4.5 unidentified cottid 16.5 ±20.4 3.2 ±0.7 0.8 ±0.1 Cyprinidae peamouth chub 3.8 2.3 ±0.6 2.8 Embiotocidae shiner surfperch 18.2 ±8.2 23.6 ±19.4 7.0 ±2.9 Engraulididae northern anchovy 5.5 ±3.2 2.1 ±2.0 Gadidae Pacific hake 27.9+9.7 17.0 ±5.7 41.6 ±25.5 Pacific tomcod 15.4 ±7.8 16.1 ±7.0 12.3 ±8.3 Gasterosteidae threespine stickleback 2.8 Gobiidae unidentified gobiid 7.7 1.7 Hexagrammidae lingcod 3.8 0.7 Loliginidae market squid 12.8 ±10.2 3.5 ±1.3 Myxinidae Pacific hagfish 17.5 ±7.9 6.7 ±3.5 16.5 ±9.4 Octopodidae Octopus rubescens 3.8 ±1.4 8.3 ±2.6 8.4 ±7.0 Ophidiidae spotted cusk-eel 0.9 Osmeridae unidentified osmerid 20.8 ±11.3 14.6 ±8.2 19.5 ±10.0 Petromyzontidae Pacific lamprey 7.7 ±8.2 20.5 ±10.1 8.2 ±2.9 river lamprey 5.6 3.7 Pholididae saddleback gunnel 14.7 ±16.9 2.6 ±0.3 5.3 Pleuronectidae English sole 21.9 ±1.7 8.7 ±5.2 17.5 ±12.0 Dover sole 7.4 ±5.9 4.6 ±0.7 13.5 ±13.6 slender sole 11.0 ±7.2 14.9 ±14.9 butter sole 3.8 7.2 ±3.7 1.4 rex sole 27.4 ±12.1 14.2 ±9.6 19.9 ±20.5 petrale sole 0.7 starry flounder 15.8 ±7.4 3.7 ±1.0 5.8 ±1.2 Rajidae unidentified rajid 2.8 5.0 ±1.6 2.8 Scombridae Pacific mackerel 3.8 ±1.4 4.6 ±4.0 0.8 ±0.1 Scorpaenidae Sebastes spp. 15.7 ±8.3 9.1 ±2.6 2.1 Trichodontidae Pacific sandfish 1.7 2.1 unidentifed bothid/ unidentified flatfish 38.5 ±15.9 20.2 ±10.3 14.8 ±2.5 pleui-onectid Zoarcidae unidentified zoarcid 1.4 Salmonidae coho salmon unknown 5.8 ±3.6 juvenile 4.8 3.3 ±2.3 0.7 adult 2.4 6.2 ±6.2 steelhead/rainbow trout unknown 2.7 ±1.4 0.7 juvenile 0.9 adult 0.9 chinook salmon unknown 7.6 ±3.5 0.8 ±0.1 juvenile 4.0 ±1.1 3.4 3.6 ±3.0 adult 4.8 unidentified salmonid(s) unknown 4.3 ±0.6 2.4 0.8 ±0.1 juvenile 4.8 7.7 114 Fishery Bulletin 102(1) species (two with coho and chinook salmon and one with coho salmon and steelhead trout, Table 2). No cutthroat trout were identified with conventional or molecular genetic techniques. Using otoliths and other diagnostic skeletal struc- tures, we enumerated at least 54 individual salmonids in 39 scats (Table 2). All individuals identified as adults I n =5 ) were coho salmon, except one chinook salmon from spring 1997. Individual juveniles identified as steelhead trout (n=l), coho salmon (re=7), chinook salmon («=12), or unidentified salmonids (/2=2) were present during all periods. Because of the difficulty of determining age from size-variable structures such as gillrakers and teeth, most individuals («=27) were designated as "unknown age." Discussion Investigating diet is essential to assessing the role of harbor seals in marine and freshwater ecosystems in order to quantify their interactions with fisheries and determine their impact on the recovery of endangered species. All methods used to investigate diet of seals and other pinnipeds have some limitations (Murie and Lavigne, 1985, 1986; Harvey, 1989). With scats, it is assumed that the relative frequency of prey identified from undigested remains reflects the frequency of prey eaten (Tollit et al., 1997). However, several investigators have determined that this assumption may be seriously biased in several ways (Hawes, 1983; da Silva and Neilson, 1985; Jobling, 1987; Dellinger and Trillmich, 1988; Harvey, 1989; Pierce and Boyle, 1991; Cottrell et al., 1996; Tollit et al., 1997; Bowen, 2000; Orr and Harvey, 2001). No diet study can estimate detrimental or lethal impacts to prey resulting from harassment by pinnipeds. In addition, once a prey is captured, a seal might consume only the soft tissue (especially of larger prey), which would not leave identifiable evidence in scats. Additionally, because skel- etal remains from different prey species pass through the alimentary canal and erode at different rates they may not reflect the true number or proportions of prey consumed (Hawes, 1983; Harvey, 1989; Pierce and Boyle, 1991; Cottrell et al., 1996; Tollit et al., 1997). Therefore, preda- tion estimates determined from scat samples should be regarded as a measure of minimum impact. Although there are complications inherent in the use of scats to describe the diet of seals, scat analysis remains useful because many scats can be collected quickly, with minimum effort and without harm to the animals (Harvey, 1989). Scats Recently, skeletal remains other than otoliths and beaks have begun to be used to identify and enumerate prey of pinnipeds (e.g. Olesiuk et al., 1990; Cottrell et al., 1996; Riemer and Brown, 1997; Browne et al., 2002). There are constraints, however, for using all skeletal elements to identify prey species, including the need for a reference col- lect ion and the extensive training of personnel to identify Fall I9M7 Q nverine-estuanne marine or mixed Scat categorization Figure 2 Mean percentage plus standard deviation (SD) of scats that were classified as "riverine-estuarine" (i.e. samples composed of prey taxa that are exclusively or potentially (e.g. anadromous species, osmerids) found in rivers or estuaries), "marine" (i.e. samples composed exclusively of prey that inhabit marine waters l, and "marine or mixed" (i.e. samples composed of prey taxa exclusively found in marine waters or those that might inhabit marine waters at some stage in their life). digested prey structures (Cottrell et al., 1996). Moreover, there is usually a bias in the recovery and recognition of prey structures from different taxa (Cottrell et al., 1996; Laake et al., 2002). This bias may be a significant problem in estimating relative abundance of prey or biomass con- sumption by harbor seals and is the reason these indices were not considered in this study. Despite these complications, the use of all available structures increased our estimates of prey diversity, MNI, and % FO for most prey taxa. Examination of all diagnostic structures also allowed us to consider a greater sample size because 93% of scats with identifiable remains contained bones, whereas only 53% of scats contained otoliths. Spe- cies not represented by otoliths, such as salmonids (during 1998) and cartilaginous fishes, were detected because all structures were used. In addition, the MNI of important prey such as Pacific hake. Pacific herring, and Pacific sar- dine would have been greatly underestimated had otoliths been used exclusively because the MNI derived by using all structures was at least threefold greater. Although there are complexities associated with estimating MNI from all structures, this method avoids the use of numerical correc- tion factors determined from recovery rates of otoliths fed to captive seals during laboratory experiments (Browne et al., 2002). Results from captive experiments are highly variable between repeated trials for the same individual and among different individuals (Harvey, 1989; Bowen et al., 2000; Orr and Harvey, 2001 1, Foraging habits Harbor seals in the lower Umpqua River consumed prey from over 35 taxa; however, only a few prey taxa were dominant in their diet, as reflected by %FO. Overall, the five most abundant families of prey were Clupeidae, Cot- Orr et al.: Foraging habits of Phoca vitulina nchardsi in the Umpqua River, Oregon 115 tidae, Embiotocidae, Gadidae, and Pleuronectidae. These are similar to those reported in other studies of harbor seal diet in Oregon (Riemer and Brown, 1997; Browne et al., 2002; Riemer et al. 3 - 4 ). It was evident by the presence of prey like Pacific hake. Pacific sardine, hagfish, and various flatfishes that seals fed offshore in pelagic and demersal areas. Harbor seals also consumed prey (e.g. Pacific staghorn sculpin) com- monly found inshore or in estuarine waters. The NMFS recommendations to remove pinnipeds from systems where endangered prey also occur, rely on the assumption that pinnipeds are primarily feeding (on ESA-listed species) in that system. Our study indicated that this was not the case. Although the seals at the Umpqua hauled out several kilometers up river, they foraged primarily at sea. Because of the life histories of many of the prey taxa, our foraging habitat categories must be considered estimations of where the prey might have been consumed. For example, we estimated that 24% of scats contained prey attributable to the riverine-estuarine environment. However, this may actually be an overestimation because some of these spe- cies potentially inhabit the marine environment at some time in their life and may have been consumed there. Ad- ditionally, scats categorized as marine or mixed may reflect that the seal fed solely in the marine environment (because all the taxa can potentially be found in marine waters) or fed at sea and within the river. Nevertheless, these catego- ries are useful for a broad apportioning of foraging habitat. Even though we were able to determine that approximately 76% of the scats contained marine and potentially marine prey taxa, we were unable to assess whether this reflected a seal population with homogeneous or heterogeneous for- aging patterns. In other words, because the scats could not be attributed to a particular individual, we had no way of discerning: 1) whether the entire seal population foraged roughly three-fourths of the time at sea and one-fourth of the time in the river, or 2) whether 76% of the seals fed at sea whereas 24% foraged closer to shore and in the river. This distinction may be important if only a subgroup of seals is feeding in the river and preying on fish that are seasonally abundant in the estuary, such as salmonids. Studies that incorporate radio- or satellite-telemetry or genetic identification of individual prey items in scats may reveal these distinctions in the future. Because the seals haul out almost 5 km upriver and have been observed as far as 32 km upriver, it is clear that 3 Riemer, S. D., R. F. Brown, and M. I. Dhruv. 1999. Monitoring pinniped predation on salmonids in the Alsea and Rogue River estuaries: fall. 1997. //; Pinniped predation on salmonids: pre- liminary reports on field investigations in Washington, Oregon, and California, p. 104-152. Compiled by National Marine Fisheries Service, Northwest Region. [Available from ODFW, 7118 NE Vandenberg Avenue, Corvallis, OR 97330.] 4 Riemer, S. D., R. F. Brown, and M. I. Dhruv. 1999. Monitoring pinniped predation on salmonids in the Alsea and Rogue River estuaries: fall, 1998. In Pinniped predation on salmonids: pre- liminary reports on field investigations in Washington, Oregon, and California, p. 153-188. Compiled by National Marine Fisheries Service, Northwest Region. [Available from ODFW. 7118 NE Vandenberg Avenue, Corvallis, OR 97330.] seals use the river environment. However, the prevalence of marine fish remains in the scat samples indicates that the seals that haul out at the Umpqua River do not feed exclusively in the river. The predominance of marine prey may reflect a foraging strategy in which the effort required to find marine sources of food is offset by the energy gained by exploiting large aggregations of marine schooling fish (e.g. Pacific hake and Pacific sardine). In this scenario, the seals in the Umpqua estuarine-riverine system may depend on marine resources while taking advantage of protected estuarine waters that provide a sheltered place to rest and occasionally feed. Salmonids We used two methods to estimate the number of salmonids eaten by harbor seals: prey remains and genetic analyses of scat samples. Analysis of skeletal remains was of lim- ited value because the majority of salmonid structures recovered from scat samples were bones, which could be identified only to family. This study represents a novel application of genetic techniques to identify salmonid spe- cies from bones found in scats. These techniques allowed us to determine species for a majority of the salmonid samples that would have otherwise remained unidentified because they did not contain otoliths. Salmonid bones or otoliths were found in 6% of the har- bor seal scats collected during our study — a finding that is comparable to the 5% found by Laake et al. (2002) at the Columbia River. However, it is about one-half of what was found by Riemer and Brown ( 13% ; 1997 1 at selected sites in Oregon. Brown et al. (1995) found salmonids in 12% of gastrointestinal tracts of harbors seals taken incidentally by commercial salmon gillnet fishing operations, and Roffe and Mate (1984) observed that salmonids made up 30% of the prey for harbor seals surface feeding in the Rogue Riv- er. Regardless of sampling method, in these studies, most of the salmonids could be identified only to family because few otoliths were recovered and genetic techniques to identify bones to species had not yet been developed. Salmonids are present in the Umpqua River year-round although species and age composition change throughout the year. In this study, most salmonid prey of known age were juveniles; however, we could determine age of only one-half of the individuals. Juveniles are found in the Umpqua River system year-round and may be easier for seals to catch than adults. Alternatively, perhaps seals did not consume many adult skeletal elements because adult salmonids are large fish, which may be ripped apart rather than swallowed whole. Our sampling seasons encompassed at least some por- tion of the migrations of all salmonids, all of which (except cutthroat trout ) were prey of harbor seals. The fact that portions of all migrations were included in the sampling design was noteworthy because there were a large num- ber of seals in the river throughout the year and yet we found no evidence through genetic or otolith identification that seals consumed cutthroat trout in the Umpqua River. The genetic identification tools developed and applied in our collaboration with CBMGL were useful in discerning 116 Fishery Bulletin 102(1) scarce from abundant salmonids. These techniques may be useful in identifying other pinniped prey that lack spe- cies-specific structures and would allow managers to better assess the impact of pinniped predation on threatened or endangered species. Acknowledgments This study was proposed and initiated in collaboration with Joe Scordino. Scat collection and harbor seal counts were conducted by Lawrence Lehman, Kirt Hughes, Mer- rill Gosho, Sharon Melin, and Robert DeLong. The U.S. Coast Guard Umpqua River Station provided boat storage and a location for keeping a chest freezer during the 1997 field season. We would like to thank the Oregon Institute of Marine Biology, Charleston, OR, where the samples col- lected during 1997 were processed. We greatly appreciate the collaboration with Conservation Biology Molecular Genetics Laboratory, which resulted in the identification of our salmon remains based on genetic methods. We would also like to thank Susan Reimer who kindly helped us with difficult identifications, as well as Lawrence Lehman and Jason Griffith for their verification of bone and otolith identifications. We thank Patience Browne, Patrick Gearin, John Jansen, Mark Dhruv, and three anonymous review- ers for providing helpful comments on earlier drafts of this manuscript. Literature cited Bigg, M. A.. G. Ellis, P. Cottrell, and L. Milette. 1990. Predation by harbour seals and sea lions on adult salmon in Comox Harbour and Cowichan Bay, British Columbia. Can. Tech. Rep. Fish. Aquat. Sci. 1769, 31 p. Bowen, W. D. 2000. Reconstruction of pinnipeds diets: accounting for complete digestion of otoliths and cephalopod beaks. Can. J. Fish. Aquat. Sci. 57:898-905. Brown, R. F. 1980. Abundance, movements and feeding habits of the harbor seal, Phoea vitulina, at Netarts Bay, Oregon. M.S. thesis, 69 p. Oregon State Univ., Corvallis, OR. Brown, R. F., S. D. Riemer, and S. Jefferies. 1995. Food of pinnipeds collected during the Columbia River Area Commercial Salmon Gillnet Observation Program, 1991-1994. ODFW (Oregon Dep. Fish Wildlife), Wildlife Diverstiy Program Tech. Rep. 95-6-01, 16 p. Brown, R. F, and S. Kohlmann. 1998. Trends in abundance and current status of the Pacific harbor seal {Phoea vitulina richardsi) in Oregon: 1977-1998. ODFW, Wildlife Diverstiy Program Tech. Rep. 98-6-01, 16 p. Browne, P., J. L. Laake, and R. L. DeLong. 2002. Improving pinniped diet analyses through identifica- tion of multiple skeletal structures in fecal samples. Fish. Bull. 100:423-433. Butler. U. L. 1990. Distinguishing natural from cultural salmonid dep- osits in Pacific Northwest North America. Ph.D. diss., 218 p. Univ. of Washington, Seattle, WA. Cottrell, P. E., A. W. Trites, and E. H. Miller. 1996. Assessing the use of hard parts in faeces to identify harbour seal prey: results of captive-feeding trials. Can. J. Zool. 74:875-880. da Silva, J., and J. Neilson. 1985. Limitations of using otoliths recovered in scats to estimate prey consumption in seals. Can. J. Fish. Aquat. Sci. 42:1439-1442. Dellinger, T, and F. Trillmich. 1988. Estimating diet composition from scat analysis in otariid seals (Otariidae): is it reliable? Can. J. Zool. 66: 1865-1870. Eschmeyer. W. N, E. S. Herald, and H. Hammann. 1983. A field guide to Pacific Coast fishes of North America, 336 p. Houghton Mifflin Co., Boston, MA. Harvey, J. T. 1987. Population dynamics, annual food consumption, move- ments and dive behaviors of harbor seals, Phoca vitulina richardsi, in Oregon. Ph.D. diss., 177 p. Oregon State Univ., Corvallis, OR. 1989. Assessment of errors associated with harbor seal (Phoca vitulina) faecal sampling. J. Zool., Lond. 219: 101-111. Hawes, S. 1983. An evaluation of California sea lion scat samples as indicators of prey importance. M.S. thesis, 50 p. San Francisco State Univ. San Francisco, CA. Jobling, M. 1987. Marine mammal faeces samples as indicators of prey importance — a source of error in bioenergetics studies. Sarsia 72:255-260. Johnson, O, M. Ruckelshaus, W Grant. F. Waknitz, A. Garrett. G. Bryant, K. Neely, and J. Hard. 1999. Status review of coastal cutthroat trout from Washing- ton, Oregon, and California. NOAA Tech. Memo. NMFS- NWFSC-37, 292 p. King, J. 1983. Seals of the world, 240 p. Comstock Publishing Assoc, Cornell Univ. Press, New York, NY. Laake, J. L., P. Browne. R. L. DeLong, and H. R. Huber. 2002. Pinniped diet composition: a comparison of estimation models. Fish. Bull. 100:434-447. Murie, D., and D. Lavigne. 1985. A technique for the recovery of otoliths from stomach contents of piscivorous pinnipeds. J. Wildl. Manag. 49: 910-912. 1986. Interpretation of otoliths in stomach content analy- ses of phocid seals: Quantifying fish consumption. Can. J. Zool. 64:1152-1157. NMFS (National Marine Fisheries Service). 1997. Investigation of scientific information on the impacts of California sea lions and Pacific harbor seals on salmo- nids and on the coastal ecosystem of Washington, Oregon, and California. NOAA Tech. Memo. NMFS-NWFSC-28, 172 p. Olesiuk, P. E, M. A. Bigg, G. M. Ellis. S. J. Crockford, and R. J. Wigen. 1990. An assessment of the feeding habits of harbour seals (Phoca vitulina i in the Strait of Georgia. British Columbia, based on scat analysis. Can. Tech. Rep. Fish. Aquat. Sci. 1730. 135 p. Orr, A. J., and J. T. Harvey. 2001. Quantifying errors associated with using fecal sam- ples to determine the diet of the California sea lion {Zalo- phu* califbrnianus). Can. J. Zool. 79:1080-1087. Orr et al.: Foraging habits of Phoca vitultna richardsi in the Umpqua River, Oregon 117 Pearson, J., and B. Verts. 1970. Abundance and distribution of harbor seals and northern sea lions in Oregon. Murrelet 51:1-5. Pierce, G. J., and P. R. Boyle. 1991. A review of methods for diet analysis in piscivorous marine mammals. Ocean. Mar. Biol. Ann. Rev. 29:409-486. Purcell, M, G. Mackey, E. LaHood, H. Huber, and L. Park. 2004. Molecular methods for the genetic identification of salmonid prey from Pacific harbor seal ( Phoca vitulina richardsi) scat. Fish. Bull. 102:213-220. Reeves, R., B. Stewart, and S. Leatherwood. 1992. The Sierra Club handbook of seals and sirenians, 359 p. Sierra Club Books, San Francisco. CA. Riemer, S. D., and R. F. Brown. 1997. Prey of pinnipeds at selected sites in Oregon identi- fied by scat (fecal) analysis, 1983-1996. ODFW Wildlife Diversity Program Tech. Rep. 97-6-02. 34 p. Roffe, T, and B. Mate. 1984. Abundances and feeding habits of pinnipeds in the Rogue River, Oregon. J. Wildl. Manag. 48:1262-1274. Tollit, D. J., M.J. Steward, P. M. Thompson, G J. Pierce, M. B. Santos, and S. Hughes. 1997. Species and size differences in the digestion of oto- liths and beaks: implications for estimates of pinniped diet composition. Can. J. Fish. Aquat. Sci. 54:105-119. U. S. Fish and Wildlife Service. 2000. Endangered and threatened wildlife and plants: final rule to remove the Umpqua River cutthroat trout from the list of endangered wildlife. Federal Register: 26 April 2000, 65181:24420-24422. 118 Abstract— Larval development of the sidestriped shrimp ^Pandalopsis dis- par) is described from larvae reared in the laboratory. The species has five zoeal stages and one postlarval stage. Complete larval morphological charac- teristics of the species are described and compared with those of related species of the genus. The number of setae on the margin of the telson in the first and second stages is variable: 11+12, 12+12, or 11+11. Of these, 11+12 pairs are most common. The present study confirms that what was termed the fifth stage in the original study done by Berkeley in 1930 was the sixth stage and that the fifth stage in the Berkeley's study is comparable to the sixth stage that is described in the present study. The sixth stage has a segmented inner fla- gellum of the antennule and fully devel- oped pleopods with setae. The ability to distinguish larval stages of P. dispar from larval stages of other plankton can be important for studies of the effect of climate change on marine communities in the Northeast Pacific and for marine resource management strategies. Larval development of the sidestriped shrimp (.Pandalopsis dispar Rathbun) (Crustacea, Decapoda, Pandalidae) reared in the laboratory Wongyu Park School of Fisheries and Ocean Sciences University of Alaska Fairbanks Juneau, Alaska, 99801-8677 E-mail address: wparkig'uaf edu R. Ian Perry Pacific Biological Station, Fisheries and Oceans Nanaimo, British Columbia, V9R 5K6, Canada Sung Yun Hong Department of Marine Biology Pukyong National University Pusan, 608-737, Korea Manuscipt approved for publication 23 June 2003 by Scientific Editor. Manuscript received 20 October 2003 at NMFS Scientific Publications Office. Fish. Bull. 102:118-126 (2004). Sixteen species of the genus Pandalop- sis have been recognized in the South- western Atlantic and North Pacific Oceans (Komai, 1994; Jensen, 1998; Hanamura et al., 2000). Most members of the genus attain a large body size and are valuable as commercial fishery resources (Holthuis, 1980; Baba et al., 1986). In the North Pacific, P. dispar, P. ampla, P. aleutica, P. longirostris, P. lucidirimicola, and P. spinosior have been reported. Of these, Pandalopsis dispar is an important component of the commercial shrimp fisheries along with several species of the genus Pandalus. Commercial landings of shrimp during 1999 totaled approximately 19 million tonstPSMFC, 1999). Knowledge of the life histories of these species, including the duration and growth of their larvae, is important for stock assessment and management. However, remarkably little is known about their early life histories because most species of the genus live at con- siderable depths. Of the 16 Pandalopsis species, the larvae of only three species have been described partly or com- pletely from plankton samples or from larvae reared in the laboratory. The larvae of Pandalopsis japonica were described completely from specimens reared in the laboratory by Komai and Mizushima (1993). Kurata (1964) described the first stage of P. cocci nata from plankton samples and from larvae hatched in the laboratory. Thatje and Bacardit (2000) assumed that larvae of P. ampla occurring in Argentine waters were similar to those of P. dispar and Pandalopsis coccinata. Berkeley ( 1930) described four larval stages of P. dispar based on samples collected in British Columbia coastal waters. The first stage was obtained from ovigerous females, whereas the larvae of the other stages were separated from plankton samples. In addition, the stage described as the fifth stage was not clearly defined. In this study, we describe the complete series of larval stages of P. dispar using specimens reared in the laboratory. Materials and methods Ovigerous females of Pandalopsis dispar were collected on 25 March Park et al.: Larval development of Pandalopsis dispor 119 1999 by using a small shrimp trawl fished at depths of about 40 m near Gabriola Island in the vicinity of the Pacific Bio- logical Station, Nanaimo, Brit- ish Columbia (latitude 49°13', longitude 123°55'). Water tem- perature at the collection site was around 9°C, and salinity was 29.0 < ?c The females were each kept in a 20-L jar with seawater. The larvae hatched on 1 April 1999. Hundreds of larvae hatched from one female. Of these, one hundred newly hatched larvae were transferred into individual 250-mL jars. To obtain samples for drawing and descriptions, a total of 150 larvae from the female were reared in a 20-L jar. Newly hatched Artemia nauplii were used to feed the larvae. We used filtered natu- ral seawater from 40 m depth without adjusting the water temperature or salinity. Water temperature during the rearing experiments ranged from 8.7°C to 12.2°C (mean 10.5°C). Salin- ity during the rearing experi- ments ranged from 26.0%c to 31.0% f (mean 28.9%o). The water in each jar was changed daily. All drawings were made with a drawing tube attached to a mi- croscope. Carapace length (CD was measured with an ocular micrometer from the posterior edge of the orbital arch to the middorsal posterior edge of the carapace. The anatomical terms used in this paper are from Pike and Williamson ( 1969) and Haynes (1985). Measurement bars represent 1 mm. Figure 1 Results In the complete larval development of Pandalopsis dispar there are five zoeal stages. In addition, there is one post- larval stage. The duration of each larval stage and the survival rate of P. dispar are shown in Table 1. Larval description First stage Carapace (Fig. 1A) Carapace length (CL), 1.6 mm (SD: 0.06 mm, n=89); with concave lateral margin; rostrum long. well developed and directed forward and upward; weak Table 1 Duration of each larval stage of Pandalopsis dispar at 8.7-12.2°C (mean 10.5°C) and 26.0-31.0% (mean28.9%c). Stage 6 is a postlarval stage. Mean duration Range Number of Stage (day) (day) ] arvae observed 1 10.7 9-15 89 2 8.9 8-11 81 3 9.5 8-14 67 4 10 9-12 59 5 10.8 10-13 51 6 10.5 9-12 48 120 Fishery Bulletin 102(1) dorsal denticles and bare ventral tubercles on rostrum; rostrum about 0.7 times as long as carapace. Eyes (Fig. 1 A) Sessile. Abdomen (Fig. 1A) 5 somites plus telson. Antennule (Fig. 1, A and B) Peduncle unsegmented with a strong seta at distromesial margin; outer flagellum with 2+2 short aesthetascs. Antenna (Fig. 1, A and C) Longer than the whole body length; flagellum segmented throughout its length; outer- distal corner terminated with an acute spine and a minute seta; inner-distal margin 5-segmented with 1, 1, 1, 1, 2 setae; inner margin fringed with 28-29 setae. Measurement bars represent 1 mm. Figure 2 Mandible (Fig. 1 D) Asymmetrical; without the same arrangement of denticles, however, almost the same size; incisor process not separated from molar process; armed with several teeth on molar part. Maxillule (Fig. 1 E) Coxal and basal endite with serially developed strong spines and multiple setae; endopod with 2+3 terminal setae Maxilla (Fig. 1 F) Palp with 2, 1, 1, 2 setae; coxal endite with 6 distal setae; basal endite with 8 distal setae; broad scaphog- nathite with narrow posterior lobes having long naked setae. First maxilliped (Fig. 1G) Endites separated by shallow notch and with multiple setae; bilobed epipod; endopod 4-seg- mented with 6, 3, 3, 4 setae; exopod with 14 plumose natatory setae; terminal segment with 3 terminal spines and 1 subterminal spine. Second maxilliped (Fig. 1 H) Coxa with 7 setae; basis with 3 setae; no epipod; endopod 5 segmented with 5, 5. 2. 4, 4 setae; exopod with 27 plumose natatory setae. Third maxilliped (Fig. II) Coxa with 1 seta; basis with 2 setae; endo- pod 5-segmented with various number of setae; exopod with 34-36 plumose natatory setae. Pereiopods (Fig. 1, J— N) 1 st pereio- pod (Fig. 1J) not chelate; 3 long ter- minal spines on dactylus; dactylus short; propodus longer than carpus; exopod without natatory setae; endopod of 2 nd pereiopod chelated (Fig. IK); chela with numerous small spines; ischium and carpus of pereiopods 3-5 (Fig. 1, L-N) longer than 1 st and 2 nd ones; propodus armed with several minute spines. Pleopods (Fig. lO) Bilobed buds, not functional. Telson (Fig. 1 P) Triangular form; broadened at the end, posterolat- eral margin with 11 + 12 (12+12. 11+11) marginal spines; each spine with fine hairs. Second stage Carapace (Fig. 2A) CL,2.2mm(SD: 0.11, n=81>: rostrum not strongly curved upwards; 5-6 prominent dorsal denticles and 3-4 weak ventral spines; rostrum shorter than carapace; supraorbital spine present. Eyes (Fig. 2A) Stalked; separated from carapace. Antenna (Fig. 2A) General shape unchanged; longer than that of 1 st Antennule (Fig. 2B) Peduncle 3- Park et al.: Larval development of Pandalopsis dispar 121 segmented; inner flagellum with 2 distal setae; outer flagellum with 2, 3, 4, 2 aesthetascs on inner margin. Mandible (Fig. 2C) General shape unchanged; bigger than that of 1 st stage. Maxillule (Fig. 2D) Coxal and basal endite with serially developed strong spines and multiple setae; endopodite with 2+3 spines; a strong subtermi- nal seta. Maxilla (Fig. 2E) Palp with 2, 2, 2, 3 setae; broad scaphogna- thite with narrow posterior lobe having a long naked seta; coxal endite with 6 distal setae; basal endite with 7 distal setae. First maxilliped (Fig. 2F) Epi- pod bilobed; endopod with 3+1, 2+1, 2+1, 3 setae; exopod unsegmented with 14 plumose natatory setae. Second maxilliped (Fig. 2G) One long and several intermedi- ate sized spines in basal endite; endopod 5-segmented; exopod with 24 plumose natatory setae. Third maxilliped (Fig. 2H) En- dopod 5-segmented, armed with many spines; exopod of 36 plu- mose natatory setae. Pereiopods (Fig. 2, I— M) Not chelate; 1 st pereiopod of 4 spines in basal endite; 3 strong and two weak spines in dactylus of 1 st pereiopod; general shape unchanged from 2 nd pereiopod through 5 th pereiopod. Pleopods (Fig. 2N) Bilobed buds, not functional; no seta and hair on buds; no further devel- opment from the 1 st stage. Telson (Fig. 20) Unchanged. Third stage Measurement bars represent 1 mm. Figure 3 Carapace (Fig. 3A) CL, 2.7 mm (SD: 0.12, rc=67); longer rostrum than that of 2 nd stage; almost 0.9 times as long as carapace; rostrum with 5-6 dorsal spines and 1-2 ventral spines. Antennule (Fig. 3B) Inner flagellum 2-segmented with 0, 2 setae; outer flagellum 2-segmented with 3+3+3, 3+3 aesthetascs. Antenna (Fig. 3A) General shape unchanged; longer than 2 nd stage. Mandible (Fig. 3C) Molar and incisor processes present; incisor process with 6-9 teeth; molar process with heavy teeth on biting edge. Maxillule (Fig. 3D) Palp with 2+3 setae; a small subtermi- nal spine; basal and coxal endite with numerous spines. Maxilla (Fig. 3E) Protopodite unsegmented; palp with 1, 2, 2, 1+2 setae and with 4 lobes; broad scaphognathite with narrow posterior lobe bearing numerous setae. First maxilliped (Fig. 3F) Epipod bilobed; endopod 4-seg- mented with 4, 2, 2, 2 setae; exopod with 15-16 plumose natatory setae; Second maxilliped (Fig. 3G) Coxal endite with an epipod and a strong spine; endopod 5-segmented with 3, 2, 2, 4, 6 setae exopod with setae. Third maxilliped (Fig. 3H) Coxal endite with one long and 122 Fishery Bulletin 102(1) one short spine; basal endite with 2 long and 2 interme- diate sized spines; endopod 5-segmented with numerous setae; exopod with 25-26 plumose natatory setae. Pereiopods (Fig. 3, 1— M) General shape unchanged except addition of setae. Pleopods (Fig. 3N) Buds biramous; much longer than that of 2 nd stage. Uropods (Fig. 30) Biramous; endopod with a fused spine at distal quarter of outer margin and numerous setae on inner distal margin; exopod with 4 spines on outer margin and numerous setae on inner distal margin. Telson (Fig. 30). With 12 pairs of posterolateral spines plus a median spine. ,F,I-M,Q , ,B,G,H,N Measurement bars represent 1 mm Figure 4 Fourth stage Carapace (Fig. 4A) CL. 3.1 mm (SD: 0.13. re=59); Rostrum slightly longer than carapace and directed forward; ros- trum with 15 dorsal spines and 6 ventral spines. Antenna (Fig. 4A) General shape unchanged; longer than that of 3 rd stage. Antennule (Fig. 4B) Much longer inner flagellum than that of 3 rd stage; inner flagellum about 0.9 times as long as outer flagellum, 2-segmented with 0, 2 setae; outer fla- gellum 6-segmented with 1, 2, 2, 3, 4 aesthetascs. Mandible (Fig. 4C) Similar to third stage. Maxillule (Fig 4D) General shape unchanged except addi- tion of setae on endites. Maxilla (Fig. 4E) Palp with 3, 2, 2, 3 setae; endites and scaphog- nathite added numerous setae. First maxilliped (Fig. 4F) Expod with 15 plumose natatory setae. Second maxilliped (Fig. 4G) Basal endite with an epipod and a long spine; exopod with 28-29 plumose natatory setae. Third maxilliped (Fig. 4H) Ex- popod with 36-37 plumose nata- tory setae. Pereiopods (Fig. 4, l-M) Num- ber of spines increased. Pleopods (Fig. 4N) Lobes much longer than those of third stage. Uropods (Fig. 40) Endopod and exopod with numerous setae on inner distal margin. Telson (Fig. 40) With 12 pairs of spines on posterolateral margin; a pair of lateral spines at distal third. Fifth stage Carapace (Fig. 5A) CL. 3.6 mm (SD: 0.15, re=51); Rostrum directed forward and upward, slightly longer than cara- pace; rostrum with 17-18 dorsal spines and 7-8 ventral spines. Antennule (Fig. 5B) Inner flagellum 3-segmented and about 0.9 times as long as outer flagellum: outer flagellum with 2+2+3+3+3+2+3+5 aesthetascs and distal third 6-segmented. Mandible (Fig. 5C) More ad- vanced development than that of 6 th ; not much change in biting surface. Maxillule (Fig. 5D) General shape unchanged except addi- tion of setae on endites. Park et al.: Larval development of Pandalopsis dispar 123 Maxilla (Fig. 5E) General shape unchanged. First maxilliped (Fig. 5F) Exo- pod with 16 plumose natatory setae. Second maxilliped (Fig. 5G) Exopod with 31-33 plumose natatory setae. Third maxilliped (Fig. 5H) Exo- pod with 46-48 plumose nata- tory setae. Pereiopods (Fig. 5, l-M) Is- chium slightly expanded in first pereipod. Pleopods (Fig. 5N) Much more developed than pleopods of 4 th stage; exopod with 13, 1 setae; endopod with 6 setae and ves- tiges of appendix interna. Uropod (Fig. 50) Exopod with numerous minute spines on outer margin Telson (Fig. 50) Both lateral margins parallel; 19 termi- nal spines; 2 pairs of lateral spines. Sixth stage Carapace (Fig. 6A) CL, 4.0 mm (SD: 0.21, n=48); adult-like. Antennule (Fig. 6B) Inner flagellum as long as outer fla- gellum; inner flagellum with multisegments; outer flagellum with numerous segments. Mandible (Fig. 6C) Incisor part separated from molar process and extended anteriorly. Maxillule (Fig. 6D) 9 terminal spines on basal endite. Maxilla (Fig. 6E) Palp with 2, 2, 2, 1+2 spines; broad scaphogna- thite with narrow posterior lobe bearing 3 long setae. First maxilliped (Fig. 6F) Exop- odite with 4+2, 2, 2 3 long and 1 short spines. Second maxilliped (Fig. 6G) spines; vestigial dactylus. Third maxilliped (Fig. 6H) Propodus armed with many spines; dactylus with 2 spines. Pereiopods (Fig. 6, l-M) 1 st pereipods with subchelated terminal segment; 1 st pereiopod with slightly expanded ischium. Pleopods (Fig. 6N) Endopod and exopod with numer- ous plumose natatory setae; endopod with epipod almost adult-like. Uropods (Fig. 60) Biramous; larger than those of fifth stage; adult-like. Measurement bars represent 1 mm. Figure 5 Basal endite with 2 long Telson (Fig. 60) Telson with 20 terminal spines and 4 pairs of lateral spines. Discussion The first stage larva of Pandalopsis dispar described by Berkeley (1930) is identical to the larva described in the present study. However, we found that she overlooked some important characteristics. She described the first stage larva as having 24 setae on the margin of the telson. We found, however, that the number of setae is variable, and that the larvae have 11+12, 12+12, or 11+11 marginal 124 Fishery Bulletin 102(1) setae. Of these, 11+12 pairs are more common than the others. Berkeley ( 1930) described the fifth stage based on plank- ton materials. In the present study, what was described by Berkeley ( 1930) as the fifth stage larva turned out to be the sixth stage because the larvae of this stage have fully devel- oped pleopods. Although the larvae of the fifth stage have somewhat natatory setose on their pleopods, they appear not to be completely functional. Compared to the larvae of P. japonica, P. dispar has one more stage than that of P. japonica. The pleopod development of P. japonica from the fourth stage to the fifth stage is very obvious, whereas that off! dispar has another stage and the changes in its fea- tures between the fourth and sixth stages are easily seen. Measurement bars represent 1 mm. Figure 6 The major characteristics of the six larval stages of P. dispar are summarized in Table 2. This table can be used for the identification of the larval stages of this species. Komai ( 1994) reviewed the morphological characters of the first larval stage of three Pandalopsis spp.: P. dispar. P. coc- cinata, and P.japonica.The larvae of P. dispar at this stage are quite different from those of the other two species. The larvae of P dispar have a triangular telson, whereas those of P coccinata and P. japonica have a semicircular telson. The adults of the genus Pandalopsis differ from those of other pandalid shrimps by having a laminated expansion on the first pereiopod (Schmit, 1921; Butler, 1980). This character is also present in larvae of P coccinata and P. japonica, whereas it is not present in larvae of P. dispar. From the third stage the is- chium does indicate expansion, however, it is not distinctive. It is assumed that in P dispar. the expansion should be distinctive after the larval stages. In P. coccinata and P. japonica f ) 'vi_— the ischium of the first pereio- pod has a laminated expansion; however, in P. dispar it has no lamination. The structure of the ischium of the first pereiopod can be a diagnostic feature of P. dispar in addition to the shape of the telson. Interspecific variation in the larval stages of pandalid shrimp is large, ranging from three to thirteen stages (Rothlisberg, 1980; Komai and Mizushima, 1993). Haynes (1980, 1985) assumed that P. dispar might have seven pelagic stages, or at least more than four. The pres- ent study has determined that P. dispar has five zoeal stages prior to the juvenile stage. Pandalopsis dispar is one of the four principal target species of shrimp trawl fisheries in both offshore and inshore areas of the NE Pacific Ocean (PICES, 2001) but has undergone very large fluctuations in abundance, particularly in Alaska where it was reduced to extremely low levels during the late 1980s and through the 1990s. These fluc- tuations appear to have been associated first with climate fluctuations (Anderson, 2000), and second with intense har- vesting (Oresanz et al., 1998). Anderson (2000) has suggested that pandalid shrimp population changes are one of the early in- i i< Park et al.: Larval development of Pandalopsis dispor 125 Table 2 Major characters of Pandalopsis dispar larvae. Characters Larval stage' 1 2 3 4 5 6 (postlarva) Antenna Inner flagellum One strong spine One peduncle with a few small spines 2 segments 2 segments 3 segments Multisegmented over 14 Outer Not segmented Slightly developed 2 segments 6 segments 7 segments 12 segments Telson 12+11, 12+12, or 11+11 10 pairs of terminal spines, 2 pairs of uropods One spine on each midlateral margin 2 spines on each lateral margin 4 spines on each lateral margin Pleopod development Wide as much as long Longer than wide Almost separated lobes Longer lobes than those of stage 3 Lobes separated completely with natatory setae Adult-like, with many natatory setae on both lobes ' Eyes of the first stags are sessile on carapace, whereas those of the second and later stages are stalked. dicators of shifts in marine communities in this region. Orensanz et al. (1998) have suggested it is important to recognize that crustacean stocks can have multiscale spatial structures; species have possibly both widely dis- tributed populations (such as in the oceanic offshore) and populations with discrete and localized distributions (as may occur in the nearshore inlets). The ability to distinguish the larval stages of Pandalopsis dispar from routine plankton samples is therefore of use in studying both these problems of population fluctuations and population distributions. Early identification of trends in strong versus weak year classes can provide rapid indica- tions of possible changes in large-scale climate conditions. Unambiguous identification of planktonic stages of P. dis- par is also essential for studies of the spatial structure of its populations, for studies of transport pathways and potential mixing rates among populations, and ultimately for under- standing the metapopulation structure of these populations. This latter point is critical for the development of improved management approaches, which may include identification of reproductive refugia (Orensanz et al., 1998). Acknowledgments We wish to thank Jim Boutillier and Steve Head for their support with this study. This study was supported by the Korea Research Foundation Grant (KRF-2002-013- H00005). Literature cited Anderson, P. J. 2000. Pandalid shrimp as indicators of ecosystem regime shift. J. Northw. Atl. Fish. Sci. 27:1-10. Baba, K., K. Hayashi, and M. Toriyama. 1986. Decapod crustaceans from continental shelf and slope around Japan, 336 p. Japan Fisheries Resource Conserva- tion Association, Tosho Printing Co. Ltd., Tokyo. Berkeley, A. 1930. The post-embryonic development of the common pan- dalids of British Columbia. Cont. Can. Bio. Fish., New Series 6:79-163. Butler, T H. 1980. Shrimps of the Pacific coast of Canada. Can. Bull. Fish. Aquat. Sci. 202, 280 p. Hanamura. Y., H. Khono. and H. Sakai. 2000. A new species of the deepwater pandalid shrimp of the genus Pandalopsis (Crustacea: Decapoda: Pandalidae) from the Kuril Islands, North Pacific. Crust. Res. 29:27-34. Haynes, E. 1980. Larval morphology of Pandalus tridens and summary of the principal morphological characteristics of North Pacific pandalid shrimp larvae. Fish. Bull. 77:625-640. Haynes, E. 1985. Morphological development, identification, and biol- ogy of larvae of Pandalidae, Hippolytidae and Crangoni- dae (Crustacea: Decapoda) of the northern North Pacific Ocean. Fish. Bull. 83:253-288. Holthuis, L. B. 1980. Shrimps and prawns of the world, an annotated catalogue of species of interest to fisheries. FAO species Catalogue. FAO Fish. Syn. 125, FIR/S 125 Vol.1, 271 p. Jensen, G. C. 1998. A new species of the genus Pandalopsis (Decapoda: Caridea: Pandalidae) from the Eastern Pacific, with notes on its natural history. Species Diversity 3:81-88. Komai. T. 1994. Deep-sea shrimps of the genus Pandalopsis (Decap- oda: Caridea: Pandalidae) from the Pacific Coast of eastern Hokkaido, Japan with the description of two new species. J. Crust. Biol. 14:538-559. Komai, T, and T. Mizushima. 1993. Advanced larval development of Pandalopsis japonica 126 Fishery Bulletin 102(1) Balss, 1914 (Decapoda: Caridea: Pandalidae) reared in the Laboratory. Crustaceana 64:24-39. Kurata, H. 1964. Larvae of deacapod Crustacea of Hokkaido. 3. Pandalidae. Bull. Hokkaido Reg. Fish. Res. Lab. 28:23- 34. Orensanz, J. M., J. Armstrong, D. Armstrong, and R. Hilborn. 1998. Crustacean resources are vulnerable to serial deple- tion — the multifaceted decline of crab and shrimp fisheries in the greater Gulf of Alaska. Rev. Fish Biol. Fisheries 8: 117-176. Pike, R. B„ and D. I. Williamson. 1964. The larvae of some species of Pandalidae (Decapoda). Crustaceana 6:265-284. PICES. 2001. Commercially important crabs, shrimps and lobsters of the North Pacific Ocean. PICES Scientific Report 19. 79 p. North Pacific Marine Science Organization, Sidney, B.C., Canada PSMFC (Pacific States Marine Fisheries Commission). 1999. 52 nd annual report of the Pacific States Marine Fish- eries Commission (A. J. Didier. ed.l, 37 p. Pacific States Marine Fisheries Commission, Gladston, OR. Rothlisberg, P. C. 1980. A complete larval description of Pandalus jordani Rathbun (Decapoda, Pandalidae i and its relation to other members of the genus Pandalus. Crustaceana 38:19-48. Schmitt, W. L. 1921. The marine decapod Crustacea of California with special reference to the decapod Crustacea collected by the United States Bureau of Fisheries Steamer "Albatross" in connection with the biological survey of San Francisco bay during the years 1912-1913. LTniv. California, Publ. Zool., vol. 23, 470 p. Thatje, S., and R. Bacardit. 2000. Larval development of Austropandalus grayi (Cun- ningham, 1871) (Decapoda. Caridea. Pandalidae) from the southwestern Atlantic Ocean. Crustaceana 73:609-628. 127 Abstract— This study was undertaken to resolve problems in age determina- tion of sablefish (Anoplopoma fimbria). Aging of this species has been ham- pered by poor agreement (averaging less than 45%) among age readers and by differences in assigned ages of as much as 15 years. Otoliths from fish that had been injected with oxytetracycline (OTC) and that had been at liberty for known durations were used to determine why age determinations were so difficult and to help determine the correct aging procedure. All fish were sampled from Oregon southwards, which represents the southern part of their range. The otoliths were examined with the aid of image processing. Some fish showed little or no growth on the otolith after eight months at liberty, whereas otoliths from other fish grew substantially. Some fish lay down two prominent hyaline zones within a single year, one in the summer and one in the winter. We classified the otoliths by morphological type and found that certain types are more likely to lay down multiple hyaline zones and other types are likely to lay down little or no zones. This finding suggests that some improvement could be achieved by detailed knowledge of the growth char- acteristics of the different types. This study suggests that it may not be possible to obtain reliable ages from sablefish otoliths. At the very least, more studies will be required to under- stand the growth of sablefish otoliths. Sources of age determination errors for sablefish (Anoplopoma fimbria)* Donald E. Pearson Santa Cruz Laboratory National Marine Fisheries Service 1 10 Shaffer Road Santa Cruz, California 95060 E-mail address Don Pearsom&Noaa Gov Franklin R. Shaw Alaska Fisheries Science Center National Marine Fisheries Service 7600 Sand Point Way NE Seattle, Washington 98118 Manuscript approved for publication 14 July 2003 by Scientific Editor. Manuscript received 20 October 2003 at NMFS Scientific Publications Office. Fish Bull. 102:127-141 (2004). Sablefish (Anoplopoma fimbria) are a valuable groundfish resource off the west coast of North America. The fish- ery in California, Oregon, and Wash- ington is tightly regulated according to periodic stock assessments. Between 1990 and 1998 landings averaged more than 8000 metric tons per year and an average exvessel (retail) value of 12.5 million dollars per year (PFMC, 1999). Sablefish are distributed in the northeastern Pacific Ocean from Baja California to the Bering Sea and southeast to northern Japan (Miller and Lea, 1972). Males and females are sexually mature between 55 and 67 cm, although there is considerable variation (Fujiwara and Hankin 1988a; Hunter et al, 1989). Off Washington, Oregon, and California, sablefish spawn from Octo- ber through April and spawning peaks in January and February. Sablefish are oviparous, releasing eggs that float near the surface (Hunter et al., 1989). After hatching, larvae and juveniles in- habit surface waters offshore for several years after which they migrate inshore and settle to the bottom. Sablefish are found on the continen- tal slope and are commercially fished at depths from 200 to 1400 meters (Leet et al., 1992). Adult sablefish feed on fish, cephalopods, and crustaceans (Laidig et al., 1998). They reach a maximum length of 102 cm (Miller and Lea, 1972) and are believed to be a very long-lived species (possibly 100 years or more). Many physical features have been used to age this species, including scales, finrays, thin-sectioned otoliths, and broken and burned otoliths, but all methods have resulted in less than 45% agreement among readers (Lai, 1985; Fujiwara and Hankin 1988b; Kimura and Lyons, 1991; Heifetz et al. 1999). The broken and burned otolith method (Chilton and Beamish. 1982) is the principal method used in aging of the species in both the United States and Canada. Typically, age readers agree on ages less than 50% of the time, and for fish older than 7 years, agreement drops to less than 15% (Kimura and Lyons. 1991). There have been repeated efforts at validating sablefish ages and develop- ing aging criteria. Beamish et al. ( 1983) successfully used oxytetracycline (OTC ) marking to validate ages and repeated his experiment in 1995 when additional marked fish were recovered (MacFar- lane and Beamish, 1995). Lai (1985) validated the use of otoliths for aging sablefish. Fujiwara and Hankin ( 1988b) examined otolith growth characteristics to help refine aging criteria. Heifetz et al. (1999) validated the currently ac- cepted aging practices and examined sources of error in the aging of sablefish. Kastelle et al. (1994) used radiometric methods to generally validate the aging criteria currently used. Even with all of these studies that have validated age * Contribution 119 from the Santa Cruz La- boratory, National Marine Fisheries Ser- vice, Santa Cruz, CA 95060. 128 Fishery Bulletin 102(1) ?8W 126"W 124°W 122 W 120W 118"W 116°W Figure 1 Map of California and southern Oregon showing the locations ( black dots ) of sablefish sampling and tagging in September and October of 1991. determinations, independent age readings seldom are in agreement. This suggests that the methods used to validate the ages were insufficient to allow development of precise aging criteria. The lack of reliable age data has made stock assessments difficult and controversial (Crone et al., 1997 ). and in addition, accurate aging is needed to support eco- logical and habitat studies. In September and October of 1991, a tagging and oxytet- racycline (OTC) injection study was included as part of a fish trap survey of the abundance of sablefish in southern Oregon and California. The purpose of this study was to attempt, once more, to improve our ability to reliably age sablefish, thereby improving our ability to manage the species. Methods trarily selected fish at each station, and the rest of the fish were tagged with blue spaghetti tags. Three of every four tagged fish were injected intraperitoneally with 30 mg of OTC per kilogram offish (Beamish et al., 1983) and the fourth fish was used as a control. A complete description of the survey can be found in Parks and Shaw ( 1994 ). A scientist visited the major commercial fishing ports in California and southern Oregon to make port samplers, commercial dealers, and fishermen aware of the impor- tance of the study and to explain handling procedures in the study. A $50.00 reward was offered for the return of whole tagged fish. When a tagged fish was returned, the port sampler measured it (fork length in mm), determined the sex, and removed the otoliths. The otoliths were cleaned and stored in painted glass vials (because the OTC mark was light labile) with a 5095 ethanol solution. Capture, tagging, injection, and recovery In September 1991, the fisheries research vessel Alaska was chartered by the National Marine Fisheries Service to conduct a trap survey from Coos Bay, Oregon, to Cortez Bank, California (Fig. 1). A total of nine sites were visited. At each site seven strings of ten traps were deployed in various depths between 250 and 1900 meters. The traps were retrieved after 24 hours, the catch was removed, and the traps reset for an additional 24 hours. All the sablefish were counted, otoliths were removed from the first 20 arbi- Processing of the otoliths Two pairs of otoliths were initially selected to develop the procedures to be used in the study. It was found that the OTC mark was very faint and upon heating (as required by conventional age determination methods), the mark disappeared. Accordingly, we developed a method to obtain images of the otoliths before and after heating, and to superimpose the two images of the same otolith; the first viewed under UV light and, the second, after heating, under white light. Pearson and Shaw: Age determination errors for Anoplopomo fimbria 129 OTC Mark Alignment point Alignment point Pasted UV Image Figure 2 Composite image of a sablefish otolith. The otolith was first viewed under UV light and an image was captured. It was then baked and a second image was captured by using white light. Then a small rectangle from the UV image was electronically cut and pasted on the image of the baked otolith. The fiourescent mark produced by the OTC appears as a dark line on the UV section. Points on the otolith used for correct positioning of the pasted section are shown. The otoliths were embedded in epoxy casting resin. After the resin hardened, the blocks containing the otoliths were sliced in half across the dorsoventral axis with a diamond saw. Images were captured in a two-stage process. The first stage used ultraviolet light to reveal the OTC mark, and the second stage used white light to reveal the growth marks used for age determination. In the first stage, the room was completely darkened and an image of the otolith, including the OTC mark, was captured by using a video camera capa- ble of capturing images under low light conditions. We used an ultraviolet lamp which produced a strong beam of light at 365 angstroms. The otolith was viewed on a compound microscope using reflected light. The camera and image pro- cessing system were connected to a PC computer equipped with a frame grabber card. A version of NIH Image, a pub- lic domain image processing software (Scion Corporation, Frederick, MD), was used to process the images. The embedded otolith was placed on the microscope and a drop of mineral oil was placed on the surface of the oto- lith. The limited amount of UV light available to the cam- era required the use of frame averaging. Usually 30 frames were sufficient to produce a sharp view of the otolith and the fluorescing mark. In some cases, the mark was too faint to allow an image to be captured. When there was sufficient fluorescence, two composite images were captured, one at 4x and one at 40x. In the second stage, the same embedded otolith was placed in a small toaster oven at 270°C and heated for 20 to 25 minutes until it had turned dark brown. This baking process enhanced the growth rings for visual analysis and approximated what age readers see using the break and burn method; however, the latter process results in darker hyaline zones than those obtained with this method. After cooling, the otolith was viewed under white light. A second set of images was then captured. A section of each UV im- age was then electronically cut and pasted onto the image captured under visible light. With some experimentation it was found that the pasted sections could be aligned exactly over the visible light images, creating a final composite im- age as shown in Figure 2. Initial examination of the otoliths Initially, all OTC-marked otoliths were examined with knowledge of the year and season of release, but without any other information about the fish. Composite UV and white light images were obtained as previously described. The age reader determined the following: whether or not the OTC mark was visible; whether the OTC mark was in a hyaline or opaque zone; the number of annual hyaline zones visible beyond the OTC mark (and whether or not the edge was included in the count); edge type (hyaline, narrow opaque, wide opaque, or unidentifiable), and the shape of the otolith. In some cases the OTC mark could not be identified or the mark was too faint to be captured as a composite image; these specimens were excluded from subsequent analyses. 130 Fishery Bulletin 102(1) : v. ; - ■*■-■ count from here Figure 3 Example of an image of a baked sablefish otolith which has been annotated with a mark. The image is an example of one of the images provided to three researchers in order to obtain cross-reading comparisons. Following standard age determination procedures (Chil- ton and Beamish. 1982), if a hyaline zone was not visible on the edge between January and March, then the edge was counted. If a mark was not visible on the edge between April and May and there was a wide opaque zone, then the edge was counted as a mark. If a mark was visible on the edge and the month was after May, the edge was not count- ed. This procedure is used to properly assign the fish to an annual cohort. Because the reader was not given the month of recapture, the ages were adjusted based on the count of hyaline zones, the month of recapture, and whether the edge had been counted. This adjustment provided a cor- rected reader count of annual marks. The corrected count was compared to the number of annual marks that would have been present if marks were laid down annually. Previous experience suggested that there are differ- ent patterns of sablefish otolith growth. We attempted to classify and characterize these different types of growth patterns based on morphology of the otoliths as seen in cross section. After the otoliths had been examined, we developed a standard classification scheme of morphologi- cal classes and types which could be used to classify the most commonly observed morphological types. The otoliths were re-examined and reclassified to see if difficulties and discrepancies in aging were associated with morphological type. It was hoped that this process could be used to refine the aging criteria and improve precision. Because sample size was small, we used a Fisher exact test (Agresti, 1990) to test for independence of morphological type versus tendency to over-estimate, correctly estimate, or under-estimate the number of annual marks. The columns in the test indicated whether the fish had been over-aged. correctly aged, or under-aged. The rows in the test were the four morphological types identified in this study. Examination of the otoliths by the age readers To determine how age readers would count the marks on the otoliths, we selected a subsample of 25 otoliths to be aged at four West Coast fisheries laboratories. The otolith selection was based on having good quality images and otoliths. The images of the baked otoliths (not the compos- ite images ) were annotated with a mark ( Fig. 3 ). The mark was placed in a location which could be readily located on the actual otolith by the readers — on the zone just inside of the OTC mark. Readers were given the following: a set of printed images, an electronic file of the images for viewing on a computer screen, the embedded otolith, the month of capture, the size and sex of the fish from which the otolith came, and a set of instructions for examining the otoliths. Readers were not told where the mark on the image was placed in relation to where the OTC mark was in order to reduce bias from readers who may have known when the fish were injected and recaptured. Readers were asked to provide the following: the number of annual marks vis- ible outside the mark on the image, whether the edge was counted, how confident they were of their readings, and any comments they might have. Three readers participated in this analysis, two of whom had extensive, long-term experience in aging sablefish. The readings and age determination criteria (including edge count criteria) were compared to each other and to the time known to have passed between OTC marking and recapture. Pearson and Shaw: Age determination errors for Anop/opoma fimbria 131 Figure 4 Images of four otolith morphological types. (A) Otolith is a wide type, (B ) otolith is a wide, wedge subtype. (C) otolith is a thick type, and (D) otolith is a thick, wedge subtype. To determine if age determination difficulties were relat- ed to sex, size, area of capture, depth of capture, or otolith morphological type; Fisher exact tests were performed. In each test, the variables were compared to whether the fish had been correctly aged, over aged, or under aged. Results Recoveries A total of 2575 fish were tagged at the nine sites, and 368 tagged fish were recaptured. Of the recaptured fish, 284 had been injected with OTC. Of the 284 injected fish, usable otoliths were recovered from 191 fish; for the remaining fish, otoliths either were not recovered or were too badly damaged during removal to be used. Otolith morphological types After examination of all the otoliths, "wide" and "thick" morphological types were identified, and each type had a "wedge" subtype ( Fig. 4 ). Each otolith in the study was then classified according to this scheme. The wide type (Fig. 4A) is characterized by new growth that steadily increases cross sectional width along the dorsal and ventral surfaces. In the wedge subtype (Fig. 4B), initial growth increases the width, but the most 132 Fishery Bulletin 102(1) recent growth is concentrated on the medial or lateral surface at the sulcus, decreasing towards the dorsal and ventral surfaces, resulting in a wedgelike appearance. The thick type (Fig. 4C) is characterized by new growth that increases the thickness of the otolith without increas- ing the cross sectional width, causing the annulii to appear closely spaced on the lateral surfaces. In the wedge subtype (Fig. 4D), the most recent growth is concentrated at the sul- cus and narrows towards the dorsal and ventral surfaces, forming a wedge shape. It should be noted that these types and subtypes are not always clearly defined. It should also be noted that clas- sification to the subtype is based on the most recent one or more hyaline zones. A wedge subtype is formed when a single hyaline zone widens near the sulcus and comes to a point at the outer edge. Of the 191 otoliths examined, 63 (33.0%) were classified as "wide" types, 76 (39.7% ) were classified as "wide, wedge subtypes," 32 (16.8%) were classified as "thick" types, 5 (2.6%) were classified as "thick, wedge subtypes,' and 15 i 7.99? ), could not be classified by this scheme. Position of the OTC mark There was no detectable OTC mark in 22 of 191 otoliths. The absence of marks appeared to be a random event, occurring in otoliths from several different recovery years and equally likely to be found among different sexes, otolith types, different depths, and locations. Of the 169 otoliths with detectable marks, the OTC mark was found in a hyaline zone in 129 otoliths (76.3%), in an opaque zone in 36 otoliths (21.3%), and could not be reli- Pearson and Shaw: Age determination errors for Anoplopoma fimbria 133 Table 1 Frequency of otoliths with an OTC mark appearing on the edge versus those with the marks inside the edge. All fish were injected between September and October of 1991. Mark Mark Year Month on edge not on edge 1991 Oct 2 1 Nov 1 3 Dec 4 2 1992 Jan 2 4 Feb 1 6 Mar 7 4 Apr 3 1 May 7 26 Jun 2 Jul 1 7 Aug 1 4 Sep 1 2 Oct 5 Nov 3 Dec ably determined in four otoliths (2A c /c) because the marks were between a hyaline and opaque zone. Of the .36 otoliths with the mark in an opaque zone, the mark occurred just after a hyaline zone in four otoliths. In 24 of the 36 otoliths with the mark in an opaque zone, the mark was on the edge where it can be difficult to determine whether it is opaque or hyaline. In no case did the reader indicate that the mark was in a hyaline zone at the edge and thus the edge appeared to be opaque in most cases. The OTC mark occurred on the otolith edge in 30 of the otoliths recaptured prior to 1993 (up to 16 months after injection). Examination of the monthly distribution of oto- liths with marks on the edge ( Table 1 ) indicated that some fish exhibited little or no otolith growth for substantial lengths of time. Otoliths from fish recaptured in 1992 with marks on the edge (i.e. showing little growth) were examined and classi- fied by morphological type (Table 2). This examination indi- cated that the thick type is more likely to have little growth Table 3 Number of visible hyaline zones occurring after an OTC mark on otoliths from fish recaptured in 1992. This is shown by three-month interval to show the progression of development of the hyaline zones. All fish were injected in September and October of 1991. Interval No. of hyaline zones 1 2 Jan-Mar 12 8 1 Apr-Jun Jul-Sep Oct-Dec 5 14 4 6 2 3 1 because 32"* of the otoliths with marks on the edge were the thick type, yet they made up only Y1 C A of the otoliths in the study. Conversely, only 18% of the otoliths with the mark on the edge were of the wide type; however, they made up 33^ of the otoliths in the study. This trend was not statistically significant, however, because the P-value was 0.106. Number of visible hyaline zones The number of prominent hyaline zones after the OTC mark for fish recaptured in 1992 at three-month intervals is shown in Table 3. This distribution shows the otoliths that had no detectable growth but also shows that a hya- line zone forms in many fish during the winter. It also shows that in some fish, a summer hyaline zone is formed; however, the sample size for October-December was small and this is a period when a summer hyaline zone would be expected to be fully visible. The number of visible and prominent hyaline zones after the OTC mark for fish recaptured after 1992 (Table 4), com- pared with the number of zones which should have been counted, showed that if a reader had counted each of the prominent hyaline zones as an annulus, the count would have overestimated the age of the fish. An example of an otolith with a larger number of prominent hyaline zones than expected is shown in Figure 5. It should be noted that a reader would not necessarily have counted each of the Table 2 Number of otoliths in 1992 with OTC marks on the edge by otolith morphological type. Also shown is morphological types in the present study. All fish were injected in September and October 1991. the overall percentage of the Otolith type Wide Wide, wedge Thick Thick, wedge No. Percent No. Percent No. Percent No. Percent 1992 otoliths 4 Otoliths in this study 63 18 10 45 7 33 76 40 32 32 17 1 5 5 3 134 Fishery Bulletin 102(1) Figure 5 Image of a sablefish otolith having more prominent hyaline zones than should have been present. The fish was caught after eight months at liberty. A single hyaline zone should have formed; however, there is a zone on the edge and one midway between the dark OTC mark. Table 4 Counts of the number of prominent hyaline zones versus the number of annual hyaline zones that should have been present after an OTC mark. These counts are for fish recaptured more than 15 months after initial capture. Agreement between counts and number of expected annual hyaline zones is shown in bold. Year Expected number 1993 1994 1995 1996 1997 No. of prominent hyaline zones 10 3 1 3 1 5 1 2 1 1 1 2 1 1 2 Table 5 Percent and number (in parentheses I of sablefish otoliths with more hyaline zones than were expected, with the expected number of hyaline zones (correct count), and with fewer hyaline zones than were expected for each otolith type. Otolith type More zones Expected number of zones Fewer zones Thick 10.3% (3) 41.4%(12) 48.3% ( 14 1 Thick, wedge (0) 40.09! (2) 60.09! (3) Wide 39.39! (22) 48.29! (27) 12.5% (7) Wide, wedge 35.29! (25) 45.19! (32) 19.79! (14) prominent hyaline zones as an annulus (they might have considered them to be checks). In many of these otoliths, there were less prominent zones that were not counted and which were interpreted as checks. Thick type otoliths and thick, wedge subtype otoliths tend to have fewer visible hyaline zones than expected (Table 5). In contrast, wide type and the wide, wedge sub- type otoliths are more likely to have more hyaline zones than expected. The Fisher exact test yielded a significant P-value of 0.001. Blind comparisons of reader counts A comparison of the counts of annual hyaline zones for each reader to the expected number of annual hyaline zones Pearson and Shaw: Age determination errors for Anoplopoma fimbria 135 Table 6 Comparison of number of annual hyaline zones by reader 1 versus the expected number of annua zones that should have been counted. Agreement expected counts are shown in bold. counted hyaline with the Expected count Reade • 1 count 1 2 3 4 5 6 7 1 2 7 2 1 2 2 4 1 1 3 1 1 4 2 5 1 Table 8 Comparison of number of annual hyaline zones counted by reader 3 versus the expected number of annual hyaline zones which should have been counted. Agreement with the expected counts are shown in bold. Reader 3 count Expected count 1 2 3 4 5 6 7 1 10 2 2 2 1 3 1 1 4 2 5 1 3 1 1 Table 7 Comparison of number of annual hyaline zones counted by reader 2 versus the expected number of annual hyaline zones that should have been counted. Agreement with the expected counts are shown in bold. Reader 2 count Expected count 12 3 4 5 6 7 1 5 2 3 1 2 3 2 2 3 1 1 4 5 1 1 1 1 1 after the OTC mark are shown in Tables 6, 7, and 8. In these tables, it is assumed that the readers should not have counted the zone in which the OTC mark occurred because that mark is presumed to have formed in the summer of 1991. Readers 1 and 2 tended to overestimate, whereas reader 3 (the least experienced age reader) had generally good agreement. Reader 1 agreed with the expected count 24% of the time, reader 2 agreed with the expected count 4% of the time, and reader 3 agreed with the expected count 44% of the time. The result for reader 3 is deceptive, how- ever, because that reader did not follow accepted methods of when to count the edge. Reader 1 and reader 2 agreed on whether to count the edge of the otolith in 24 of 25 otoliths (Table 9). Reader 3 agreed with reader 1 on whether to count the edge in 16 of 25 otoliths and 17 of 25 otoliths with reader 2. Had reader 3 followed accepted practice, agreement with the expected count would have been much less. Efforts to determine what factors (depth of capture, loca- tion of capture, sex, size of the fish, and otolith morphologi- cal type) resulted in a miscount of the true number of an- nual marks were inconclusive. We first corrected the count for the fact that all readers counted the mark in which the OTC mark had occurred by subtracting one from their counts, and we then eliminated the readings from reader 3 because of his lack of experience and anomalous age de- termination criteria. Then we examined the relationship of how many otoliths had been over-aged, correctly aged, and under-aged to the above factors. Depth of capture was divided into two groups: less than 600 m and 600 or more m. Location was divided into two groups: north and south of latitude 39 north. Sizes were divided into two groups: <55 cm FL and ;>55 cm FL. And finally, we tested each of the four otolith morphological types. We used Fisher exact tests to determine the probability that differences were due to chance alone. There were no detectable differences from the null hypothesis for depth, sex, or location of capture (Table 10); however, there was some evidence that fish length and otolith morphological type might be related to miscounting. Small fish showed a slightly greater tendency to be over counted (more rings than should have been present) than larger fish (P=0.150). Otolith morphological type showed some departure from randomness: thick types appeared to be more likely to be undercounted (fewer rings than should have been pres- ent) and wide types were more likely to be over counted (P=0.066). Discussion Position of mark There was no visible mark on 22 of the 191 otoliths ( 11.5%). Beamish et al. ( 1983 ) reported that 14 of 129 OTC-injected fish ( 10.9%) had no detectable mark. They attributed this to improper handling of the fish after recapture. The similar- ity in the number of otoliths failing to show the OTC mark between their study and our study suggests that some portion of the population may not absorb sufficient OTC to produce a visible mark. The finding that most of the OTC marks were in a hyaline zone is important. This indicates that many of the sablefish in our study laid down a prominent hyaline zone in the summer. Age readers who conventionally as- sume that an annual mark is laid down only in the winter 136 Fishery Bulletin 102(1) Table 9 Blind reading results of 25 s ablefish otoliths by 3 readers. All fish had been captured and injected with OTC in September and Octo- ber of 1991. The counts thev providec are the number of annual marks outside of the OTC mark "Expected count" indicate s how many winter hya ine zones should have been present. The columns labeled "Edge' refer to whether or not the edge was included in the age reader' s counts. Fish ID no. Recapture date Expected count Reader 1 Reader 2 Reader 3 Count Edge Count Edge Count Edge 10375 4 May 92 1 2 Y 2 Y N 10030 14 May 92 1 1 Y 2 Y N 10267 17 May 92 1 2 Y 3 Y N 10408 17 May 92 1 2 Y 2 Y Y 10417 18 May 92 1 2 Y 3 Y N 10630 25 May 92 1 4 Y 4 Y N 12148 26 May 92 1 3 Y 4 Y N 12176 26 May 92 1 2 Y 5 Y N 12431 26 May 92 1 2 Y 2 Y Y 10568 29 Jul 92 1 1 N 2 N N 11121 lOct 92 1 2 N 6 N N 11117 16 Oct 92 1 3 N 4 N N 10400 12 Jan 93 2 3 Y 5 Y 3 Y 10370 14 Jan 93 2 4 Y 4 Y 3 Y 10870 15 Feb 93 2 2 Y 7 Y 5 Y 10246 15 Apr 93 2 3 N 3 Y 3 Y 11735 16 May 93 2 3 Y 3 Y 2 Y 11586 18 May 93 2 2 Y 4 Y 4 Y 11106 3 Aug 93 2 3 N 3 N 1 N 10617 2 Dec 93 2 5 N 5 N 1 N 10580 23 Mav 94 3 2 Y 4 Y 2 Y 10714 9 Dec 94 3 5 N 3 N 1 N 11516 3 Aug 95 4 4 N 7 N 1 N 11524 16 Dec 95 4 4 N 6 N 1 N 11761 25 Apr 96 5 3 Y 5 Y 3 N Table 10 Comparison of the lumber offish under counted. correctly counted, and over counted by two experienced age readers versus depth of capture, location ( north or south of 39 degrees latitude), sex, fork length and otolith moi •phological type. The P-value from the Fisher exact test is shown indicating the level of significance. LInder counted Correctly counted Over counted P Depth <600 meters 7 14 15 0.987 >600 meters 3 6 5 Location South 4 8 10 0.606 North 3 12 7 Sex Male 3 2 5 0.381 Female 7 18 15 Length <55 cm 4 1 1 15 0.150 255 cm 6 6 5 Otolith type Thick 4 2 2 0.066 Thick, wedge 1 1 Wide 2 5 11 Wide, wedge 3 12 7 Pearson and Shaw: Age determination errors for Anop/opoma fimbria 137 Figure 6 Image of a baked sablefish otolith with an electronically pasted section taken from an image captured under UV light. The dark OTC mark is clearly located within a hyaline zone, and the hyaline zone persists through the entire otolith. The fish was injected with OTC on 5 October 1991. would probably mis-age these fish. Because the age read- ers who examined the otoliths without knowledge of the recapture information were not informed that the point they were counting from was just inside the summer mark, it was interesting to note that all three of them counted the hyaline zone in which the OTC mark had occurred as an annual hyaline zone in all cases. In other words, the summer hyaline zone did not appear to be a check to the readers. The readers indicated that the manner of prepa- ration of the otoliths (embedded and baked) was not the manner in which they were accustomed to view otoliths and may have influenced their results. The fact that the hyaline zones were not as dark with the baking method as opposed to the burning method may have influenced the readers age estimates; however, some otolith burns can be quite light and experienced readers recognize the various levels of burning, particularly when cross reading otoliths from other age readers. Readers sometimes use multiple sections and are free to manipulate the otolith to improve viewing, which was not possible in the present study. Beamish et al. (1983) indicated that when readers knew how many marks to look for, they were able to iden- tify false annual marks (checks). According to their study, a check is not persistent throughout the otolith. In Figure 6, the hyaline zone in which the OTC mark appeared clearly persists throughout the otolith. If the hyaline zone which contained the OTC mark began to be laid down in the win- ter, then there would be very little time for the formation of a wide opaque zone to form after injection in the fall. Because the age readers counted the hyaline zone in which the OTC mark occurred, they clearly assumed that it was not a check. If the age readers had known that the hyaline zone (in which the OTC mark occurred) had formed in the summer, then they presumably would not have counted it. It is therefore of interest to see the effect on agreement between reader counts minus the hyaline zone where the OTC mark occurred and the actual number of hyaline zones that should have been present. When we adjusted the reader counts by subtracting one year from their original counts and compared their adjusted counts to the expected number of annual marks (Table 11 ), agreement for readers 1 and 2 improved, whereas it decreased for reader 3 (the least experienced reader). Also of importance is the fact that on some otoliths, even after eight months at liberty, no growth had occurred, as evidenced by the fact that the OTC mark was on the edge. For example, otoliths from two fish, recaptured after eight months at liberty showed marked differences in otolith growth ( Fig. 7 ). On otolith A there was no detectable growth with the OTC mark on the edge, whereas on otolith B there was substantial growth. The OTC marks on both otoliths were very prominent. These otoliths came from similar fish; that is, otolith A came from a 597-mm female fish caught in 680 meters of water at 40°52' latitude, and otolith B came from a 610-mm female fish caught in 480 meters of water at 41°54' latitude. This provides strong evidence that otolith growth, and presumably fish growth, varies greatly among individual sablefish. Beamish et al. (1983) reported that the OTC mark was on or near the edge in 28 otoliths (18.1%) of 154 fish which had been at liberty for two to three years. In a similar time interval, we found that 34 of 126 (27.0%) had the OTC marks on or near the edge. Both the finding of a summer hyaline zone and the differences in growth of the otolith among individual fish 138 Fishery Bulletin 102(1) Figure 7 Images of otoliths from two sablefish showing differences in otolith growth rate. Both fish were injected with OTC in early October of 1991 and were recaptured in May of 1992. (Al Otolith was from a 597-mm female caught in 680 meters of water at 40°52' latitude. iBl Otolith was from a 610-mm female fish caught in 480 meters of water at 41°52' latitude. The OTC mark in A was on the edge, whereas the position of the OTC mark in B is shown on the insert. are important factors in developing reliable and consistent age determination criteria. The importance of using the same age determination criteria among readers cannot be overestimated. In the blind comparison, the readers were asked whether they had included the edge in their count of annual zones. With standard age determination methods, if no hyaline mate- rial is visible on the edge up to about May, then the edge is counted. This procedure is based on the assumption that a zone is in the process of forming but is not yet clearly vis- ible. On the other hand, if hyaline material is observed on the edge after May, it is not counted because it is assumed to be either a check or the beginning of the next winter's hyaline zone. Reader 1 and reader 2 (the two most expe- rienced age readers) agreed on whether to count the edge 96% of the time, indicating that they were using the same criteria. Reader 3, however, agreed with reader 1 only 64% of the time and with reader 2 only 68% of the time which suggests that reader 3 was using different edge-interpreta- tion criteria. Pearson and Shaw: Age determination errors for Anoplopoma fimbria 139 Table 11 Percent agreement between number of hyaline zones counted by three age readers and the number which should have been pres- ent. Also shown is the effect of removing the count of a hyaline zone which formed in the summer and which should not have been counted as an annual mark. Reader 1 Reader 2 Reader 3 Original Corrected Original Corrected Original Corrected 24% 44% 36% 44% 20% Effect of ages on stock assessments Crone et al. (1997) noted that one of the problems with stock assessments of sablefish is that the size at 50% sexual maturity is between 55 and 67 cm ( age 5-7 ) and that there is considerable variability in the these estimates. Further, they noted that there has been difficulty in determining age-specific selectivity because of problems with the ages used in previous assessments. Crone et al. (1997) further noted that there is a considerable discrepancy in ages among the age determination laboratories on the west coast. Finally, the model used to perform stock assessments has estimated that in order to obtain a good fit with the data, the actual level of aging error should be higher than has been reported. The lack of reliable age data has been used to criticize stock assessments. Age and length at sexual maturity has been found to vary substantially by depth (Fujiwara and Hankin, 1988a). Fujiwara and Hankin found that both males and females had a length of 550 mm for the length at 50% sexual matu- rity in shallow water (<600 meters ). In depths greater than 600 m, the size at 50% sexual maturity was 450 mm for males and 500 mm for females. To determine age, they used sectioned otoliths and methods that may not have been directly comparable to the methods used in other studies or the methods used in the present study; nonetheless, they found that both males and females matured at a younger age in deeper water. Saunders et al. (1997) also reported differences in length at maturity related to depth and loca- tion of capture. Methot 1 found that ontogenetic movement into deeper water for spawning was more closely related to age than size. If sexual maturity is more closely related to age than length as suggested by Methot, then unreliable ages may explain the variable maturity schedule for sable- fish. In our study, fish were captured over a 900 nmi range at depths from 200 to more than 1000 m. If depth is related to growth of sablefish, then it is possible that the different morphometric types of otoliths observed in our study may also be a function of depth. If depth is responsible for the morphological types, it also suggests that reliability of ages may be a function of the depth at which the sablefish are found. Further, if depth influences growth, a fish which 1 Methot. R. D. 1995. Geographic patterns in growth and maturity of female sablefish off the U.S. west coast. Unpubl. manuscript, 39 p. NOAA, NMFS, Northwest Fisheries Science Center, Seattle, WA. changes its depth over time, may exhibit different patterns of growth throughout its life which would further compli- cate the problem of determining reliable ages. Potential sources of error in this study This study used sablefish caught in the southern part of the sablefish range. Many species show latitudinal varia- tion in growth (June and Reintjes, 1959; White and Chit- tenden, 1977; Leggett and Carscadden, 1978; Shepherd and Grimes, 1983; Pearson and Hightower, 1991). It is possible that the results of this study do not apply to the northern portion of their range. Another potential source of error in our study is the effect of tagging on the growth of the sablefish. MacFarlane and Beamish ( 1990 ) found that tagged sablefish grew slower than untagged fish. If this is true, then the results of this study are much more difficult to interpret. MacFarlane and Beamish did not use OTC and as a result they based their ages on conventional aging methods. If they had injected the fish, it would have been interesting to note whether the ages for the fish in their study would have been inter- preted differently. If fish do grow differently after tagging, many age, growth, and validation studies will need to be re-evaluated. Conclusion Obtaining accurate ages, with reasonable precision, for sablefish is very difficult. Previous aging studies of sable- fish have obtained results similar to ours, even when the readers knew how many annual marks should have been present (Beamish et al. 1983; MacFarlane and Beamish, 1995). We found that some fish lay down two marks a year and others may not lay down any. We also found that certain morphological types of otoliths may be indicative of slow growing fish and others may be indicative of rapidly grow- ing fish (assuming otolith growth relates to fish growth). The fact that agreement among readers or with the cor- rect age consistently ranges between 30% and 45% sug- gests that this imprecision may be inherent in sablefish aging. A substantial fraction of the population may not be able to be reliably aged: some otoliths do not appear to grow and others grow very rapidly, laying down prominent summer hyaline zones that even experienced age readers cannot differentiate from winter hyaline zones. 140 Fishery Bulletin 102(1) We believe the wide type and wide, wedge subtypes are often over-aged, and the thick type and thick, wedge sub- types are occasionally under-aged and further propose that readers be made aware that a hyaline zone typically forms in the winter, but that it is not uncommon for a second mark to form in the summer. Another, less desirable approach, would be for age read- ers to record the morphological type of otolith as a routine part of aging. Users of the data could then incorporate this information into their studies by using a correction factor for fish likely to be under-aged and for fish likely to be over-aged. This factor could be in the form of an aging error matrix as suggested by Heifetz et al. ( 1999 ). This approach may not be practical until more data are available on the true effect on ages for the morphological types described in this study, including how many years would need to be added or subtracted for each type. Finally, a more complete description of the morphological types would be needed to assist the age readers. Acknowledgments We would like to express our gratitude to Delsa Anderl (Alaska Fisheries Science Center), Kristin Munk (Alaska Department of Fish and Game), Shayne MacLellan (Pacific Biological Station, Canadian Department of Fisheries and Oceans), and Bruce Pederson (Oregon Department of Fish and Wildlife) for participating in the otolith blind reading component of this paper. We would also like to thank Dan Kimura and Craig Kastelle of the Alaska Fisheries Science Center for their assistance in developing the design of this study. We would like to thank Michael Mohr (Southwest Fisheries Science Center, Santa Cruz, CA) for his valuable contribution to the statistical analyses used in this study This study could not have been completed without the sup- port of Gary Stauffer (Alaska Fisheries Science Center) who provided funding for the recovery of the sablefish. Additionally, this study would never have been completed without the assistance of numerous commercial market samplers, port biologists, commercial fishermen, and deal- ers who were responsible for collecting and processing the sablefish when they were caught. And finally, we would like to thank William Lenarz (Southwest Fisheries Science Center, retired) for his support of this study. Literature cited Agresti, A. 1990. Categorical data analysis, 558 p. Wiley. New York. NY. Beamish. R. J.. G. A. 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Aging discrepancy related to asymmetrical otolith growth for sablefish Anoplopoma fimbria in northern California. Nippon Suisan Gakkaishi 54(1):27-31. Heifetz, J., D. Anderl, N. E. Maloney, and T. L. Rutecki. 1999. Age validation and analysis of aging error from marked and recaptured sablefish. Anoplopoma fimbria. Fish. Bull. 97:256-263. Hunter, J. R., B. J. Macewicz, and C. A. Kimbrell. 1989. Fecundity and other aspects of the reproduction of sablefish, Anoplopoma fimbria, in central California waters. CalCOFI Rep. 30, 1989, p. 61-72. June, F. C, and J. W. Reintjes. 1959. Age and size composition of the menhaden catch along the Atlantic coast of the United States, 1952-55: with a brief review of the commercial fishery. U.S. Fish and Wildl. Serv., Spec. Sci. Rep. Fish. 317, 65 p. Kastelle, C. R, D. K. Kimura, A. E. Nevissi, and D. R. Gunderson. 1994. Using Pb-210/Ra-226 disequilibria for sablefish. Ano- plopoma fimbria, age validation. Fish. Bull. 92:292-301. Kimura, D. K., and J. J. Lyons. 1991. Between-reader bias and variability in the age deter- mination process. Fish. Bull. 89:53-60. Lai, H. L. 1985. Evaluation and validation of age determination for sablefish. pollock and yellowfin sole; optimum sampling design using age-length key; and implications of aging variability in pollock. Ph.D. diss., 426 p. Univ. Washing- ton, Seattle, WA Laidig, T. E., P. B. Adams, and W M. Samiere. 1998. Feeding habits of sablefish, Anoplopoma fimbria, off the coast of Oregon and California. NOAA Tech. Rep NMFS 130:65-79. Leet, W. S., C. M. Dewees, and C. W. Haugen. 1992. California's living marine resources and their utiliza- tion. Calif. Seagrant Publication UCSGEP-92-12, 257 p. Univ. California Davis, Davis, CA. Leggett, W. C, and J. E. Carscadden. 1978. Latitudinal variation in reproductive characteristics of American shad (Alosa sapidissima): evidence for popu- lation specific life history strategies in fish. J. Fish. Res. Board Can. 35:1469-1478. Macfarlane, G. A., and R. J. Beamish. 1990. Effect of an external tag on growth of sablefish ffice. Fish. Bull. 102:142-155 (2004). Growth, mortality, and hatchdate distributions of larval and juvenile spotted seatrout {Cynoscion nebulosus) in Florida Bay, Everglades National Park Allyn B. Powell Robin T. Cheshire Elisabeth H. Laban National Ocean Service National Oceanic and Atmospheric Administration Center for Coastal Fisheries and Habitat Research 101 Pivers Island Road Beaufort, North Carolina 28516 E-mail address (for A. B Powell): allyn powellgnoaa gov James Colvocoresses Patrick O'Donnell Florida Fish and Wildlife Commission Florida Marine Research Institute 2796 Overseas Highway, Suite 119 Marathon, Florida 33050 Marie Davidian Room 209, Patterson Hall 2501 Founder's Drive North Carolina State University Raleigh, North Carolina 27695 The spotted seatrout (Cynoscion nebu- losus) is an important recreational fish in Florida Bay and spends its entire life history within Florida Bay I Rutherford et al.,1989). The biology of adult spotted seatrout in Florida Bay is well known (Rutherford et al., 1982, 1989), as are the distribution and abundance of juveniles in the bay, including a description of the juvenile habitats and their diets (Het- tler, 1989; Chester and Thayer, 1990; Thayer et al., 1999; Florida Department of Environmental Protection 1 ). The temporal and spatial distribution and abundance of larval spotted seatrout in Florida Bay and adjacent waters, and the spatial and temporal spawning habits of these larvae also have been determined (Powell et al., 1989; Rutherford et al.. 1989; Powell, 2003). The early life history of spotted seatrout in other south Florida estu- aries also has been well documented. Peebles and Tolley ( 1988) described the distribution, growth, and mortality of larval spotted seatrout in Naples and Fakahatchee Bays, and McMichael and Peters (1989) described the size distri- bution, growth, spawning, and diet of spotted seatrout in Tampa Bay. Information on growth and mortality of larval and juvenile spotted seatrout in Florida Bay is lacking. Research on these topics would enhance our under- standing of the entire life history of this valuable species, and in particular aid in eventually developing a spatially ex- plicit model for spotted seatrout that is highly desired by the Program Manage- ment Committee for the South Florida Ecosystem Restoration Prediction and Modeling Program. In addition, these life history studies could help clarify ju- venile growth and survival and provide needed information for the restoration Florida Department of Environmental Protection. 1996. Fisheries-independent- monitoring program. 1995 annual report, 58 p. Florida Department of Environmen- tal Protection, Florida Marine Research Institute, 100 8 th Avenue SE, St. Peters- burg, FL 33701. Powell et al.: Growth, mortality, and hatchdate distributions for Cynoscion nebulosus 143 25°20' 25° 10' 2.V00' — 24"50' 81 "00' 80"45' so Mr Figure 1 Location of sampling sites for spotted seatrout (Cynoscion nebulosus) in Florida Bay, Everglades National Park, Florida, including Florida Bay Subdivisions. of the Everglades, including a return of historic freshwater flows into Florida Bay. Two conceptual frameworks have been advanced to couple the role of growth and mortality in influencing cohort dy- namics. Anderson ( 1988), in a review of hypotheses relating survival of prerecruits to recruitment, advocated a growth- mortality hypothesis as a rational framework for early life history studies that address recruitment variability. This concept predicts that survival of a cohort is directly related to growth rates during the early life stages. The growth- mortality framework, which includes several important in- tegrated components and is based on bioenergetic principles of growth and ecological theory that predict growth rate, is directly related to survival. If it can be demonstrated that survival is a function of growth during the early life stage, then a valuable tool becomes available for examining mecha- nisms influencing recruitment of marine fishes. Another framework suggests that the mortality rate does not operate alone in determining stage-specific survival, but it is the mortality:growth (M:G) ratio (mortality per unit of growth) that determines stage-specific survival (see citations in Houde, 1997 ). Houde ( 1997 ) advanced the idea of using the M:G ratio as an estimator of production and potential survivorship especially in early life stages when both mortality and growth are high and variable. This con- cept was partly based on the strong coupling of growth and mortality demonstrated by Ware ( 1975 ) who argued that when growth rate is poorer than average, larvae would be exposed to sources of mortality over a longer period and hence their mortality rate would increase. Growth and mortality values for successive cohorts would tend to form a cluster of points around a regression of mortality on growth based on average values for a particular species. Our intent is not to test the growth-mortality hypothesis (sensu Hare and Cowen, 1997) as outlined by Anderson (1988), nor fully to develop the M:G ratio concept (Houde, 1997), but rather to use these concepts as a framework for our study. The major goal is to provide information on growth and survival of larval and, mainly, juvenile spotted seatrout that can ultimately be used to develop a spatially explicit model that can be linked to Everglades restoration activities. Therefore, the major objectives of this paper are 1 ) to determine overall growth rates of larval and juvenile spotted seatrout in Florida Bay; 2) to determine and com- pare juvenile growth rates geographically; 3) to estimate natural mortality rates of juveniles; 4) to estimate hatch- date distributions; 5 ) to compare cohort growth and mortal- ity rates and G:M ratios for juveniles; and 6) to evaluate the effects of salinity and temperature on otolith growth — a surrogate for somatic growth. Methods and materials Field collections Larval fish used for otolith microstructure analysis were collected from September 1994 through July 1997, mainly in the Gulf transition, western, and central subdivisions (Table 1, Fig. 1). These subdivisions designated by the 144 Fishery Bulletin 102(1) Table 1 Florida Bay sampling stations where otoliths from spotted seatrout were collected Included are numbers in > of larvae and juveniles used in the otolith microstructure ar alysis. and subdivisions as defined by the South Florida Ecosystem Restoration Prediction and Modeling Program, Program Management Committee. Station Latitude Longitude Florida Bay Juveniles Larvae numbei (degrees and minutes) (degr ees and minutes) subdivisions Location (n) in) 1 25 06.81 81 05.27 Gulf transition Cape Sable 4 2 25 06.37 81 01.42 Gulf transition Middle Ground 1 10 3 25 06.40 80 58.58 Gulf transition Conchie Channel — 4 4 25 07.70 80 56.90 Gulf transition Bradley Key 119 — 5 25 07.12 80 56.07 western Murray Key 4 8 6 25 08.11 80 50.95 central Snake Bight 3 — 7 25 09.45 80 53.42 central Snake Bight 4 — 8 25 07.50 80 48.51 central Rankin Lake 12 — 9 25 05.06 80 47.30 central Roscoe Key 20 — 10 25 02.30 81 .1.12 Gulf transition Sandy Key 49 — 11 25 02.90 80 55.00 western Johnson Key Basin 125 — 12 25 06.00 80 52.50 western Palm Key Basin 110 — 13 25 04.50 80 45.15 central Whipray Basin 2 62 14 25 08.00 80 43.20 central Crocodile Point 9 — 15 24 56.70 80 57.20 Gulf transition Schooner Bank 2 — 16 24 54.70 80 56.31 Gulf Transition Sprigger Bank — 8 17 25 00.40 80 47.68 central Sid Key Bank 6 — 18 24 57.03 80 47.52 central Twin Key Basin 6 — 19 25 07.98 80 40.48 eastern Madeira Point 1 — 20 25 11.85 80 37.15 northern Little Madeira Bay 8 — 21 25 13.00 80 27.80 eastern Shell Key 5 — South Florida Ecosystem Restoration Prediction and Modeling Program, Program Management Committee, were based on modifications of the benthic mollusc com- munity (Turney and Perkins, 1972). In 1994 and 1995, we used 60-cm bongo nets fitted with 0.333-mm mesh fished from the port side of a 5.4-m boat. Beginning in 1996, we used a paired 60-cm bow-mounted push net with 0.333- mm mesh nets similar to that described by Hettler and Chester (1990). Juvenile spotted seatrout were obtained from monitor- ing programs established by the NOAA Center for Coastal Fisheries and Habitat Research (NOAA) and Florida Ma- rine Research Institute (FMRI). NOAA collections were made from May 1995 through September 1997. Juveniles were collected with an otter trawl towed between two 5-m boats. The otter trawl measured 3.4 m (headrope) and was fitted with a 3.2-mm mesh tailbag with 6-mm mesh. FMRI collections were made in 1995 with a seine and a trawl. The 21.4-m center-bag drag seine was fitted with a 1.8 m x 1.8 m x 1.8 m bag of 3.2-mm mesh. The 6.1-m (headrope) otter trawl was fitted with a body of 38.1 -mm stretch mesh and a 3.2-mm mesh tailbag. The majority of juveniles (86 r i ) from NOAA and FMRI collections were collected in 1995. Otolith microstructure analysis Otolith processing Otolith removal and preparation gen- erally followed the methods of Secor et al. (1991). All oto- liths, except for the right sagitta, were mounted on a slide with mounting media and archived. The right sagittal oto- lith was embedded for transverse sectioning or polishing (or both). The left sagitta was embedded for transverse sec- tioning if the right was damaged. Sagittae were read with a light microscope at lOOOx magnification under oil immer- sion. The first increment was determined as that following the core increment; which was defined as a well-defined dark increment surrounding the core (Powell et al., 2000). Two blind counts of increments were made by one reader and if the counts differed by more than 5, then the otolith was read again. If the counts were within the acceptable range, the two counts were averaged. Based on a previous validation study (Powell et al., 2000), 2.5 days were added to the increment counts to obtain the daily age. A total of 582 sagittal otoliths were aged. This total included 96 from larval collections from September 1994 through July 1997, 139 juveniles from NOAA collections from June 1995 through September 1997, and 347 from FMRI collections from June 1995 through December 1995. Increment widths were measured on 347 otoliths from FMRI collections (1995) by using image analysis. The measuring path consisted of two segments: a ventral path from the core to the 21 st increment and a ventral-medial path along the sulcus, from the 21 st increment to the edge (Fig. 2). The 21 st increment was selected as the transition point in these measuring paths by test reading 30 otolith sections representing the entire range of sample fish Powell et al.: Growth, mortality, and hatchdate distributions for Cynoscion nebulosus 145 Distal Edae Ventral Counting Path 2 (21 days to capture) Figure 2 Transverse polished section of a spotted seatrout ( Cynoscion nebulosus) ( 18 mm SL; age 48 days) otolith showing the counting paths. lengths. In all samples, the 21 st increment could easily be traced in both measuring paths and in all samples the first 21 increments could be measured within the same image. Increment widths were averaged over a 7-day period. Age estimates were also obtained and we eliminated any oto- lith used to measure increment widths if the difference in total increment count between the two methods ( counts ob- tained directly from the microscope versus those attained by image analysis) was greater than 7 days or 10%. On this basis, 117 otoliths were removed from the increment width analysis. We believed counts obtained directly from the microscope were more accurate than those obtained by summing the number of increments measured on the computer moni- tor with the image analysis system. Counting increments directly through the microscope lens allows the reader to optically section the otolith (by varying the focus), which helps in detecting daily increments. "Frozen" multiple im- ages are a result of using the image analysis; hence optical sectioning is not possible. Data analysis Data from all years and sources were used for 1) overall growth (i.e. larval and juvenile); 2) juvenile growth; and 3) estimates of juvenile mortality. Data from NOAA larval and juvenile collections were used to estimate a body-length-otolith-radius relationship. Data from 1995 FMRI and NOAA collections, which was the most com- plete data set, were used for growth comparisons between cohorts, and hatchdate distributions. Data from 1995 FMRI collections were used for 1) growth comparisons between geographical subdivisions; 2) estimating a wet-weight-age relationship to compute the ratio of wet-weight specific- growth to mortality (G:M ratios), which assesses the rela- tive recruitment potential of individual cohorts (Houde, 1996; Rilling and Houde, 1999; Rooker et al., 1999); and 3) determining the influence of temperature on otolith incre- ment width. We used the FMRI data set exclusively for the above analyzes because collections were spatially more localized and wet weights were available. Natural mortality (M) estimates were derived by regress- ing log. unadjusted numbers on age classes (5-day bins); the resulting slope provided an estimate of total mortality (Ricker, 1975). However, on the basis of the age-frequency distributions (Fig. 3), we considered juveniles a40 days old fully recruited to our gear and juveniles >90 days old ap- peared to avoid our gear. Hence, only juveniles between 40 and 90 days old were used to calculate mortality. Hatchdate distributions were computed on a weekly ba- sis and adjustments for mortality were made on individual juveniles by the equation N =N,/e-z<, where N = estimated number at hatching; N t = number at time t (N t =l because N was calcu- lated for each individual fish); Z = instantaneous daily mortality coefficient; and t = age in days. Spotted seatrout cohorts were divided into weekly units, but comparisons between cohort growth was done on a monthly basis because of inadequate numbers for weekly comparisons. A test of heterogeneity of slopes was imple- 146 Fishery Bulletin 102(1) CJ ^f •* -a- Tt n 't m to n CO ■5f o CM o o o o o co -^- in co r*~ Age class (days) o CO o CD Figure 3 Frequency distribution of spotted seatrout {Cynoscion nebulosus) age classes used in deter- mining minimum age at full recruitment to the sampling gear, and mortality. 32 30 I 28 CO ra 26 a> Q. E CO merited by using a generalized linear model (SAS/STAT software, version 6.12, SAS Insti- tute, Cary, NO to test if growth differed among cohorts. A general linear test ( Neter et al., 1983 ) was used to compare growth between three geo- graphical subdivisions (Gulf transition, western, and central). This test is a function of the error sum of squares of the reduced model minus the error sum of squares of the full model. Adequate numbers of juveniles were not available to com- pare growth in eastern and northern subdivi- sions (Table 1). Circular statistics (Batschelet, 1981) were used to determine if spawning, as determined from hatchdate distributions, was uniform over the lunar month. The phase of the moon for 1995 was identified by the fraction il- luminated (U. S. Naval Observatory Applications Department, 1997). A 3-point moving average was used to test if spawning was cyclical. Cohorts (1995) were categorized according to the following hatchdates: cohort A, 29 March-2 May ("April"); cohort B, 3 May-6 June ("May"); cohort C, 7 June-4 July ("June"); cohort D, 5 July-1 August ("July"); cohort E, 2 August-5 September ("August"); cohort F, 6 September— 3 October ("September"). Comparisons of the relative recruitment potential of individual cohorts (G:M ratios) between all cohorts were unresolved. Although cohort mortality estimates could be generated, they were appropriate (by analyzing r 2 and P-values from regression analysis) for only three cohorts (cohorts B, D, and F). A random coefficient model was used to investigate the relationship between growth rate of otoliths with age and 24 22 20 - (I O II 4U - 35 - 30 - < , * \ i \ I 25 - 20 - 15 - 10 - < t 5 - « » Station Figure 4 Mean and ranges of temperature and salinity data by station used in the otolith microstructure longitudinal analysis (relationship between increment width and temperature and salinity). For station locations relative to subdivisions, see Table 1 and Figure 1. temperature from juveniles collected in 1995. Most fish were exposed to salinities in a narrow range between 28 and 34 ppt; only 9 fish were exposed to salinities in the 5-13 ppt range (Fig. 4). Consequently, there was insufficient in- formation to obtain reliable inferences on the relationship of growth rate to salinity or the relationship to salinity and temperature for growth information obtained by using either otolith measuring path. This was a disappointment because growth responses to salinity were considered an important objective in relation to proposed Everglades water management activities. Thus, investigation was restricted to the relationship of growth with temperature. A separate model was fitted for the first ( 1-21 increments) Powell et al.: Growth, mortality, and hatchdate distributions for Cynoscion nebulosus 147 and second (22-60 increments) measuring paths because otolith increment width changed at a constant (age-inde- pendent) rate for each path. We did not include fish with >60 increments because the relationship past this number was determined for only 10% of the fish and included obvi- ous outliers. Letting Y be the otolith width measurement for fish ; at age a , where y indexes time, the model for each path was Y ,j = «o, + «i where a 0l and « 1; are the fish-specific intercept and slope describing the relationship between increment width and age for fish i, and e is a normally distributed error term; thus, a h is the growth rate for fish i over the measuring path. Temperature exhibited only negligible change for any given fish over the measuring path; thus, temperature for fish i was summarized as t r the average temperature over the path for that fish. To determine an appropriate model for the relationship between intercept and growth rate and temperature, a preliminary analysis was performed in which ordinary least squares estimates of « 0; and a h were obtained separately for each fish i and plotted against tem- perature. For the first measuring path (1-21 increments), the appropriate model was «o, = A)0 + 0oi'i + b or «i, = Pw + Put, + P\4? + b ii> where b 0l and b h are normally distributed random effects, allowing growth rates for fish at the same temperature to vary across fish. For the second measuring path (22-60 increments), the appropriate model was, «o, = Poo + /V, + Po-i'r + V «ii = Pw + 0ii'i + Put? + b u- By substitution, these considerations yielded models 1 and 2 for the first and second paths, respectively; Y „ = { Poo + fVP + Cfto + 011*1 + 012*^ a „ + b o b lpii +e ii (•Pw + Pn l , + 012^ a a + b o, + b i, a „ + e ,j (1) (2) thus representing otolith increment width in each case as having a straight line relationship with age, where the slope (age-independent growth rate) depends on average temperature according to a quadratic relationship. The random effects allow observations on the same fish to be correlated, whereas observations across fish are inde- pendent. Models 1 and 2 were implemented in SAS Proc Mixed (SAS/STAT software, version 6.12, SAS Institute, Cary,NC). Daily temperature records were obtained from the Unit- ed States Department of Interiors National Park Service, Florida Bay monitoring stations and averaged over a 7-day period. In 1995, temperature records were available only for Johnson Key Basin ( JKB), Whipray Basin (WB), Little Blackwater Sound (LBS), and Little Madeira Bay (LMB), but spotted seatrout were also collected at other sites (Table 1). Daily temperatures were estimated for Sandy Key (SK) and Roscoe Keys (RK) from values recorded dur- ing sampling trips because both these stations are not in close proximity to National Park Service monitoring sites. Sandy Key values were regressed on JKB values (same dates). Sandy Key temperatures were collected from Janu- ary 1994 through August 1996. The regression model for temperature was SK = 0.76 + 0.9536 JKB [r 2 =0.89; w=25], Roscoe Key values were regressed on WB values (same dates). Roscoe Key temperatures were collected from Janu- ary 1994 through August 1996. The regression model for temperature was RK = 5.60 + 0.7976 WB [r 2 =0.87; n=31). Temperature values were available at Murray Key (MK) in 1997. To attain values for our 1995 analysis we regressed MK on JKB (same dates). The temperature regression model was MK = 0.77 + 0.9680 JKB [r 2 =0.99; re=342]. We reported measurements in standard length (SL). For preflexion and flexion larvae, standard length was mea- sured from the tip of the snout to the tip of the notochord. For postflexion larvae and juveniles, standard length was measured from the tip of the snout to the base of the hy- pural plate. Results Overall growth of larvae and juveniles (<80 mm SL) was best described by the equation log, standar-d length = -1.31 + 1.2162 (log e age) [«=582; r 2 =0.97]. Growth in body length of juveniles (12-80 mm SL) was best described by the linear equation standard length = -7.50 + 0.8417 {age) [n=486; /- 2 =0.84]; hence, juveniles between approximately age 20-100 days grew on average 0.84 mni/d. There were no significant differences in juvenile growth in body length among three geographical subdivisions [F* 327 =0.756; n=333] (Table 2), but there was a significant growth differ- ence in length for one of six 1995 cohorts (Table 3, Fig. 5). Growth in wet weight of juveniles ( 15-69 mm SL) was best described by the equation log ( , wet weight = -AAA + 0.0748 (age) [n=347, r 2 =0.84]. There was a significant growth dif- ference in wet weight for one cohort (Table 4, Fig. 6). Weekly 1995 hatchdate distributions, determined by us- ing daily instantaneous mortality ( 0.0585. Fig. 7 ). indicated juveniles in collections (i.e. survivors) were from spawning that was cyclical and protracted (Fig. 8). The most intense successful spawning occurred during 21-27 June (9.2% of total). Using a 3-point moving average, we observed three similar cycles (Fig. 8). From data on survivors, -25% of ju- veniles were spawned by late May, 50% by early July, and 75% by late August and from data on cohorts, three cohorts (cohorts C, D, and E; early June-late August) comprised 55% of the total estimated spawn of spotted seatrout. There was no correlation between spawning and moon phase (pe- riodic regression r 2 =0.019, P=0.754) (Fig. 8). The relative recruitment potential (G:M ratio) of the 1995 year class estimated from the wet-weight specific growth coefficient (0.0748) and the instantaneous daily mortal- ity rate (0.0585, Fig. 7) was 1.28. The G:M ratio for three cohorts (B, May; D, July; and F, September) was greater than the ratio for the total 1995 year class because mortal- 148 Fishery Bulletin 102(11 Table 2 Summary of growth data used to compare best described by the linear equation: stan growth ir dard leng length of spotted th = a + b ( age in seatrout among days). three Florida Bay subc ivisions. Growth was Subdivision Intercept Slope n r- Size range (mm SD Gulf transition -11.07 0.8914 139 0.86 16-69 Central -12.23 0.9298 49 0.80 15-63 Western -10.56 0.8834 145 0.85 17-69 Table 3 Summary of statistics for a test for heterogeneity of slopes for cohort somatic growth rates rized according to month of hatchdate (see text). The base parameter is cohort F and all the base cohort. For growth equations, see Figure 5. of spotted seatrout. Cohorts were catego- parameter estimates are deviations from Parameter Estimate Standard error /-value P-value Intercept -7.97270 3.02829 -2.63 0.0088 Cohort A -0.86811 4.31970 -0.20 0.8408 Cohort B -11.85849 3.91387 -3.03 0.0026 Cohort C 1.65094 3.86470 0.43 0.6695 Cohort D -6.70820 4.74936 -1.41 0.1586 Cohort E 1.02077 3.50931 0.29 0.7713 Slope 0.82088 0.05613 14.62 <0.001 Cohort A 0.04054 0.08604 0.47 0.6378 Cohort B 0.24578 0.07106 3.46 0.0006 Cohort C -0.00113 0.07091 -0.02 0.9873 Cohort D 0.15741 0.08730 1.80 0.0721 Cohort E 0.04544 0.06821 0.67 0.5058 Table 4 Summary of statistics for a test for heterogeneity of slopes for cohort wet-weight growth rate of spotted seatrout. Cohorts were categorized according ,o month of hatch date (see text ). The base parameter is cohort F and all parameter estimates are deviations from the base cohort. For growth equations, see Figure 6. Parameter Estimate Standard error /-value P-value Intercept -4.27384 0.23763 -17.99 <0.0001 Cohort A 0.10201 0.37014 0.28 0.7830 Cohort B -0.46348 0.34092 -1.36 0.1749 Cohort C -0.27866 0.32116 -0.87 0.3862 Cohort D -0.19540 0.38352 -0.51 0.6108 Cohort E -0.38260 0.29853 -1.28 0.2009 Slope 0.06974 0.00439 15.88 <0.0001 Cohort A 0.00195 0.00729 0.27 0.7889 Cohort B 0.00679 0.00622 1.09 0.2754 Cohort C 0.00502 0.00575 0.87 0.3835 Cohort 1) 0.00759 0.00702 1.08 0.2808 Cohort E 0.01188 0.00564 2. 11 0.0359 Powell et al.: Growth, mortality, and hatchdate distributions for Cynoscion nebulosus 149 Cohort A Length = -8.84+0 8614 (Age) 60 40 20 20 60 Cohort B Length = -19.83 + 1.0667 (Age) F B0 ^ = 0.80 F n = 57 <9 en 60 o 'O a> 40 % o •n nftri'™ 20 --?-: c m rn 40 80 100 Cohort C i Length = -6.32 + 0.8198 (Age) ? = 0.90 B0 | n = 55 40 20 80 60 40 20 80 60 40 20 80 60 40 20 Cohort D Length = -14 68 + 0.9783 (Age) r 2 = 0.80 n = 69 Cohort E Length = -6.95 + 0.8663 (Age) ^ = 0.89 n =99 20 40 60 Cohort F Length = -7.97 + 0.8209 (Age) r = 0.86 n = 50 Age (days) Figure 5 Comparison of growth in standard length among six spotted seatrout (Cynoscion nebulosus) cohorts collected in 1995. See text for cohort hatchdates. Table 5 Daily gr owth (wet weight in grams) rates and daily mort ality rates for three cohorts in Florida Bay in 1995. Cohorts were cate- gorized according to month of hatchdate (see text). The G:M ratio derived from the growth and mortality rates is also presented. For growth equations and associated r- values, see Figure 6. Cohort Hatchdate month Growth rate Mortality rate r 2 G:M ratio Size range (mm SL) B May 0.0765 0.0445 0.54 1.72 28- -62 D July 0.0773 0.0565 0.82 1.37 37- -68 F September 0.0697 0.0354 0.67 1.97 37- -66 ity rates appeared relatively low compared to the overall mortality rate (0.0585) for juveniles (Table 5). However, differences in mortality rates among these three cohorts were not significant (F 4 . ;i =1.414). There were no significant differences in weight-specific coefficients among the three cohorts (B, D, and F) (Table 4), but a significant difference in length-specific coefficients among the three cohorts was found (Table 3). Cohort B (May) had a significantly higher growth rate than the other two cohorts. There was a close relationship between otolith radius and body length (Fig. 9). A linear equation with the sagittal ven- tral radius, had a similar r 2 as a curvilinear equation with the sagittal dorsal radius. However, we were unable to mea- sure increment widths along this plane and instead used a combination of a ventral path and a ventral medial path. As an initial demonstration that otolith increment width increased with age along the 1-21 increment measuring path and decreased along the 22-60 increment path, simpli- 150 Fishery Bulletin 102(1) 2 ! 1 o -1 -2 -3 Cohort A Log e weight = -4.17 + 0-0717 (age) 20 40 Cohort B Log e weight z 2 = 0.88 n = 47 60 80 100 : -4.74 + 0.0765 (age) 20 40 60 80 100 Cohort C Log e weight = -4.55 + 0.0748 (age) ^ = 0.94 n = 47 JM o^°^ o 20 40 60 80 100 Cohort D Log B weight = -4.47 + 0.0773 (age) ^ = 0.81 n = 61 20 40 60 80 100 3 2 1 -1 •2 -3 -4 20 Cohort E Log e weight = ^1.66 + 0.0816 (age) ? = 0.85 n = 66 40 60 80 100 Cohort F Log e weight = -4.27 + 0.0697 (age) f 2 = 0.86 n = 47 20 40 60 80 100 Age (days) Figure 6 Comparison of growth in wet-weight (grams) among six spotted seatrout \Cynoscion nebulosus) cohorts collected in 1995. See text for cohort hatchdates. fieri versions of Equations 1 and 2 ( see above ) were fitted, in which all coefficients of temperature were set equal to zero, so that Equations 1 and 2 represent simple linear relation- ships with age. For the first path, the estimate of slope was 0.153 fjm/d (P<0.0001); that for the second path was -0.065 fim/d (P<0.0001>. Addition of quadratic terms to each model was not supported (P=0.81 and 0.12, respec- tively). For the first path, whether intercept or growth rate were associated with temperature was determined by test- ing whether the parameters j3 01 , /3 n , and j3 12 were equal to zero. There was no evidence that any of these parameters were different from zero (P=0.45, 0.35, and 0.42, respec- tively); the latter two may indicate that the data do not support the contention that growth rate depends on tem- perature in this range (1-21 d). For the second path, tests "I /'„ ,=0 and /i 12 =0 offered strong evidence that these pa- rameters are different from zero (P<0.001 in each case). In particular, these results suggested for the age range 22-60 d, otolith growth rates decrease. The extent of the decrease is strongly associated with average temperature according to a quadratic relationship such that growth rates were more steeply decreasing with age for lower temperatures and then became shallower at higher temperatures. In summary, for temperatures at the lower and higher end of the observed temperature range, otolith growth rates for the age range 22-60 d were higher than they were in the middle of the observed temperature range. Discussion Growth in body length of juvenile spotted seatrout in Flor- ida Bay was faster than growth of juveniles from Tampa Bay (Table 6, McMichael and Peters, 1989). Florida Bay is generally considered an oligotrophic system (Fourqurean and Robblee, 1999). Nevertheless, seagrass beds in west- ern Florida Bay, where juvenile spotted seatrout are most common (Chester and Thayer, 1990), are significantly more dense than beds in northwestern Florida waters, slightly north of Tampa Bay (Iverson and Bittaker, 1986). Increased growth of juveniles in Florida Bay could be attributed to the dense seagrass beds that provide habitat for epifaunal crustaceans (Holmquist et al., 1989; Mathe- son et al., 1999), which are important in the diet of juve- Powell et al.: Growth, mortality, and hatchdate distributions for Cynosaon nebulosus 151 5.0 - Log, abundance = 6.83 -0.0585 (age) ^ = 094 4.5 - n n= 10 4.0 - ^^^\ 8 3.5- c CO T3 § 3.0 - .a CO Cu g 1 2.5 - _j ^^\. 2.0 - \ 1.5 - o ^f ^f -^ Tf r}- ■3- in cd h~ co o o o o o ^f in cd r^. co Age class (days) Figure 7 Catch curve of juvenile spotted seatrout (Cynoscion nebulosus) used to estimate daily instantaneous mortality (Z). Z = slope = -0.0585. Spotted seatrout were fully recruited to the gear at age 40-44 days. Comparison of spotted seatrout growth (size Florida Bay, Florida (this study). Table 6 in mm SL at age) betw ;en Tampa Bay. Florida (McMichaels and Peters, 1989) and Age (days) Area 10 20 30 40 50 60 70 80 90 Tampa Bay 5.1 10.2 Florida Bay 4.4 10.3 15.3 20.3 16.9 23.3 25.4 31.4 30.5 35.6 39.2 47.2 40.7 55.6 45.8 64.1 nile spotted seatrout (Hettler, 1989; McMichael and Peters, 1989). Additionally, warmer water temperatures have been observed in Florida Bay (Boyer et al., 1999) compared to Tampa Bay (McMichael and Peters, 1989); these warmer temperatures could enhance growth if adequate food is available (Warren, 1971). However, our study and that of McMichael and Peters ( 1989) were quite a few years apart; hence differences that we observed could also be accounted for by interannual variability. In addition, differences in growth could also be attributed to differences in sampling gear between the two studies. Florida Bay is a heterogenous ecosystem and consists of ecologically distinct regions (Phlips and Badylak, 1996; Fourqurean and Robblee, 1999); however, we did not de- tect any differences in growth of juvenile spotted seatrout among our three subdivisions. In general, juvenile collec- tions from the central subdivision were from stations that were spatially dispersed; whereas, juvenile collections in the western and Gulf transition subdivisions were from relatively few stations (Table 1 ). Normally, the central sub- division is characterized by the highest salinities in the bay and the western and the Gulf transition are characterized by high salinities (Orlando et al., 1997). However, in our study, salinities in the three subdivisions were moderate and similar (Fig 4). and growth rates estimated for the three subdivisions could be useful as baseline rates, par- ticularly in the central subdivision where salinities are commonly hyperhaline (Orlando et al., 1997). The spawning habits of spotted seatrout throughout their entire range are generally similar. They have a protracted spawning season, are multiple spawners, and reach sexual maturity at an early age. Initiation of spawn- ing might be temperature dependent, with water tempera- tures between 20° and 23°C necessary to initiate repro- ductive development (Brown-Peterson and Warren, 2001). Hatchdate distributions calculated for spotted seatrout in 152 Fishery Bulletin 102(1) Birthweek Figure 8 ( Al Spotted seatrout {Cynoscion nebulosus) («=417) weekly hatchdate distributions adjusted for mortality, including moon phases (#=new moon; 0=full moon), and 3-point moving average (solid line) of hatchdate distributions. (B) Cumulative frequency of spotted seatrout (n=417) hatch- date distributions. Florida Bay in this study along with early stage larval collections (Powell, 2003) indicate that spotted seatrout spawn between March and October (based on hatchdate distributions) and that the majority of spawning occurs between 27° and 35°C , with very little spawning between 20° and 26°C (based on early stage larval collections). Spawning peaks, based on larval collections in 1994-96, occurred in June, August, and September (Powell, 2003), and early May, late June, and late August through early September based on 1995 hatchdate distributions (this study). However, Stewart (19611 reported that spotted seatrout in Florida Bay spawned throughout the year and that spawning peaked in spring and fall. Another larval fish study in Florida Bay indicated that some spawning occurs as early as February and continues into December (Rutherford et al., 1989). Log e Body length = -1 .64 + 0.7821 (dorsal radius) ? = 0.99 n = 232 80 -i 60 40 20 - E 1 ' 1 ' 1 ' 1 ' ' 1 B> 200 400 600 800 1000 1200 Sagittal dorsal radius (microns) £ 80 CO (7) au -i Body length = = 0.75 + 0.0503 (ventral radius) ? = 0.99 60 - n = 232 rffO 40 - CM§^> QqAO 20 - n- kd I ' I ' I ' I ' I 200 400 600 800 1000 1200 Sagittal ventral radius (microns) Figure 9 The relationship between sagittal otolith radius and standard length (top), and sagittal ventral radius and standard length (bottom) for spotted seatrout (.Cynoscion nebulosus). Peak spawning activity of spotted seatrout is highly variable (McMichael and Peters, 1989; Brown-Peterson and Warren, 2001). McMichael and Peters (1989) observed two spawning peaks; spring and summer. Older fish participate in two peak spawning periods ( Tucker and Faulkner, 1987 ), and a portion of the larger spring-spawned fish (age- 1+) en- ter the spawning population during their second summer, augmenting the number of summer spawning fish. We found that spawning activity and moon phase were uncorrelated, which is not in concordance with observations of McMichael and Peters (1989). They found that distinct peaks in spawning (based on hatchdate distributions of lar- val spotted seatrout) occurred at monthly intervals, and this periodicity might coincide with moon phase. However, this monthly periodicity was not observed when their data for juvenile spotted seatrout were examined. Moreover, statisti- cal tests were not performed on the data in their study. Powell et al.: Growth, mortality, and hatchdate distributions for Cynoscion nebulosus 153 Our inferences, from this study, in relation to spotted seatrout peak spawning are based on hatchdate distribu- tions and should be viewed with caution because hatch- dates are based on survivors. Differential survival for early life history stages can bias results. Hatchdate distributions are valuable when compared to egg or recently hatched lar- val densities and might suggest processes responsible for differential cohort survivorship. Because spotted seatrout undergo a protracted spawning period and because there is high variation associated with icthyoplankton samples ( Cyr et al., 1992), intensive and extensive sampling of recently hatched larvae would be required over a long duration to answer these process-oriented mortality questions. The daily instantaneous mortality rate of juvenile spot- ted seatrout was higher in Florida Bay than those reported from northwestern Florida systems (Nelson and Leffler, 2001). Mortality rates of juvenile spotted seatrout from Florida Bay were 5.7%/d; whereas, for the other systems, rates approximated 3%/d. In general, mortality rates might increase with increasing estuarine temperatures (Houde and Zastrow, 1993). Although we were unable to estimate instantaneous daily mortality rates for larval spotted seat- rout, these data have been estimated for larvae (3.5-6.5 mm) in two southwestern Florida estuaries (Peebles and Tolly, 1988). Highly variable rates were reported between the two Florida estuaries (Naples Bay: 0.70 or 50%/d; and Fakahatchee area: 0.37 or 31%/d). Houde ( 1996) reported a generalized instantaneous daily mortality rate for marine fish larvae of 0.239 (21%/d). Estimating mortality rates for larval spotted seatrout in Florida Bay will be critical for calculating G:M ratios in order to evaluate stage-specific survival and to develop credible spatially explicit models. Mortality rates of spotted seatrout cohorts could be cal- culated for only three of six cohorts (B, May; D, July; and F, September) because slopes were significantly different from zero for only these cohorts. Furthermore, mortality rates of two of the three cohorts (B and F) were associated with low r 2 values (Table 5); hence the G:M ratios along with the mortality rates for these three cohorts should be considered "rough" estimates. Attaining more accurate mortality estimates for spotted seatrout would be valuable in linking cohort variability with potential recruitment and stage-specific survival. For example, larval cohorts of bay anchovy [Anchoa mitchilli) from Chesapeake Bay, a tem- perate estuary, exhibit growth rates that are temporally variable and mortality rates that are spatially and tem- porally variable (Rilling and Houde, 1999). Temperature, zooplankton prey and gelatinous predators are believed to influence growth and mortality rates of the bay anchovy. For striped bass iMorone saxatilis ) in a subestuary of Ches- apeake Bay, cohorts exhibited highly variable seasonal G:M ratios that were strongly influenced by temperature (Houde, 1997). In a subtropical estuary, cohort-specific mortality rates for juvenile red drum varied temporally; early and late season cohorts exhibited the highest mortal- ity rates, which coincided with highest growth rates and G:M ratios for midseason cohorts (Rooker et al., 1999). We agree with Houde ( 1997) that future research should focus on the variability and causes of variability in growth and mortality, both of which interact to determine stage-spe- cific survival. The developmental stage or age where G:M variability is greatest, along with the relationship of this variability to recruitment, need to be determined for spot- ted seatrout in Florida Bay. No doubt a relationship exists between G:M ratios and recruitment. Future research should also determine if cohort G:M ratios and somatic growth rates are seasonally or spatially variable. If they are, then a limited spatial and temporal sampling program could be designed to annually evaluate G:M ratios at highly variable stages or ages as an index of year-class strength of spotted seatrout in Florida Bay. Such an index could be verified by examining year-class catch rates on an annual basis or by virtual population analysis. In our study there was little temporal difference in growth of juvenile spotted seatrout cohorts. Larval growth and mortality, which was not treated adequately in our study, could be influenced by copepod prey — an important dietary component of larval spotted seatrout (McMichael and Peters, 1989). The copepod Acartia tonsa is dominant in Florida Bay, but egg production rates for this species are low in the bay compared to those in other systems (Kleppel et al., 1998). We suspect the "bottleneck" to recruitment of spotted seatrout could occur during the larval stage. Hence, future research should examine mortality and growth of larval and recently settled spotted seatrout; in particular the patterns of larval production potential (G:M ratios). Research in these areas should increase our understand- ing of the degree of variability in stage-specific survival and recruitment of spotted seatrout in Florida Bay (Houde, 1996). For most species, especially those with protracted spawn- ing habits, it is most informative to analyze cohort growth and mortality. For example, striped bass and bay anchovy cohorts in Chesapeake Bay exhibit highly variable growth rates, mortality rates, and stage durations (Rutherford and Houde, 1995; Rilling and Houde, 1999). This variabil- ity could cause differential survival for cohorts and result in frequency distributions of survivor hatchdates that do not resemble recently hatched larvae or egg-production frequency distributions (e.g. Crecco and Savoy, 1985; Rice etal., 1987). We are unable to interpret the significance of the abso- lute value of the G:M ratio for juvenile spotted seatrout, because interannual comparisons were not made, but we presented the ratio for future comparisons. Generally, the G:M ratio is <1.0 during the early larval stage, indicating a decline in biomass. However, the G:M ratio of a cohort will eventually exceed 1.0 as a result of a relative decline in mortality as larvae grow (Houde and Zastrow, 1993). Clearly, stage specific analysis of the spotted seatrout from egg through juvenile stage would have been more informa- tive in determining when the maximum G:M ratio occurs (when cohort biomass increases at a maximum rate) and in providing insight into stage-specific dynamics of spotted seatrout (Houde, 1997). A constraint of our study was our inability to estimate larval mortality rates; hence early life history stage dynamics could not be examined. Size-selective mortality in the juvenile life history stages can have important consequences for recruitment. Sogard ( 1997 ) argued that "within-cohort size-selective mortality" 154 Fishery Bulletin 102(1) is more evident in the juvenile stage than during the egg and larval stages when random mortality independent of fish size is more likely to occur (e.g. dispersal of eggs and larvae away from suitable nursery areas). In addition, vari- ation in size, which provides a "template" for size-selective processes, increases during the juvenile stage as larval size is constrained by egg size. Sogard ( 1997) cited a number of recent studies that suggest the early juvenile period plays a greater role in determining year-class strength than previously thought. We were unable to determine if salinity influenced incre- ment width (a surrogate for somatic growth) at early life stages. Understanding the relationship between salinity and growth is critical because Everglades restoration will most likely result in increased freshwater flows to Florida Bay, and during low rainfall periods, salinities in the north central portion of the bay can exceed 45 ppt (Orlando et al., 1997; Boyer et al., 1999). But, salinities were moderate and similar at most stations where juvenile trout were col- lected in the bay during 1995 I Fig. 4). Very few fish were collected at low salinities; in fact, juvenile spotted seatrout are not commonly collected at low-salinity stations (Table 1; Florida Department of Environmental Protection 1 ), and hyperhaline conditions were not observed in 1995. There- fore, we were only able to determine if temperature could influence increment widths. The curvilinear relationship between otolith growth rate and temperature, although a statistically strong relationship, is difficult to explain biologically. Temperature could mask other factors, e.g. temporal variability in prey and predator availability, and optimal temperatures for growth (Rooker et al., 1999). We were able to demonstrate that one cohort grew faster than five other cohorts, possibly indicating differential prey availability in 1995. An individual-based bioenergetics model for spotted seatrout now in preparation (Wuenschel et al. 2 ) should add to our understanding of the effects of salinity and temperature on larval and juvenile spotted seatrout Acknowledgments We are especially grateful to Al Crosby, Mike Greene, Mike LaCroix, and other Beaufort staff that participated in the field work. We thank James Waters of the NMFS Southeast Fisheries Science Center for computer programing assis- tance and Jon Hare of our laboratory for performing the circular statistics. We are grateful to Dean Ahrenholz, Jon Hare, Patti Marraro, Joseph Smith, and three anonymous reviewers for their valuable reviews of the manuscript. We also thank Steve Bobko at Old Dominion University for the image analysis macro used to obtain otolith increment widths. 2 Wuenschel, M. J., R. G. Werner, D. E. Hoss, and A. B. Powell. 2001. Bioenergetics of larval spotted seatrout (Cynoscion nebulosus) in Florida Bav. Florida Bay Science Conference, April 23-26, 2001, p. 215-216. Westen Beach Resort, Key Largo, Florida. Abstract. Center for Coastal Fisheries and Habitat Research, Beaufort Laboratory, 101 Pivers Island Road, Beaufort, NC 28516. Literature cited Anderson, J. T. 1988. A review of size dependent survival during pre-recruit stages of fishes in relation to recruitment. J. Northw. Atl. Fish. Sci. 8:55-66. Batschelet, E. 1981. Circular statistics in biology, 371 p. Academic Press, New York, NY. Boyer, J. N, J. W. Fourqurean, and R. D. Jones. 1999. Seasonal and long-term trends in the water quality of Florida Bay ( 1989-1997). Estuaries 22:417-430. Brown-Peterson. N. J., and J. W Warren. 2001. 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Philadelphia, PA. 156 Abstract— Age and growth of the night shark (Carcharhinus signatus) from areas off northeastern Brazil were determined from 317 unstained ver- tebral sections of 182 males (113-215 cm total length [TLI>, 132 females (111.5-234.9 cm! and three individuals of unknown sex ( 169-242 cm ). Although marginal increment (MI) analysis sug- gests that band formation occurs in the third and fourth trimesters in juve- niles, it was inconclusive for adults. Thus, it was assumed that one band is formed annually. Births that occur over a protracted period may be the most important source of bias in MI analysis. An estimated average percent error of 2.4'S was found in readings for individuals between two and seventeen years. The von Bertalanffy growth function (VBGF) showed no significant differences between sexes, and the model derived from back-calculated mean length at age best represented growth for the species (1^=270 cm, K= 0.11/yr, t =-2.71 yr) when compared to the observed mean lengths at age and the Fabens' method. Length-frequency analysis on 1055 specimens (93-260 cm) was used to verify age determina- tion. Back-calculated size at birth was 66.8 cm and maturity was reached at 180-190 cm (age 8) for males and 200-205 cm (age ten) for females. Age composition, estimated from an age- length key, indicated that juveniles predominate in commercial catches, representing 74.3% of the catch. A growth rate of 25.4 cm/yr was esti- mated from birth to the first band (i.e. juveniles grow 38?< of their birth length during the first year), and a growth rate of 8.55 cm/yr was estimated for eight- to ten-year-old adults. Age determination and growth of the night shark (Carcharhinus signatus) off the northeastern Brazilian coast Francisco M. Santana Rosangela Lessa Universidade Federal Rural de Pernambuco (UFRPE) Departamento de Pesca, Laboratory de Dinamica de Populacoes Mannhas - DIMAR Dois Irmaos, Recile-PE, Brazil, CEP 52171-900 E-mail address (for R. Lessa. contact author) rplessaigig.com br Manuscipt approved for publication 26 June 2003 by Scientific Editor. Manuscript received 20 October 2003 at NMFS Scientific Publications Office. Fish. Bull. 102:156-167 (2004). The night shark (Carcharhinus sig- natus) is a deepwater coastal or semi- oceanic carcharhinid that is found in the western Atlantic Ocean along the outer continental or insular tropical and warm temperate shelves, at depths exceeding 100 meters (Bigelow and Schroeder, 1948). The species has been recorded from Delaware to Florida, the Caribbean sea (Cuba), and northern South America (Guayana) (Compagno, 1984). It has also been recorded in southern Brazil, Uruguay, and Argen- tina (Krefft, 1968; Compagno, 1984; Marin et al., 1998), and on the sea- mounts off northeastern Brazil (02°16' to 04°05'S and 033°43' to 037°30'W. Menni et al., 1995) where it is called "toninha." Since 1991, tuna longline vessels have targeted the night shark in northeast- ern Brazil (Hazin et al., 1998) because of its highly prized fins, the increasing value of shark meat in the local market, and their relatively large abundance and accessability on seamounts (Menni et al., 1995). This species is most im- portant in the area, making up 909; of catches over shallow banks (CPUE, in number, is 2.94/100 hook), and only 15% of catches on the surrounding deep area, yielding 0.04/100 hook (Amorim etal., 1998). Information on this species is re- stricted to taxonomic descriptions (Bigelow and Schroeder 1948; Cadenat and Blache, 1981; Compagno, 1984, 1988), and some biological aspects (Guitart Manday, 1975; Hazin et al., 2000). Night sharks reach >270-280 cm maximum total length (TL) (Compagno, 1984; Branstetter, 1990). Off northeast- ern Brazil, females mature at 200-205 cm TL, males at 185-190 cm. Litter sizes range from 10 to 15 pups and the gesta- tion period may last one year ( Hazin et al., 2000). The assumed size-at-birth off the United States is 60-65 cm TL (Com- pagno, 1984; Branstetter, 1990). Age and growth have not been estimated. The aim of this study is to present the first growth curve for Carcharhinus signatus from vertebral and length-fre- quency analyses. This information will permit the use of age-based stock as- sessment methods for the management of the species in the Exclusive Economic Zone (EEZ) off Brazil. Materials and methods Sampling data and vertebrae were col- lected from November 1995 to Novem- ber 1999 from commercial landings (Natal, Brazil) caught in deep (Aracati, Dois Irmaos, Fundo, Sirius) and shallow (Pequeno, Leste, and Sueste) seamounts with depths between 38 to 370 m at the summits (Fig. 1 ). Commercial vessels were equipped with -30 km Japanese-style multifila- ment longline gear (Suzuki et al., 1977). On average, each vessel used 970-980 hook per day; mainline sets began at -02:00 h and ended at -06:00 h. The retrieval of gear began at noon and fin- ished by dusk. The Brazilian sardinella (Sardinella brasiliensis), margined fly- ingfish (Cypselurus cyanopterus), and squid [Loligo sp. ) were used as bait (Hazin etal, 1998). A total of 1055 individuals, landed whole, eviscerated, or as carcasses (headless and finless). were sampled. The interdorsal space (posterior dorsal Santana and Lessa: Age and growth of Carcharhinus signatus off the northeastern Brazilian coast 157 0° 02°S - 04°S - 06°S ATLANTIC OCEAN Archipelago of Fernando de Noronha 40 : W 38=W 36°W 34 =W 32W Figure 1 Location of the sampling area for the night shark iC. signatus) collected off northeastern Brazil. fin base to origin of the second dorsal fin [IDS, cm] ), total length (snout to a perpendicular line from the tip of the up- per caudal fin [TL, cm] ) and fork length (snout to fork of tail [FL, cm]) were measured. In carcasses, only IDS was mea- sured, and IDS, FL, and TL were recorded for eviscerated or whole individuals. A set of five or six vertebrae were removed from below the first dorsal fin in 317 specimens. Total length was measured as the "natural length" (without depressing the tail) according to Garrick ( 1982). To estimate TL for carcasses, relationships from sub- samples of IDS versus TL and FL versus TL were estab- lished for males and females separately. Linear regressions derived for each sex were tested for homogeneity and ana- lyzed for covariances (ANCOVA), resulting in TL=1.2049 FL + 1.7972 (r 2 =0.944.n=668,P=0.41) and TL = 3.3467 IDS + 30.879 (r 2 =0.824; rc=764, P=0.161). Whenever length is mentioned hereafter, we always refer to TL. Vertebrae were processed by removing excess tissue, fixed in 49c formaldehyde for 24 hours, and preserved in 70% alcohol. Each vertebra was embedded in polyester resin and the resulting block was cut to about a 1-mm thick sec- tion containing the nucleus by using a Buehler® low speed saw. Initially, alizarin-red-s stained sections (Gruber and Stout, 1983) were compared to unstained sections from the same individuals to define the best contrast for narrow and broad zones. In the first procedure, sections were immersed overnight in an aqueous solution of alizarin red s and 0.1% NaOH at a ratio of 1:9 and then rinsed in running tap water. In stained sections, narrow zones were visible as dark red and broad zones as light red, whereas in unstained sections translucent (narrow) and opaque (broad) zones were visible under transmitted light. Unstained sections produced com- parable results to alizarin stained sections and were used for band observation in the study. Bands counted in each section and distances from the focus to the margin of each narrow zone were recorded. Vertebral radius (VR) was measured by using a binocular dissecting microscope equipped with an ocular micrometer. Measure- ments were made at lOx magnification ( 1 micrometer unit=l mm) with both reflected and transmitted light. The same reader read sections from the same specimen twice at dif- ferent times without knowledge of the individual size or previous count. Whenever the counts differed between the two readings, a third reading was used for back-calculation of size-at-age. The index of average percentage error (IAPE) (Beamish and Fournier, 1981) to compare reproducibility of age de- termination between readings was calculated. IAPE = 1 / Ar]T ( 1 / R^ ( | X tj - Xj \Xj)x 100, where N = the number of fish aged; R = the number of readings; X t - the mean age off 1 ' fish at the i' h reading; and Xj = the mean age calculated for the/ ,! fish. Marginal increment ( MI ) analysis to determine the time of band formation was used. The analysis was restricted to 1995-97, when samples were collected every month. The dis- tance from the final band to the vertebral's edge (MI) was expressed as a percentage of the distance between the last two bands formed on vertebrae (Crabtree and Bullock, 1998). The distance between the last and the penultimate band was divided by the distance between the nucleus and the 158 Fishery Bulletin 102(1) last band for each vertebra that was measured, and we then calculated the mean of this number for the entire sample: IK*. ,)-i?„)//2=0.13(SE = 0.0009). The expected distance between the last (R n ) and the pen- ultimate (i? n _! ) bands was estimated as a function of the distance between the vertebral nucleus and the last band (MI). The percent marginal increment (PMI) was calcu- lated as PMI = [MI I (0. 13 x R n )] x 100. Analysis of variance to test for differences in PMI by month was used. Post-hoc tests (Tukey honest significant differences ( [HSD] ) were performed to indicate which months were different. Characterization of the vertebral edge was used to de- termine the time period of band formation (Carlson et al., 1999). Under reflected light, a narrow dark zone (MI 0), a narrow light zone ( MI 0. 1 to 0.5 ), and a broad light zone ( MI 0.6 to 1 ) were observed. Absolute marginal increments ( MI ) were also analyzed by trimester for juveniles aged four and five years, and for adults ( more than eight years ) to confirm the time of translucent zone formation. The relationship between VR and TL was calculated by sex, tested for normality, and compared by ANCOVA (Zar, 1996). The final regression in both sexes did not pass through the origin, thus suggesting that the Fraser-Lee method was the most appropriate for back-calculation (Ricker, 1969). [TL]„ = (RJVR)({TL\-a) + a, where [TL] R = the back-calculated length at age n; - vertebral radius at the time of the ring n\ VR = the vertebral radius at capture; TL = the length at capture; and a = the intercept on the length axis. A von Bertalanffy growth function (VBGF) (von Berta- lanffy, 1938) was fitted to back-calculated and observed length-at-age data with the following equation. L . 1- kit („)i where L t = predicted length at age t; L r = mean asymptotic total length; K = growth rate constant; and t = the age when length is theoretically zero. To obtain parameters of VBGF, data were analyzed by using FISHPARM (Prager et al., 1987) for nonlinear least- squares parameter estimation. The Kappenman's method (1981), based on the sum of squares of the differences between observed and predicted lengths from a growth model, was used for comparing male and female growth curves. In addition, likelihood-ratio tests were used to com- pare parameter estimates of the von Bertalanffy equation between sexes (Cerrato, 1990). Von Bertalanffy parameters (L x , K) were also estimated by the method of Fabens ( 1965 ) usually employed for recap- ture data and which takes into account the size at birth (L (l ) instead of t . This method reconfigures VBGF and forces the regression through a known size at birth: L, =Ljl-be- where b = (L., -L )/L x We used Fabens routine for growth increment data analysis of the FAO-ICLARM stock assessment tools (FI- SAT) program (Gayanilo et al., 1996), assuming that the time intervals (=At) for each size-at-age class were equal and had a periodicity identical to that obtained from the vertebral analysis. The lengths of 1055 individuals were divided into 5-cm intervals and analyzed by the Shepherd method ( 1987 ) with the length-frequency data analysis program ( LFDA ). Initial values of L v were based on results from maximal lengths in the sample and from literature (Compagno. 1984). K values ranging from 0.05 to 1.8 were used as input into the program, which was run repeatedly until the highest score function was obtained. The L x and /f values were then used to calculate t (Sparre et al., 1989): t Q = t + {l/K)(\nlL. -lt])/LJ. Using an age-length key, based on 317 individuals for which vertebrae were read, we evaluated the age composi- tion of the sample (Bartoo and Parker, 1983). Maximal ages in the sample were calculated by employing the inverted VBGF (Sparre et al.. 1989). Further, the formula by Fa- bens (1965) [5(ln2)/AT for longevity estimation was used. All statistical inferences were made at a significance level of 0.05. Results The total sample size consisted of 1055 individuals: (551 males [93-248 cm], 499 females [110-252 cm], and 5 individuals of undetermined sex [169-260 cm]) (Fig. 2). Of these, vertebrae were removed from 317 specimens (182 males [113-215 cm], 132 females [111.5-234.9 cm], and 3 individuals of undetermined sex [169-242 cm]). Differences in the relationship between VR and TL between sexes were not found to be significant (P=0.81D. The regression for the overall sample showed a linear relationship: TL = 13.523V/? + 41.824 , indicating that vertebrae are suitable structures for age determination, and methods based on direct proportion are appropriate for back-calculation. The average percentage error, calculated between two readings, ranged from 098 to 4.5^ in vertebrae with 2 to 17 bands and the average IAPE for the overall sample was 2.4'-. Coefficient of variation (CV) between readings for total sample was 6.88' < . Monthly PMI analysis, for the entire sample, indicated that bands were formed from June to October, when high- Santana and Lessa: Age and growth of Carcharhinus signatus off the northeastern Brazilian coast 159 70 i 60 50 >, 40 CJ c CD => 30 i cr CD it 20- 10 ii n i if 1 1 1 n=1055 \\\] Jl 1 r, t I . . Lengtl easter bars = muimmmLfiifimiflminmmifimifimcn OUCVJCvjCvjC\ic\JC\iC\iOT-cjpO'0.05) and likelihood ratio tests (Table 4). Data were then treated together, incorporat- ing individuals of undetermined sex. VBGFs derived from observed length at age were not tested because of missing values in different age classes. The method of Fabens for combined sexes, fitted to back-calculated data, provided L, and K, by using b = 0.781, L = 62.5 cm (Compagno, 1984) and. At = 1 year (Table 2). Parameters from back-calculation were close to those derived from length-frequency analysis for 1055 specimens, whereas observed lengths and the Fabens method, provided the most varying parameters with lowest correlation and highest coefficients of variation (Table 2). The smallest specimen in the vertebral sample show- ing two complete bands in sections was 111.5 cm, close to the estimated mean back-calculated length at age two of 113.7 cm (Table 3). Size at maturity, 185-190 cm for males and 200-205 cm for females, corresponded to 8- and 10-year-old individuals, respectively (Fig. 6). The largest and oldest specimen whose vertebrae were used, was 242 cm, which corresponded to 17-year-old individual. A growth rate of 25.4 cm/yr was estimated from birth to the first band — a rate that corresponded to 389 of the birth • □ 0.1-0.5 5! r 1 □ 0.6-1 33 45 8 51 6 15 2< \ 43 4 • 2 1 7 9 1 6 5 ' % -i • -| i IJI 1 J 1 -X --I- 1 - M A J J Month Figure 4 Categorization of edges by month for the night shark iC. signal its) off northeastern Brazil. length (the length at birth being 66.8 cm). Also, a mean rate of 8.55 cm/yr was calculated for 8- to 10-year-old individu- als, when maturity is achieved (Table 3). Considering mature individuals >185 cm. the age com- position for the vertebral samples («=317) indicated that 17.3% of specimens were adults (Table 5). Instead, for the total sample (ra=1055), where the age ranged between 2 to al7 years, adults corresponded to 25.3% of the total sample Santana and Lessa: Age and growth of Carcharhinus signatus off the northeastern Brazilian coast 161 1 0.2 3 4 5 0.6 0.7 08 9 1 12 10 - 8 6 4 2 ill 1 2 3 4 5 0.6 07 08 09 1 12 10 8 6 4 - 3 ,d Trimester n=36 I.. I 1 2 3 0.4 5 0.6 7 8 9 1 12 - 10 4 lh Trimester Nihil. . 1 2 3 4 0.5 0.6 7 08 9 1 B r' Trimester n= 14 II I - 2 nd Trimester 12 - n = 24 10 - 8 6 4 2 o - 01 0.2 0.3 0.4 0.5 0.6 0.7 08 09 1 12 10 - 3 rd Trimester n= 14 ll 01 0.2 03 0.4 05 0.6 0.7 0.8 09 1 12 10 8 6 4 2 4 m Trimester n=10 Jl 1 0.2 3 4 0.5 6 0.7 8 0.9 1 Ml Figure 5 Marginal increments (MI) by trimester for ages 4 and 5 (n = 139) (A) and a8 (Bl (n=54) for the night shark (C. signatus) from northeastern Brazil. (Fig. 7). According to the inverted back-calculated VBGF the oldest specimen in the sample was 31.7 years old (260 cm), whereas longevity was 31.5 years. Discussion Validating the time of band formation is considered critical when using hard parts for age estimates (Brothers, 1983), and validation is successful when growth zones are shown to form annually in all age groups of the population (Beam- ish and McFarlane 1983). Marginal increment analysis, carried out on younger and faster growing individuals, cannot always be used for validating older age groups, and therefore all ages must be ascertained (Brothers, 1983). In the present study, we obtained significant differences in marginal increments for the total sample. However, the significance level of the test (P=0.046) was close enough to 0.05 to cause us to suspect that the distributions could have been similar. The time of band formation varied when different age groups were analyzed separately, despite suggestions that bands are completed in the third and 162 Fishery Bulletin 102(1) E o 150 100 B \ 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 1 2 3 4 5 6 7 8 9 10 1 1 12 13 14 15 16 17 1 250 200 150 100 50 i ! V '■ Back-calculated Observed Fabens 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 Age (years) Figure 6 Growth curves generated from (A) females. (B) males, and (Cl sexes combined for the night shark (C. signatus) off the northeastern Brazil. Table 2 Von Bertalanffy parameters derived from back-calculated lengths (BC), observed lengths (OL), lengths the length-frequency data analysis (LFDA) package for the pooled database (SE is standard error; CV from the Fabens method, and is coefficient of variation i. Methods Sex L_, (cm) SE CV /f(/year) SE CV f (year) SE CV r- BC Males 256.5 5.56 0.022 0.124 0.007 0.055 -2.538 0.119 0.047 0.999 Females 265.4 4.15 0.016 0.114 0.005 0.045 -2.695 0.127 0.047 0.999 Both 270 2.78 0.01 0.112 0.003 0.031 -2.705 0.099 0.037 0.999 OL Males 306.1 37.71 0.117 0.076 0.02 0.267 -4.663 0.882 0.189 0.995 Females 297.1 26.71 0.09 0.077 0.018 0.235 -4.853 0.977 0.201 0.99 Both 289.9 7.6 0.026 0.085 0.006 0.077 -4.395 0.348 0.079 0.998 Fabens Both 285.3 15.69 0.055 0.08 0.016 0.2 — — — — LFDA Both 270.9 — — 0.106 — — — — — — fourth trimesters (new bands begin to form in this period) in juveniles. Results were inconclusive for adults. For C. obscurus (Natanson et al., 1995), C. plumbeus (Sminkey and Musick 1995), C. porosus (Batista and Silva, 1995: Lessa and Santana, 1998), C. acronotus (Carlson et al., 1999). and /. oxyrhynchus (Lessa et al., 2000), inconclusive results for MI analysis were obtained. The inability to dem- onstrate the periodicity of band deposition in adult sharks Santana and Lessa: Age and growth of Carcharhinus signatus off the northeastern Brazilian coast 163 in the present study is similar to the outcome for C. limbatus older than four years (Wintrier and Cliff, 1996). For the last mentioned species, the problem was circumvented by restricting MI analysis to juveniles (Killam and Parsons, 1989). Age was assigned by assuming an annual pattern of deposition, as commonly occurs for most carcha- rhinids like C. brevipinna and C. limbatus, Rhizoprionodon terraeno- vae (Branstetter et al., 1987; Brans- tetter and Stiles, 1987), Negaprion brevirostris (Gruber and Stout, 1983), and C. longimanus (Seki et al, 1998; Lessa et al., 1999c). Three sources of bias generally occur with MI analysis: 1) sample sizes are small for any particular month or for any age class (Cailliet, 1990); 2) data are collected over a too long a period causing variability on ac- count of annual marks that are not formed at the same time ( Brothers, 1983 ) and 3 ) births occur over a long period (Brothers, 1983). All these may have biased MI analysis in the present study. Research carried out in the study area by Hazin et al. (2000) indi- cated that copulation takes places throughout the austral summer. Embryos measuring 10 to 40 cm were collected in February, whereas 31.8 to 37.2 cm embryos were found in June. This remarkable variability in embryo size during the gestation period suggests that birth period lasts several months. Furthermore, with an estimated back-calculated birth length of 66.8 cm, individuals measuring -40 cm in February will be born long before individuals that measured 37.2 cm in June. Such a protracted parturition period could lead to differences in MI of the same cohort. Thus, after an assumed -12 months gestation period, individu- als are born with birth dates vary- ing by several months. Moreover, no significant differences in MI analysis was found for C. porosus and /. oxyrhynchus, which also have a protracted birth seasons (Lessa et al., 1999a, 1999b). A comparison of growth model parameters by using known size information, such as size-at-birth and maximum observed size, can be 01 t- CO CO 1 CM O Hr-> 03 - — - 1 CM CN CO ed co XI 00 CO CN CM a o> -— CS lO [^ r- l> CO ■* 135 a > — 1 CO ^ CO CN c- CO CO «? 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CO u 05 CJ) t-; CN CN rH O) in CN CO IM Tf 05 in CO o ho 00 c— o t-' d 00 CO 00 00 d [> CO d CO CO d CN 05 CO 2 -c Oi CO rt cm o CO CO rH 00 "* 00 rH IN "* ■* 05 Tf [^ 00 I> c- Tf en in CO CM CN CN in CO CN CO CO — CN CN ~ iri - yi CN CN ri - ft c -c CU CN rH CO r~ O 05 in in CO (N CD 00 CN CO 00 in CO CM C^ 1 1 -a c rn 03 d CO CN rH CN (N CO CO 05 d rH CO CN CN 1 1 CJ '3 CO 05 05 05 Ol 05 05 05 05 05 05 (35 OS t o CO XI O CO X CU CO l> i-j t- 00 CO CO CN in CO i-i 05 CO 00 in CO X | | -a c "cO 3 o iri iri t> t> I> 00 00 t> r> d ■* d iri d CO r-i CO CO CO in CO CO CO CO CO CO CD CD CO CO X CO T> -a '> cj ■3 ~ "oj O CN 03 o CO CO CO m O) CO rH CN rH a 4J rH CN ■* OJ CO CN CN rH CO 3 HH o o 3 CJ T3 CO CJ Ji CJ CO CD CD cm "cO o -g cm CO CO CQ Tf in CO t- 00 05 = rH CI in C- c CO CJ - CO > e c « j3 S 3q o CQ "~" < 164 Fishery Bulletin 102(1) Table 4 Likelihood ratio tests comparing estimates of von Bertalanffy parameters for males (noted as 1 1 and females (noted as 2) for C. signatus in the linear constraints. Hypothesis Linear constraints Residual SS X 2 r df P HQ none 60536.4 Hwl £=oi = L x2 10511 0.049 1 0.996 Hto2 A, = K 2 10524.3 0.047 1 0.996 Hto3 '01 = '02 10205.6 0.122 1 0.999 HvA Same L^, A. and t 24301.2 0.164 3 0.973 useful as a method of verification ( Cailliet et al., 1983). Although no specimens younger than 2-years-old were caught (perhaps due to the gear selection bias), the presumed size at birth was about 60-65 cm ( Compag- no, 1984), which is similar to the estimated size in the present study (66.8 cm). Also, the estimated L r value (270 cm), derived from the back-calculated or observed VBGF is close to the maximum size of 276 cm men- tioned by Bigelow and Schroeder ( 1948), 280 cm off Cuba (Compagno, 1984), and 275 cm byGarrick(1985). Mean observed length-at-age is gener- ally higher than back-calculated mean length-at-age (Bonfil et al., 1993; Lessa and Santana. 1998), leading to lower values of L a and higher values of K. However, in the present study, although mean observed length-at-age is higher than mean back-cal- culated lengths, parameters derived from back-calculation provided a lower L x and a higher A' value. Inconsistency of the observed length-at-age set is attributed to the missing values in for ages 0, 1, 13, 14, and 16. This led to a VBGF which provided an unrealistic birth size of 90 cm and which present a flatter shape than the back-calculated curve. Von Bertalanffy growth parameters generated from both back-calculation and by the Fabens method were all consid- ered suitable and were of the same magnitude. However, taking into account 1 ) parameters close to those derived for length-frequency analysis, and 2) the best statistical fit, the back-calculated VBGF was chosen as best representing growth in the species. Comparisions of biological features such as maturity size and maximum sizes have been used for inferences in growth and to explain differences between sexes (Natanson et al., 1995; Natanson and Kohler, 1996; Lessa et al., 2000). Tin' studied species shows a disparity of -15 cm in matu- rity sizes between sexes (Hazin, et al., 2000), corresponding to ~2 years. In addition, the largest specimen, for which six was determined, was a 252-cm female and the largest male was 248 cm. These disparities, however, did not bring about differences in growth between sexes, as indicated by results of both tests used. Such a result can be explained by the number of juveniles used for age determination (-83' I 300 250 n =1055 >. 200 c S 150 O" 1 "- 100 | 50 .ll Mil.. <1 3 5 7 9 11 13 15 >17 Age (years) Figure 7 Age composition for the night shark (C. signatus) collected off northeastern Brazil. Thus, the number of adults was not high enough to bring about any differences in the growth equation although differences frequently occur after maturity, caused by dif- ferent growth rates between sexes (Natanson et al., 1995; Sminkey and Musick, 1995). Assuming that the time elapsed between birth and the band corresponding to age 1 is one year, the species grows 38% of its birth length during the first year. This growth rate is close to that (50%) generally assumed (Branstetter 1990; Cortes, 2000). Furthermore, the estimated K value falls within the range suggested by the first author, and according to him, the night shark is a relatively fast grow- ing species, presenting a life strategy similar to that of C. falciformis, and apparently depending on rapid growth for adequate neonate survival due to vulnerability to preda- tion from large sharks. In summary, considering the increasing fishing effort on the night shark as a targeted species and that catches are mainly composed by juveniles (representing 74.7' i of specimens in landings), we believe that the A'-selected characteristics of the species (including late maturity, long gestation period, and low fertility 1 should be taken into account in determining the management of this resource. Demographic analyses will be required for the examination of consequences of current levels of exploi- Santana and Lessa: Age and growth of Carcharhtnus signatus off the northeastern Brazilian coast 165 c Q. C 3 2 pq LT> c u a) .Q » ,(B CO be 3 O bo tj, bf no ■" cm 2 I 2 I S 2? oi >5 CO «o CO !N I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I 8 I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I IS I I I I I ! I I I I I I II I I I I I I 12 I8S I M I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I CO CO [- o 1 ' CO -* CO ^ ^H CO I I I I I I CO iO lO ■* CO «-; ^ oj _j ~-; 00 t— tH CO CO t> CO I I I I I I I I I I I I I I I I co I co co t> in o 1 •* co' ~ oi "= I I I I h m -* co I I I I I I I I I I t> m tH CO CO C- I 1> I I I I I I « h ™ ^ n h ! cb I I I I I I I I H CO * —I llllllliquaiaoqwco-*. co«|||||||||| — i cm co co ■* m co I I I I | M10CB^^CDt-C5 CONHCtirtT|'d H h •-< co in in co cm I coocomcoin^-i^j- ' co'^co'cNcodcdiri CO CO CD CM CM ^H I I I I I I I I I I I I I I I I I I I I I I co in t> o — m 10 cri oci o o t-~ in 2 2 «o 7000 ~ 6000 £ 5000 g> |j 4000 □ Females UfkJ/^B w males = o.oi 64 x u** 'jijr ° — w, emates = o.oi 79 * l* «* afljllo ° 3000 2000 J r 2 (combined model) = 0.95 _^ffl^ 1000- ^«e**^ 20 40 60 80 100 Length (cm) Figure 5 Prowfish body weight (W) fitted by an exponential function of fish total length (/..land sex. Data for males (/i=83) are shown by diamonds and the fitted model by a dashed line. Data for females (n=88) are shown by squares and the fitted model by a solid line. Food habits Fish used for diet study averaged 63.8 cm in total length (range: 49-87 cm) in the Gulf of Alaska and 56.9 cm (range: 30-79 cm) in the Aleutian Islands. The contents of 18 prowfish stomachs from the Gulf of Alaska and 58 from the Aleutian Islands showed that jellyfish (999r and 31% Smith et al.: Distribution and biology of Zaprora silenus 175 100 90 80 70 E 60 £ 50 \ S 40 30 20 10 L = 89 33(1-e-° ,8 '<'-<-° 554 ») r = 0.752 10 15 Age (years) 20 25 Figure 6 Prowfish total length \L) fitted by a von Bertalanffy function of age (f). Data for males («=71) are shown by diamonds; data for females (rc=67) are shown by squares. The fitted model is shown by a solid line. Table 1 Mean percent weight (%W) and mean percent freque icy of occurrence (%FO) of the prey items from 18 prowfish stomachs collected in the Gulf of Alaska (GOA; 1996; total prev weight= =299 g and 58 stomachs from the Aleutian Islands area (Al; 1997; total prey weight=1446.6 g). Sample prowfish had an average total length of 63.8 cm (range 49 -87 cm) from the GOA and and 56.9 cm (range: 30-79 cm) from the AI. Prey name GOA(n = 18) AI(n =58) %W %FO %W %FO Scyphozoa (jellyfish) 98.84 100 30.45 29.88 Ctenophora (comb jelly) 0.09 1.23 Polychaeta (worm) 0.03 5.8 Calanoida (copepod) 0.26 28.13 0.04 29.14 Thysanoessa raschii (euphausiid) 0.05 6.67 Mysidacea Mysida (mysid) 0.01 3.13 Hyperiidea (amphipod) 0.19 33.46 Gammaridea (amphipod) 0.12 30.49 Themisto sp. (amphipod) 0.32 28.57 0.14 36.91 Salpa sp. (pelagic salp) 34.06 46.79 Larvacea (pelagic tunicate 1 0.13 12.5 Sebastes sp. (rockfish) larvae, 5-8 mm long 0.43 42.86 Microsomus paeifieus (Dover sole) eggs 0.01 3.13 Unidentified organic material 34.84 32.59 by weight of total food in the two regions, respectively) and gelatinous pelagic tunicates (Salpa spp.; 34% in the Aleutian Islands area only) were the most important food (Table 1). Although calanoid copepods and Themisto sp. (amphipod) were both often present in GOA specimens (28.13% and 28.57% of stomachs, respectively), they were not important food in terms of weight. The same was true in the AI for calanoid copepods, Themisto sp., gammaridean amphipods, and hyperiidean amphipods (29.14%, 36.91%, 30.49%, and 33.46% respectively). Mysids and larvaceans from GOA specimens as well as ctenophors, polychaetes, and euphasiids from AI specimens occurred in trace amounts. Sebastes larvae (5-8 mm standard length), the only fish species found, were found in 43% of Gulf of Alaska stomachs but made up only 0.43% of prey weight. Some Dover sole [Microstomas paeifieus) eggs had also been consumed. 176 Fishery Bulletin 102(1) 0.8 H 0.6 0.4- 0.2- t* 000000 2 -e- 311 2 12 000 000 P mat = 1/(1+e3"'»-"'M 00 i 30 35 40 45 50 55 60 65 70 75 80 85 90 Length (cm) 5 4 1 3 1 1 0.8 - 0.6 - / 3 Jo 0.4 - P 1/(1 + e 9 «- ,9 °') 0.2 - 0- 1^2 6 i 10 15 Age (years) 20 25 Figure 7 Proportion of female prowfish mature (P mat ) as logistic functions of length (L) and age it). Data points based on 39 maturity-at-length and 27 maturity-at-age observations are shown by diamonds, and numbers of females of each cm-length and year-age class are shown next to the corresponding symbol. The fitted logistic models are shown by solid lines. The length and age at which P mat = 0.5 with 95^ confidence limits are 57.0 ±0.4 cm and 5.1 ±0.7 years. Discussion Geographic distribution Historically occurring in the catch in AFSC bottom trawl surveys in areas of the eastern Bering Sea, Aleutian Islands, and Gulf of Alaska regions, prowfish were also observed more rarely farther south along the West Coast as far as the vicinity of San Miguel Island, California. This is the apparent southern limit of their range in the northeastern Pacific (Allen and Smith, 1988). They were most often encountered in the vicinity of the edge of the continental slope near 200 m depth (Fig. 2), although our data increase the maximum known depth of occurrence from 675 m (Allen and Smith, 1988) to 801 m. As indicated by survey CPUE, prowfish density was greatest between the depths of 100 m and 240 m (Fig. 3). Our distribution data show similarities with those of Tokranov ( 1999), who studied >300 bottom trawls executed in 1995-97 on the shelf and slope off the southern Kamchatka Peninsula and northern Kuril Islands, in which adult prowfish were taken at 100-480 m. Tokranov often found fish concentrated in areas of high-relief, rocky bottom — a common feature of the shelf edge in the Gulf of Alaska and Aleutian Islands regions. Such areas near the shelf break may be important prowfish habitat. Underwater videos taken in the north- east Gulf of Alaska by the Alaska Department of Fish and Game (Brylinsky 5 ) show numerous adult fish resting on or just above this type of substrate. Density was greater in the AI than in the GOA, over all bottom depths combined and in most cases by individual depth interval (Fig. 3). One reason may be that preferred habitat comprises a larger proportion of the Aleutian Is- 5 Brylinsky, C. 2000. Pers. commun. Alaska Department of Fish and Game, 304 Lake Street, Sitka, AK 99835. Smith et al.: Distribution and biology of Zaprora stlenus 177 lands area. Because of the lack of a relatively broad shelf in the region, a larger proportion of trawls are in or near areas of steep seafloor gradient and therefore likely over rough bottom (Fig. 2). Length distribution In both the Gulf of Alaska and the Aleutian Islands, few prowfish <40 cm in length were captured (Fig. 4). This paucity of small prowfish is not due to size selection by the trawl net mesh because the codend is lined with small mesh (1.3 cm stretched measure) webbing that retains small individuals of other species. A different explanation, based on the observations of Brodeur (1998) and Scheffer (1940), is that pre-adult prowfish are pelagic, remaining in proximity with large coelenterates and thus avoiding bottom trawls. Thus, the minimum capture length may indicate the length at which prowfish recruit to a demer- sal habitat. Our data showed no statistically significant length difference between sexes, in contrast with the data of Tokranov (1999) who suggested a length dimorphism where females are generally longer than males. Weight-length relationship The best-fitting model of weight versus length predicts that for any length, female prowfish are, on average, 3.7% heavier than males (Fig. 5). It seems unlikely that this relationship exists over all developmental stages because our samples were almost all adults and such a (relative) difference might not remain constant during all ontoge- netic sexual divergence. What is more certain is simply the existence of some small degree of length-weight dimorphism (females slightly heavier at a given length). Also, this dimorphism is not likely to stem primarily from a sexual difference in gonad weight because the maximum proportion of total female body weight composed of ovarian tissue was only 2.7%. Thus the difference is due to other morphological or behavioral differences. Growth There was no significant difference between sexes in length versus age. The predicted length of a prowfish of given age based on our samples was higher than that indicated by Tokranov (1999). In our study 5-year-old and 9-year-old fish averaged 56.6 cm and 73.5 cm in length, respectively. Tokranov (1999) considered that prowfish growth deter- mined from otoliths of 102 specimens from the Northwest Pacific indicated a comparatively fast-growing species reaching an average length of 44.6 cm by 5 years of age and 67 cm after 9 years. These data suggest prowfish are indeed relatively fast growing and that growth rates for the Gulf of Alaska are faster than those for off southeastern Kamchatka and the northern Kuril Islands. Alternatively, size-dependent mortality from such elements as incidental capture by commercial fishing may affect the two popula- tions differently. Historically, two other prowfish have been aged from otoliths: a male 84 cm long taken near Eureka, CA (Fitch and Lavenberg, 1971), and a female 50.1 cm long ( standard length) from off Monterey (Cailliet and Anderson, 1975). The ages estimated were 12 and 3 years, respectively. Af- ter converting the standard length record to an estimate of total length for the second specimen of 58 cm by using a ratio described by Baxter, 6 both lengths are slightly greater than our predictions for the same ages, albeit near the limits of our data range. This finding contrasts with the predictions of lesser length at a given age presented by Tokranov (1999). Maturity Little previous data exist with which to compare our obser- vations of female prowfish rate of maturation. Cailliet and Anderson (1975) examined the ovaries of their 50.1-cm 3- year-old female specimen for vitellogenesis and predicted an age at first spawning of 4 years, slightly less than the lower 95% confidence limit of 4.4 years for our expected average age at 50% maturity. Food habits Our observation that gelatinous zooplankton was the largest constituent in the contents of prowfish stomachs (Table 1) is supported by Tokranov ( 1999), who found that the two most common prey taxa among the contents of 102 stomachs of adult specimens from the northwestern Pacific were Scyphozoa (59.6-62.0% of stomachs) and Ctenophora (6.0-15.4% of stomachs). Anecdotal observations have also been made of the feeding behavior of an aquarium specimen over an approximate 2-year period (Carollo and Rankin, 1998). When first obtained, the fish ate only various jel- lyfish species, rejecting other food, including a variety of live invertebrates. In our food samples, we observed other taxa, such as invertebrates and small fish, but these were a minor part, possibly first captured by jellyfish and then sec- ondarily ingested by prowfish. Carollo and Rankin (1998) found that the aquarium specimen would ingest such items when eating the bells of Chrysaora melanaster in which such food had previously been placed, indicating the pos- sibility of this occurring naturally. Possibly more reflective of the unnatural circumstances, the specimen later began accepting such items outside the bells of jellyfish. Apparent adaptations of the prowfish to a diet of ge- latinous zooplankton include the small, sharp, close-set teeth in a single row attached only to the jaws, which are capable of a 180-degree gape, and the large rough-scaled lips (Clemens and Wilby, 1961; Hart, 1973; Carollo and Rankin, 1998). Acknowledgments We are grateful for the expert advice given by Alaska Fish- eries Science Center colleagues Delsa Anderl and Nancy 6 Baxter, R. 1990. Unpubl. manuscript. Annotated key to the fishes of Alaska, 803 p. [Available from Sera Baxter, Box 182, Seldovia, AK 99663.1 178 Fishery Bulletin 102(1) Roberson regarding age-reading of prowfish otoliths, and by AFSC colleagues Kathy Mier and Susan Piquelle regarding statistical analyses of data. Literature cited Allen, James M., and Gary B. Smith. 1988. Atlas and zoogeography of common fishes in the Bering Sea and Northeastern Pacific. NOAA Tech. Rep. NMFS 66, 151 p. Brodeur, R. D. 1998. In situ observations of the association between juve- nile fishes and scyphomedusae in the Bering Sea. Mar. Ecol. Prog. Ser. 163:11-20. Cailliet, G. M., and M. E. Anderson. 1975. Occurrence of prowfish Zaprora silenus Jordan, 1896 in Monterey Bay, California. Calif. Fish Game 61(l):60-62. Carollo, M., and P. Rankin. 1998. The care and display of the prowfish, Zaprora silenus. Drum and Croaker 29:3-6. Clemens, W. A., and G. V. Wilby. 1961. Fishes of the Pacific coast of Canada. Fish. Res. Board Can. Bull. 68, 2nd ed., 443 p. Chilton, D. E., and R. J. Beamish. 1982. Age determination methods for fishes studied by the groundfish program at the Pacific Biological Station. Can. Spec. Pub. Fish. Aquat. Sci. 60, 102 p. Doyle, M. J., K. L. Meir, M. S. Busby, and R. D. Brodeur. 2002. Regional variation in springtime ichthyoplankton assemblages in the northeast Pacific Ocean. Progress in Oceanography 53 (2-4):247-281 Eschmeyer, W. N, E. S. Herald, and H. Hammann. 1983. A field guide to Pacific Coast fishes of North America, 336 p. Peterson field guide ser. Houghton Mifflin, Boston, MA. Fitch, J. E., and R. J. Lavenberg. 1971. Marine food and game fishes of California, 179 p. U.C. Press, Berkeley, CA. Hart, J. L. 1973. Pacific fishes of Canada. Fish. Res. Board Can. Bull. 180, 740 p. Jordan, D. S. 1897. Notes on fishes little known or new to science. Proc. Calif. Acad. Sci., 2 nd sen, 6:203-205. Kessler, D. W. 1985. Alaska's saltwater fishes and other sea life: a field guide, 358 p. Alaska Northwest, Anchorage, AK Kimura, D. K. 1980. Likelihood methods for the von Bertalanffy growth curve. Fish. Bull. 77:765-776. Martin, M. H. 1997. Data report: 1996 Gulf of Alaska bottom trawl survey. NOAA Tech. Memo. NMFS-AFSC-82, 235 p. Matarese, A. C, A. W. Kendall, D. M. Blood, and B. M. Vinter. 1989. Laboratory guide to early life history stages of north- east pacific fishes. NOAA Tech. Rep. NMFS 80, 652 p. Nelson, J. S. 1994. Fishes of the world, 3 rd ed., 600 p. John Wiley, New York, NY.. Orlov, A. M. 1998. On feeding of mass species of deep-sea skates (Bathy- raja spp., Rajidae) from the Pacific waters of the Northern Kurds and Southeastern Kamchatka. J. Icthyol. 38(8): 635-644. Payne, S. A., B. A. Johnson, and R. S. Otto. 1999. Proximate composition of some north-eastern Pacific forage fish species. Fish. Oceanogr. 8(3): 159-177. Scheffer, V. B. 1940. Two recent records of Zaprora silenus Jordan from the Aleutian Islands. Copeia 1940(31:203. Seber, G. A. F 1973. The estimation of animal abundance, 506 p. Hafner Press, New York, NY. Tokranov, A. M. 1999. Some features of biology of the prowfish Zaprora silenus (Zaproridae) in the Pacific waters of the Northern Kuril Islands and Southeastern Kamchatka. J. Ichthyol. 39(61:475-478. Van Pelt, T I., J. F Piatt, B. K. Lance, and D. D. Roby. 1997. Proximate composition and energy density of some North Pacific forage fishes. Comp. Biochem. Physiol. 118A(4 1:1393-1398. Wakabayashi, K, R. G. Bakkala and M. S. Alton. 1985. Methods of the U.S.-Japan demersal trawl surveys. In Results of cooperative U.S.-Japan groundfish investiga- tions in the Bering Sea during May-August 1979 (R. G. Bakkala and K. Wakabayashi, eds.). p. 7-26. Int. North Pac. Fish. Comm. Bull. 44. Yang, Mei-Sun. 1993. Food habits of the commercially important ground- fishes in the Gulf of Alaska in 1990. NOAA Tech. Memo. NMFS-AFSC-22, 150 p. 179 Abstract— Our analyses of observer records reveal that abundance esti- mates are strongly influenced by the timing of longline operations in rela- tion to dawn and dusk and soak time — the amount of time that baited hooks are available in the water. Catch data will underestimate the total mortal- ity of several species because hooked animals are "lost at sea." They fall off, are removed, or escape from the hook before the longline is retrieved. For example, longline segments with soak times of 20 hours were retrieved with fewer skipjack tuna and seabirds than segments with soak times of 5 hours. The mortality of some seabird species is up to 45% higher than previously estimated. The effects of soak time and timing vary considerably between species. Soak time and exposure to dusk periods have strong positive effects on the catch rates of many species. In particular, the catch rates of most shark and billfish species increase with soak time. At the end of longline retrieval, for example, expected catch rates for broadbill swordfish are four times those at the beginning of retrieval. Survival of the animal while it is hooked on the longline appears to be an important factor determining whether it is eventually brought on board the vessel. Catch rates of species that survive being hooked (e.g. blue shark) increase with soak time. In contrast, skipjack tuna and seabirds are usu- ally dead at the time of retrieval. Their catch rates decline with time, perhaps because scavengers can easily remove hooked animals that are dead. The results of our study have impor- tant implications for fishery manage- ment and assessments that rely on longline catch data. A reduction in soak time since longlining commenced in the 1950s has introduced a systematic bias in estimates of mortality levels and abundance. The abundance of species like seabirds has been over-estimated in recent years. Simple modifications to procedures for data collection, such as recording the number of hooks retrieved without baits, would greatly improve mortality estimates. Manuscript approved for publication 22 September 2003 by Scientific Editor. Manuscript received 20 October 2003 at NMFS Scientific Publications Office. Fish. Bull. 102:179-195 (2004). Fish lost at sea: the effect of soak time on pelagic longline catches Peter Ward Ransom A. Myers Department of Biology Dalhousie University Halifax, B3H 4JI Canada E-mail address (for P Ward) wardiSmathstat.dal ca Wade Blanchard Department of Mathematics and Statistics Dalhousie University Halifax, B3H 44 Canada Our knowledge of large pelagic fish in the open ocean comes primarily from tagging and tracking experiments and from data collected from longline fish- ing vessels since the 1950s. Abundance indices for pelagic stocks are often derived from analyses that model catch as a function of factors such as year, area, and season. However, the amount of time that baited hooks are available to fish is likely to be another important factor influencing catch rates (Deriso and Parma, 1987). The activity of many pelagic animals and their prey vary with the time of day. Broadbill swordfish, for example, feed near the sea surface at night. They move to depths of 500 m or more during the day (Carey, 1990). Other species may be more active in surface waters during the day (e.g. striped marlin) or at dawn and dusk (e.g. oilfish). Longline fishing crews take a keen interest in the tim- ing of their fishing operations and soak time (the total time that a baited hook is available in the water). However, as- sessments have not accounted for those factors in estimating the abundance or mortality levels of target species or nontarget species. In many assessments that use pelagic longline catch rates, fishing effort is as- sumed to be proportional to the number of hooks deployed. The effects of soak time and timing may have been omit- ted because a clear demonstration of their effects on pelagic longline catch rates is not available. The few pub- lished accounts on soak time in pelagic longline fisheries have been based on limited data and a few target species. For example, in analyzing 95 longline operations or "sets" by research vessels Sivasubramaniam ( 1961) reported that the catch rates of bigeye tuna increased with soak time, whereas yellowfin tuna catch rates were highest in longline seg- ments with intermediate soak times. In contrast to the limited progress in empirical studies, theoretical approach- es are well developed for modeling fac- tors that may influence longline catch rates. Soon after large-scale longlining commenced. Murphy (1960) published "catch equations" for adjusting catch rates for soak time, bait loss, escape, hooking rates, and gear saturation. He suggested that escape rates could be es- timated from counts of missing hooks and hooks retrieved without baits. Unfortunately, such data are rarely col- lected from pelagic longline operations. More recently, hook-timers attached to longline branchlines have begun to provide information on the time when each animal is hooked and also whether animals are subsequently lost, e.g. Boggs (1992), Campbell et al. 1 - 2 Such data are particularly useful to under- 1 Campbell, R., W. Whitelaw, and G. Mc- Pherson. 1997. Domestic longline fish- ing methods and the catch of tunas and non-target species off north-eastern Queensland (1st survey: October-Decem- ber 1995). Report to the Eastern Tuna and Billfish Fishery MAC. 71 p. Aus- tralian Fisheries Management Authority, PO Box 7051, Canberra Business Centre, ACT 26 10, Australia. 2 See next page. 180 Fishery Bulletin 102(1) standing the processes affecting the probability of capture and escape. The purpose of our study is to determine whether varia- tions in the duration and timing of operations bias abun- dance and mortality estimates derived from longline catch rates. We present a theoretical model that is then related to empirical observations of the effects of soak time on catch rates. The strength in our approach is in applying a random effects model to large data sets for over 60 target and non- target species in six distinct fisheries. We also investigate the survival of each species while hooked because prelimi- nary analyses suggested that the effects of soak time on catch rates might be linked to mortality caused by hooking (referred to as "hooking mortality"). Factors affecting catch rates To aid interpretation of our statistical analysis of soak time effects, we first developed a simple model to illustrate how the probability of catching an animal may vary with soak time. The probability of an animal being on a hook when the branchline is retrieved is a product of two probability density functions: first the probability of being hooked and then the probability of being lost from the hook. 3 In- fluencing the probability of being hooked are the species' local abundance, vulnerability to the fishing gear, and the availability of the gear. Catches will deplete the abundance of animals within the gear's area of action, particularly for species that have low rates of movement. Movement will also result in variations in exposure of animals to the gear over time — for instance, as they move vertically through the water column in search of prey (Deriso and Parma, 1987). Other processes that will reduce the probability of be- ing hooked include bait loss and reduced sensitivity to the bait (Ferno and Huse, 1983). Longline baits may fall off hooks during deployment, deteriorate over time and fall off or they may lose their attractant qualities. They may be removed by target species, nontarget species, or other ma- rine life, such as squids. Hooked animals may also escape by severing the branchline or breaking the hook. Sections of the longline may become saturated when animals are hooked, reducing the number of available baits (Murphy. 1960; Somerton and Kikkawa, 1995). After an animal has been hooked, it may escape, fall off the hook, be removed by scavengers, or it may remain hooked until the branchline is retrieved. Some of the processes affecting the probability of an ani- mal being on a hook when the the branchline is retrieved 2 Campbell, R., W. Whitelaw, and G. McPherson. 1997. Do- mestic longline fishing methods and the catch of tunas and non- target species off north-eastern Queensland (2nd survey: May- August 1996). Report to the Eastern Tuna and Billfish Fishery MAC, 48 p. Australian Fisheries Management Authority, PC) Box 7051, Canberra Business Centre, ACT 2610, Australia. In discussing continuous variables we use the terms "proba- bility" and "probability density function" interchangeably. are species-specific, whereas other processes may affect all species. For example, bait loss during longline deployment will reduce the catch rates of all species. In contrast, the probability of a hooked animal escaping may be species-de- pendent; some species are able to free themselves from the hook whereas other species are rarely able to do this. Our simple model of the probability of an animal being on a hook is based on a convolution of the two time-related processes described above: 1) the decay in the probability of capture with the decline in the number of baits that are available; and 2) gains due to the increased exposure of baits to animals and losses due to animals escaping, falling off, or being removed by scavengers. The probability of an animal being on a hook when the branchline is retrieved is the integral of the probability density functions of capture and retention: rtT) = J P(t)P r lT-t)dt, (1) where jriT) = the "catch rate" or probability of an animal being on a hook when the branchline is retrieved at time T (T is the total soak time of the hook); P ( it) = the probability density function of an animal being captured at time t; and P r (t) = the probability density function of a cap- tured animal being retained on the hook for a length of time f. The probability density function of capture can be approxi- mated with an exponential function: Pit) = P e-", (2) where P = the probability of capture when the hook is deployed (r=0); and o = a parameter determining the rate of change in capture probability over time. After the animal is hooked, the probability density function of an animal being retained after capture can be approxi- mated as PIt) = e- pw , (3) where /I = the "loss rate," a parameter determining the rate of change in the probability of an animal being retained after it has been captured. Substituting approximations 2 and 3 into Equation 1 gives 7l(T)= \P e '"e <"' ' dt (4) /?-«' Ward et al.: The effect of soak time on pelagic longlme catches 181 Seabirds (-0.06) p c\i (XX) Skipjack (-0.04) () () (> <> ° () o () O 5 10 15 20 25 5 10 15 20 25 <) <) O O o C) °<»' j (X) o o o o° Lancetfish (-0.02) in Swordfis h (M (+0.09) o . <>°o 0 e.g. swordfish Losses eventually exceed captures Soak time coefficient <0 e.g. skipjack Captures balance losses Soak time coefficient -0 eg lancetfish 20 Figure 2 Illustration of different patterns in the theoretical relationship between longline catch rates and soak time. The probability of an animal being on a hook when a branchline is retrieved (the "catch rate") is estimated from Equation 4 by using soak times iT) ranging from to 20 hours and three different combinations of values forP n (probability of capture), « (capture rate), and /3 (loss rate). For seabirds, the probabilities were estimated from Equation 6. The probabilities are not on the same scale for all species. Another approach might be to fit separate logistic regres- sions to each operation and then to combine the parameter estimates. This would overcome the problems of normality and homogeneity of variance. However, the separate re- gressions would not incorporate information that is com- mon to all operations. Instead, we used a logistic regression with random ef- fects. The key advantage in using random-effects models in this situation is that they carry information on the cor- relation between longline segments that is derived from the entire data set of operations. Data and methods Fisheries We analyzed observer data from six different fisheries in the Pacific Ocean to determine the effects of soak time and timing on longline catch rates (Table 1, Fig. 3). These fisheries involve two different types of longline fishing operation: 1 ) distant-water longlining involves trips of three months or longer and the catch is frozen on board the vessel; and 2) fresh-chilled longlining, which involves small vessels (15-25 m) undertaking trips of less than four weeks duration, and the catch is kept in ice, ice slurries, or in spray brine systems. The fresh-chilled longliners deploy shorter longlines with fewer hooks (-1000 hooks) than the distant-water longliners (-3000 hooks per operation) (Ward, 1996; Ward and Elscot, 2000). The six fisheries share many operational similarities, such as the types of bait used and soak time. However, they are quite different in terms of targeting, which is determined by fishing practices, e.g. the depth profile of the longline, timing of operations and the area and season of activity. South Pacific bluefin tuna longliners operate in cold waters ( 10-16°C) in winter to catch southern bluefin tuna. In the South Pacific yellowfin tuna longliners tar- get tropical species, such as yellowfin and bigeye tuna, in warmer waters (19-22°C) (Ward, 1996). To target bigeye tuna, longlines in the Central Pacific bigeye fishery are deployed in the early morning with hook depths ranging down to about 450 m. The depths of the deepest hook are much shallower (-150 m) in the North Pacific swordfish fishery where the longlines are deployed late in the after- noon and retrieved early in the morning (Boggs, 1992). Ward et al.: The effect of soak time on pelagic longline catches 183 Observer data National authorities and regional organizations placed independent observers on many longliners operating in the six fisheries during the 1990s. The observer data consisted of records of the species and the time when each animal was brought on board. We restricted analyses to operations where the last hook that had been deployed was retrieved first ("counter- retrieved"), where there was no evidence of stoppages due to line breaks or mechanical failure, and where there was continuous monitoring by an observer. Combined with records of the number of hooks deployed and start and finish times of deployment and retrieval, the observer data allowed calculation of soak time and catch rates of longline segments. We aggregated catches and the number of hooks into hourly segments. The soak time was estimated for the midpoint of each hourly segment. The Central Pacific bigeye tuna and North Pacific sword- fish fisheries differed from the other four fisheries in the species that were recorded and the method of recording the time when each animal was brought on board. Observ- ers reported catches according to a float identifier in the Central and North Pacific fisheries. Therefore we estimated soak times for each longline segment from the time when each float was retrieved. For those fisheries, observers re- ported the float identifier only for tuna, billfish, and shark (Table 2). Data are available for protected species, such as seals, turtles, and seabirds but were not sought for the present study. We assumed a constant rate of longline retrieval throughout each operation. The number of hooks retrieved during each hourly segment was the total number of hooks divided by the duration of monitoring (decimal hours). For each species we analyzed only the operations where at least one individual of that species was caught. Longline segments that involved a full hour of monitor- ing had several hundred hooks. Segments at either end of the longline involved less than an hour of monitoring and had fewer hooks. Catch rates may become inflated in segments with very small numbers of hooks. Therefore we arbitrarily excluded segments where the observer moni- tored less than 25 hooks. For four of the fisheries, data were available on survival rates, allowing the investigation of the relationship be- tween soak time and hooking mortality. For the Western Pacific and South Pacific fisheries, observers reported whether the animal was alive or dead when it was brought on board. We calculated survival rate (the number alive divided by the total number reported dead or alive) for spe- cies where data were available on the life status of more than ten individuals. Generalized linear mixed model Logit model We applied a generalized linear mixed model to the observer data. The model is based on a logis- tic regression, with the catch (y) on each hook assumed to have a binomial distribution with y ~ b(ra, n). n is the expected value of the distribution for a specified soak time. We refer to it as the probability of catching an animal or •s ■$ CD CO c "2 ° CJ ■2 2 •- ° 5. o J! Or'* B a -S o ^H CO CO o o CO CJ 8. " lO CM CM CO ^f CM Cfi a "in o ^ o 2 O o X - ^ CJ o g co >-* o ° C O <3J tG •*-» — t_ - • , — 1 05 , — I CN CM CM t- a. a> CM ,—1 CM CM CM CM o » "3 =3 CO .—1 cd & Q >> u CO -- ■m-h o O C c -C „ o co O en 3 6 £ S M u '43 CM lO o t> O CO cc OQ}C3 rH CD , C8 2 CD 3 2 bp cd a> CO en CO lO ■* a> CD IS i -C '.2 CO ■* rH CO ,— i CD £ +* 6 es P. lO CM Ol CM ■* CD cfl to ,o ~ CO ^ "cfl O QJ o u "-J3 b C nj ™ CM CM ^H ,H a; a» S O O O O a £ t3 o o o o r- t> cu _c c o CC ° x o "C CM 4 CM 4 CM 1 o 1 O <3i 1 CM 03 1 CM Ph O) en ai o> 05 OS o c « .2 to en o> o> Ol cn ai CO +J o CO „, CtJ u 2 cO c CO c CO C o en 3 3 3 c C M " a .2 +j -M cu ■5 c c CD CO CD Lh * * >> c -P a cd c X - CO C cC CO 0) "o , >> CO a CD _3 o CO" CO" CO" 3 m Table er oper ?rn Pac CD i-. H X CO cC •a u O c 3 CJ CD d 3 CD CU c 3 *-> CD >> CD 4^ c cC o X c u CD X +a 3 V r- CD -C o, .^ CU3 be bo w en CD O cC CO (Tj CO X X X >> CO ■g* CO he mean number of ho perations. For the two and SP = South Pacific. CO CO -c X t- u CO CO CO 1 CO CD 3 o S3 'cj CO cu X +J S- O 2: u S3 CO "3 a o CJ S3 o CO Oh 0) CO 1 CJ CC 'u CO Oh C CD *J CO 1 3 < C u CD -4-> CO CO CD X -tJ u o c 3 CO 5 CO o tj -" > c CD 2 cj X o -a J2 Cr CD CO c CO c CO ±3 fisheries the total : 1 Pacific; \ X CO CD a -e CO £2 ary of the er data, a: ; CP = Cen s a c X to cC ■a s- o "cO C 3 cu >, CO a 3 CU >> CD bo X Ph +3 c CO c 3 C CC •s o CO a 3 +3 c cC CD C cu CO _; Summ observ Pacific Ir 0) XI en E CO Oh 2 X cm O ■3 "CD >> Oh cn _3 X Oh CO 3 .2 184 Fishery Bulletin 102(1) North Pacific Swordfish o o eg Western Pacific Bigeye o CM I o I Western Pacific Bigeye Western Pacific Distant South Pacific Yellowfin South Pacific Bluefin — I — 140 T T 160 220 180 200 Longitude (degrees) Figure 3 Geographical distribution of the observer data analyzed for each fishery. 240 the expected number of animals per hook. For each longline segment (j) within each operation (£), we link jr to a linear predictor ( ?; ( ) through the equation rjj is then modeled as a function of soak time: r?y = ft+AT y , (5) where T tJ = the hook's soak time (decimal hours) in long- line segment j; P = the intercept; and /3j = the slope coefficient, which we term the "soak time coefficient." Modeling the probability of a catch on each individual hook would result in large numbers of zero observations and thus test the limits of current computer performance. Therefore we aggregated hooks and catches into hourly segments for each longline operation. We assumed that each longline segment had the same configuration and that the probability of capture was the same for each segment within a longline operation. The assumption may be violated where segments pass through different water masses or where they differ in depth profile or baits. Saturation of segments with animals will also al- ter the capture probability between segments. The effects of water masses, depth profiles, baits, and gear saturation were not analyzed in the present study. Capture probability may also vary through the differen- tial exposure of segments to the diurnal cycle of night and day. The addition of dawn and dusk as fixed effects allowed us to model diurnal influences on catch rates. Fixed effects To explore factors that might affect the rela- tionship between soak time and catch rate, we added four fixed effects to the logit model: year, season, and, as men- tioned above, whether the segment was available at dawn or dusk. A full model without interaction terms would be iu = A. + /Wj + AA> + PAi + PAj + P* Y u + °- where 7 1 , = the hook's soak time (decimal hours) in long- line segment j; A t = an indicator of whether the hook was exposed to a dawn period; P = an indicator of whether the hook was exposed to a dusk period; S: , = the season (winter or summer); Y- = the year; O i = the random effect for operation that we mod- eled as an independent and normally distrib- uted variable (see "Random effects" section); and )3 -/3 4 are parameters (fixed effects) to be estimated. We refer to fi x as the "soak time coefficient." Ward et al.: The effect of soak time on pelagic longline catches 185 Table 2 List of common and scientific names of the species analyzed. Also shown is the number of individuals of each species analyzed in each fishery. A dash indicates that the species was not analyzec in the present study it does not necessarily mean that the spe- cies was not taken in the fishery. In particular, observer data on the time of capture were not aval lable for 'other bony fish" in the North Pacific swordfish and Centra] Pacific bigeye tuna fisheries . NP = North Pacific; CP = Central Pacific WP = Western Pacific; SP = South Pacific; LN = long- nosed; and SN = short-nosed. Fishery CP WP SP SP NP bigeye bigeye WP yellowfin Bluefin Common name Species swordfish tuna tuna distant tuna tuna Tuna and tuna-like species Albacore Thunnus alalunga 9707 23,128 14,194 11,976 21,550 1399 Bigeye tuna 77? annus obesus 5409 45,476 9814 2581 1846 - Butterfly mackerel Gasterochisma melumpus — — — — — 533 Skipjack tuna Katsuwonus pelamis 546 13,882 1456 445 691 — Slender tuna Allothunnus fallai — — — — — 28 Southern bluefin Thunnus maccoyii — — — — 1030 10.537 Yellowfin tuna Thunnus albacares 2811 21,654 16,029 4689 12,454 — Wahoo Acanthocybium solandri 383 5508 1345 — 308 — Billfish Black marlin Makaira indica 25 41 353 226 160 — Blue marlin Makaira nigricans 981 2379 1467 529 179 — Sailfish Istiophorus platypterus 49 193 706 399 151 — Shortbill spearfish Tetrapturus angustirostris 543 5467 529 398 654 — Striped marlin Tetrapturus audax 1963 8332 681 182 724 — Swordfish Xiphias gladius 22,457 1680 1472 287 1173 92 Other bony fish Barracouta Thyrsites atun — — — — 53 — Barracudas Sphyraena spp. — — 707 153 — — Escolar Lepidocybium flavubrunneum 1208 3983 1343 878 1726 84 Great barracuda Sphyraena barracuda 32 743 303 442 92 — Lancetfish (LN) Alepisaurus ferox 2788 30,136 325 419 2868 610 Lancetfish(SN) Alepisaurus brevirostris — — 155 84 257 59 Lancetfishes Alepisaurus spp. — — 1431 98 — — Long-finned bream Taractichthys longipinnis — — — — — 292 Mahi mahi Coryphaena hippurus 17,463 19,090 1436 211 447 — Oilfish Ruvettus pretiosus 555 1091 420 456 653 900 Opah Lampris guttatus 68 4724 527 129 80 213 Pomfrets Family Bramidae — — 623 60 — 40 Ray's bream Brama brama — — — — 1074 10,547 Ribbonfishes Family Trachipteridae — — — — — 22 Rudderfish Centrolophus niger — — — — — 90 Sickle pomfret Taractichthys steindachneri — — 122 21 — — Slender barracuda Sphyraena jello — — — — 121 — Snake mackerel Gempylus serpens 1971 9881 256 44 — — Snake mackerels Family Gempylidae — — 456 10 — — Southern Ray's bream Brama spp. — — — — — 28 Sunfish Mola ramsayi — — — — 249 99 Sharks and rays Bigeye thresher shark Alopias superciliosus 149 1930 145 61 — — Blacktip shark Carcharhinus limbatus — — 445 125 — — Blue shark Prionace glauca 31,503 31,413 5601 1628 1689 12.797 Bronze whaler Carcharhinus brachyurus — — — — 116 — Crocodile shark Pseudocarcharias kamoharai 153 73 continued 186 Fishery Bulletin 102(1) Table 2 (continued) Fishery CP WP SP SP NP bigeye bigeye WP yellowfin Bluefin Common name Species swordfish tuna tuna distant tuna tuna Sharks and rays (continued) Dog fishes Family Squalidae — — — — — 60 Dusky shark Carcharhinus obscurus — 112 — — 20 — Grey reef shark Carcharhinus amblyrhynchos — — 282 64 — — Hammerhead shark Sphyrna spp. — — 142 191 22 — Long finned mako Isurus paucus — 83 108 15 — — Oceanic whitetip shark Carcharhinus longimanus 568 2373 2376 384 142 — Porbeagle Lamna nasus — — — — 27 1011 Pelagic stingray Dasyatis violacea 2374 2849 1212 248 534 109 Pelagic thresher shark Alopias pelagicus — — 77 34 — — School shark Galeorhinus galeus — — — — — 143 Short finned mako Isurus oxyrinchus 476 685 408 169 432 128 Silky shark Carcharhinus falciformis 25 1433 5396 2406 8 — Silvertip shark Carcharhinus albimarginatus — — 168 74 — — Thintail thresher shark Alopias vulpinus — 74 — — — 31 Thresher shark Alopias superciliosus — — 415 — 93 18 Tiger shark Galeocerdo cuvier — — 56 18 38 — Velvet dogfish Zameus squamulosus — — — — — 156 Whip stingray Dasyatis akajei — — 78 15 — — Seabirds Albatrosses Family Diomedeidae — — — — — 88 Petrels Family Procellariidae — — — — — 29 Other seabirds Family Procellariidae — — — — 38 200 All operations 104,054 238,340 73,212 30,222 51,699 40,343 To maintain a focus on the effects of soak time, the models were limited to simple combinations of fixed effects and interaction terms. Dawn and dusk were added to various models of each species in each fishery. To reduce complex- ity, year and season were limited to models of seven spe- cies (bigeye tuna, oilfish, swordfish, blue shark, albacore, southern bluefin tuna, long-nosed lancetfish) in the two South Pacific fisheries. The seven species represented four taxonomic groups and the full range of responses observed in preliminary analyses of the soak-time-catch- rate relationship. Random effects We added random effects to all models to allow catch rates of segments within each longline opera- tion to be related. The random effects model assumes that there is an underlying distribution from which the true values of the probability of catching the species, jt, are drawn. The distribution is the among-operation varia- tion or "random effects distribution." The operations are assumed to be drawn from a random sample of all opera- tions, so that the random effects (0 ( ) in the relationship between catch rate and soak time for each operation (i) are independent and normally distributed with 0~N(Q, a 2 ). The random effects and various combinations of the fixed effects were added to the linear predictor presented in Equation 5. For each species in the South Pacific yellowfin tuna data set we compared the performance of models under an equal correlation structure with that of models under an autoregressive correlation structure. Under an au- toregressive structure, catch rates in the different hourly segments within the operations are not equally correlated. For example, the correlation between segments might be expected to decline with increased time between seg- ments. However, we used an equal correlation structure for all models because the Akaike's information criterion (AIC) and Sawa's Bayesian information criterion (BIO indicated that there was no clear advantage in using the autoregressive structure rather than an equal correlation structure. Implementation We implemented the models in SAS (version 8.0) using GLIMMIX, a SAS macro that uses iteratively reweighted likelihoods to fit generalized linear Ward et al.: The effect of soak time on pelagic longline catches 187 Seabirds Other fish Tuna Billfish Sharks i -0.2 SP Bluefin — « — Other seabirds (1 07) -Albatross (0-99) Petrel (1.17) — Lancetfish(SN)(1) "Opah(1 .03) Pomfret(1 16) -Lancetfish(LN)(1.02) Southern Ray's bream (0.96) "© — Long finned bream (111) ^Ray's bream (2.47) — © Sunfish (0.97) © Ribbonfish (0.93) Seabirds Other fish e Rudderfish (0.89) © Escolar (0.66) -e-Oilfish (0.98) -e-Albacore (0.94) Slender tuna (0.9) "-Butterfly mackerel (0.93) e Southern bluefin (1.4) —©—Swordfish (0 9) — Thintail thresher shark (0.88) — Mako (0.93) ©Blue shark (1 87) -©"Porbeagle (0.92) -© Ray (0.89) Tuna Billfish - Sharks — I — 0.0 "I 0.2 SP Yellowfin © — ; Other seabirds (1.26) — © iBarracouta (0.99) — © — 'Slender barracuda (0.98) ©-?— Opah (0.99) -©iancetfish (LN) (1 14) -s-Mahi mahi (1.09) — «r-Lancetfish (SN) (0.96) © Great barracuda (0.95) : -e- Ray , s bream (1.71) — e — Sunfish (0.99) ; — e— Oilfish (1.23) -©"Escolar (1.33) -©"Skipjack (1 .06) ©Yellowfin (2.33) —f 3 — Southern bluefin (2.2) ©Albacore(2.12) -r 6 — Wahoo (0.96) -®-Bigeye(1 16) — © — Sailfish (1 03) — 9 — Blue marlin (0.88) r - e -Shortbill spearfish (0.99) :— e — Black marlin (0.92) -©-Striped marlin (0.94) -©"Swordfish (0.85) ©i Porbeagle (0.87) j-e Silky shark (0.86) Tiger shark (0.87) "Mako (1.06) -Ray (0 99) > — Bronze whaler (0.95) © — Oceanic whitetip (0.99) ©-Blue shark (0.99) © Hammerhead (0.93) © Dusky shark (0.85) -0.2 Soak time coefficient 0.0 0.2 Figure continued on next page. Figure 4 Coefficients for the effect of soak time on the catch rates of the most abundant species in each fishery. The coefficients are from random effects models where soak time is the only factor. Horizontal bars are 95% confidence intervals for the estimated coefficient. The dispersion parameter is shown in parentheses (it is 1.00 for species that are distributed as predicted by the model, but may be higher for species that have a more clumped distribution along the longline). mixed models (Wolfinger and O'Connell, 1993). To judge the performance of the various model formulations, we checked statistics, such as deviance and dispersion, and examined scatter plots of chi-square residuals against the linear predictor I rj) and QQ plots of chi-square residuals. We used the AIC and BIC to compare the performance of the various model formulations. Variance in the binomial model depends on only one pa- rameter, P. A dispersion parameter is therefore necessary to allow the variance in the data to be modeled. In effect, the dispersion parameter scales the estimate of binomial variance for the amount of variance in the data. The disper- sion parameter will be near one when the variance in the data matches that of the binomial model. Values greater than one ("over-dispersion") imply that the species may have a clumped distribution along the longline. Results Soak time For most species, soak time had a positive effect on catch rates (Fig. 4). In addition to being statistically significant, the effect of soak time made a large difference to catch rates at opposite ends of the longline. In the South Pacific yellowfin tuna fishery, for example, the expected catch rates of swordfish can vary from 0.6 (CI ±0.1) per 1000 hooks (5 hours) to 1.9 (CI ±0.3) per 1000 hooks (20 hours) (Table 3). A soak time of 5 hours and 3500 hooks (if that were possible) would result in a total catch of about two swordfish. In contrast, almost seven swordfish are expected from a longline operation of the same number of hooks with 20 hours of soak time. 188 Fishery Bulletin 102(1) WP Bigeye WP Distant Other fish Tuna Billfish - Sharks -0.2 Great barracuda (0.94) -Mahi mahi(1.15) -«— Lancetfish (LN) (0.99) Lancetfish (SN) (0.97) e — Snake mackerel (1.06) -Barracudas (0.96) *- Opah (11) ■9-Escolar (0.97) -9 Sickle pomfret (1 .2) -e-Pomfret (0.99) - &— Escolars (1.07) — ° — OHfish (1.12) -^Skipjack (1 12) ■«-Wahoo(1) ?Yellowfin (1.61) : e Albacore(1.45) ! e Bigeye(1.18) tShortbill spearfish (0.98) -^Swordfish (1.04) _e_ Stnped marlin (1.23) — e— Sailfish (1.51) — e — Black marlin (1.32) -o-Blue marlin (1.14) Hammerhead (0.87) Grey reef shark (1 .49) 1 Pelagic thresher shark (1.16) ■® Bigeye thresher shark ( 1 .06) -° Tiger shark (1) Other fish - Pomfret (1.43) -Mahi mahi (1.45) Lancetfish (LN) (1.02) e— Great barracuda (0.84) — e Opah (1.24) e Barracudas (0.97) — e — — Sickle pomfret (2.13) Escolar (1.15) -Lancetfish (SN) (0 84) Snake mackerel (3.56) -Ollfish (1.17) Tuna Billfish -e Sllvertip shark (1.17) ■Q-Silky shark (115) -6— Thresher sharks (0.88) -s— Short finned mako (0.91 ) "^Pelagic stingray (0.92) "Long finned mako (0 96) Sharks -° — Blacktip shark (1.3) 9 Blue shark (0.93) -^Oceanic whitetip (0.91) e Whip stingray (1 .37) e Crocodile shark (1 .2) 0.0 I 0.2 Skipjack (0.91) Wahoo (0.97) e-Yellowfin (2.02) & Albacore(1.51) - e "Bigeye(1.32) ■Black marlin (0.89) Striped marlin (1.19) — Shortbill spearfish (1.17) -°— Sailfish (1 .04) -° — Swordfish (0.89) — s— Blue marlin (0 98) Tiger shark (1.2) — Crocodile shark (0.95) Hammerhead (0 88) Whip stingray (1.01) Sllvertip shark (1 .46) ■Blue shark (0.95) Blacktip shark (0.91) -e-Silky shark (1.5) e Pelagic stingray (1) e Oceanic whitetip (1 .06) "Pelagic thresher shark (1.81) -Bigeye thresher shark (1.17) "Short finned mako (0.91) -0.2 0.0 0.2 Soak time coefficient Figure 4 (continued) For some species (e.g. seabirds, skipjack tuna, and mahi mahi), soak time had a negative effect on catch rates that was often statistically significant (Fig. 4). For skipjack tuna in the Western Pacific distant fishery, for example. catch rates decreased from 1.3 (CI ±0.2) per 1000 hooks for a soak time of 5 hours to 1.0 (CI ±0.1) per 1000 hooks (20 hours). Soak time had a small or statistically insignifi- cant effect on catch rates for several species, such as yel- lowfin tuna and shortbill spearfish. Fixed effects Exposure to dusk had a positive effect on the catch rates for most species (Fig. 5). Dusk often had a negative effect on the catch rates of billfish, such as striped marlin and sailfish. For most species, however, the effect of dawn was weaker, and it influenced the catch rates of fewer species. Like soak time, timing made a substantial difference to catch rates (Table 4). For a soak time of 12 hours in the South Pacific yellowfin fishery, for example, longlinc seg- ments exposed to both dawn and dusk have a catch rate of 2.0 (CI ±0.5) escolar per 1000 hooks. The catch rate is 0.8 (CI ±0.1) per 1000 hooks for segments that were not exposed to dawn or dusk. The effects of timing on catch rates were most pro- nounced in the South Pacific bluefin tuna fishery. The fishery also showed the greatest range in soak time coef- ficients, and the coefficients tended to be larger than those of other fisheries (Fig. 4). Separately, the fixed effects often had statistically signifi- cant relationships with catch rates of the seven species that we investigated in detail. However, the interaction between soak time and each fixed effect was less frequently signifi- cant. Season was significant, for example, in none of the six models that included a soak-time-season interaction term. By comparison, season was significant in six of the 18 models that included season as a factor but not with a soak-time-season interaction term. The effect of soak time was not significant for southern bluefin tuna in any model for the South Pacific bluefin tuna fishery. It was significant Ward et al.: The effect of soak time on pelagic longline catches 189 Tuna NP Swordfish h Blgeye (0 94) 3 Pacific bluefin (0.95) CP Bigeye Billfish Sharks Tuna *— Skipjack (0-84) -s-Yellowfin (0 87) ^Albacore (1.03) Slue marlin (0.91) — Shortbill spearfish (0.93) "Swordfish (0 96) -°-Striped marlin (0.88) e Sailfish (0 96) Billfish -Salmon shark (0.96) "° — Oceanic whitetip (0.98) " e Crocodile shark (0 89) - e — Short finned mako (0 95) e Blue shark (0.96) e Bigeye thresher shark (0.83) Sharks -0.2 0.0 — I 0.2 -0.2 Soak time coefficient Figure 4 (continued) ^Skipjack (0.85) e Albacore (0.81) e Yellowfin (0.93) bigeye (0.88) Black marlin (0.89) e Stnped marlin (0 86) ■^Shortbill spearfish (0 89) "^Blue marlin (0.86) — e Sailfish (1.05) "^Swordfish (0.9) — Sandbar shark (1.24) e Bignose shark (1.19) _e— Short finned mako (0.94) e Blue shark (0 81) -e-Silky shark (0.93) -° — Pelagic thresher shark (0.88) "^Oceanic whitetip (1.01) "^Bigeye thresher shark (0.86) e Long finned mako (0.86) e Thintail thresher shark (0.9) 0.0 "Dusky shark (1.05) -°— Crocodile shark (0.89) I 0.2 in 36 of the 48 models for the other six species. We con- cluded that the fixed effects modified the intercept of the soak-time-catch-rate relationship, but they rarely altered the slope of the relationship. Akaike's information criterion (AIC) and Sawa's Bayes- ian information criterion (BIC ) both indicated that models with soak time as the only variable were the most or second most parsimonious model. This was the case for all models, except for several models of albacore and long-nosed lan- cetfish. Therefore the following discussion concentrates on the effects of soak time and timing on catch rates. Discussion In considering results of the random effects models, we examined patterns in the effects of soak time and timing among taxonomic groups, the mechanisms that may cause the patterns, and their implications. First, however, we investigated whether the effects were consistent for the same species between fisheries. Comparison of fisheries The effect of soak time was consistent for several spe- cies between the fisheries, despite significant differences in fishing practices and area and season of activity. For example, the soak time coefficients for species in the South Pacific yellowfin tuna fishery were very similar to those of the same species in the Central Pacific bigeye tuna fishery (r=0.79) (Fig. 6). Several species had a narrow range of soak time coef- ficients over all the fisheries analyzed. Estimates of the coefficient of yellowfin tuna, for example, ranged from 0.00 (CI ±0.01) in the South Pacific yellowfin fishery to 0.04 ( CI ±0.0 1 ) in the North Pacific swordfish fishery. A coefficient of 0.04 is equivalent to a difference of 1.3 yellowfin tuna per 1000 hooks between longline segments with soak times of 5 and 20 hours. The range in coefficients is also small for other abundant and widely distributed species, such as al- bacore (r=0. 00-0.05) and blue shark (r=0.01-0.05). For many species, however, the correlation between soak- time coefficients from different fisheries was poor (Fig. 6). 190 Fishery Bulletin 102(1) Table 3 Examples of the effect of soak time on expected catch rates of species in the South Pacific yellowfin tuna ishery. The expected catch rates i number per 1000 hooks I are predicted from the soak-time coefficient for each species for longline segments exposed to a dusk period with a soak time of 5 or 20 hours. Figu re 4 shows the 95% confidence intervals for soak-time coe fficients used to calculate the expected catch rates. LN = ong-nosed; SN = short-nosed. Species Soak time h) 5 20 Tuna and tuna-like species Albacore 15.5 13.4 Bigeye tuna 1.1 2.3 Skipjack tuna 1.3 1.0 Southern bluefin tuna 5.2 5.5 Yellowfin tuna 8.4 7.7 Billfish Black marlin 0.4 1.6 Blue marlin 1.2 0.4 Sailfish 0.8 1.0 Shortbill spearfish 1.0 1.6 Striped marlin 0.8 1.0 Swordfish 0.6 1.9 Other bony fish Barracouta 0.8 0.7 Escolar 0.8 3.1 Great barracuda 0.9 1.1 Lancetfish (LN) 2.7 2.4 Lancetfish (SN) 1.6 1.4 Mahi mahi 1.0 0.9 Oilfish 0.8 2.2 Opah 0.7 0.5 Ray's bream 1.8 2.0 Slender barracuda 1.7 1.6 Sunfish 0.6 1.3 Wahoo 1.0 1.1 Sharks and rays Blue shark 1.1 2.0 Bronze whaler 0.7 0.8 Dusky shark 0.4 0.8 Hammerhead 0.2 1.8 Mako 0.6 0.8 Oceanic whitetip 0.5 0.9 Porbeagle 1.2 1.1 Pelagic stingray 0.9 1.2 Thresher shark 0.6 1.0 Tiger shark 0.5 0.5 Table 4 Examples of the effect of timing on expected catch rates of species in the South Pacific yellowfin tuna fishery. The expected catch rates (number per 1000 hooks I are pre- dicted from the soak-time coefficient for each species for a longline operation with a soak time of 12 hours. The differ- ent catch rates are for longline segments exposed to nei- ther the dawn or dusk period, for dawn only, and for dawn and dusk periods. LN = long-nosed; SN = short-nosed. Period Neither Dawn Dawn Species period only + dusk Tuna and tuna-like species Albacore 12.3 14.0 16.5 Bigeye tuna 0.9 1.2 2.1 Skipjack tuna 1.4 1.2 1.0 Southern bluefin tuna 3.8 2.9 4.1 Yellowfin tuna 7.7 7.6 8.0 Billfish Black marlin 1.2 0.6 0.4 Blue marlin 0.4 1.0 1.4 Sailfish 0.8 0.7 0.7 Shortbill spearfish 1.3 0.9 0.9 Striped marlin 0.8 0.9 0.9 Swordfish 0.5 0.7 1.3 Other bony fish Barracouta 1.1 1.2 0.7 Escolar 0.8 1.0 2.0 Great barracuda 1.0 0.8 0.8 Lancetfish (LN) 2.8 2.7 2.5 Lancetfish (SN) 1.2 1.1 1.3 Mahi mahi 1.2 1.3 1.1 Oilfish 0.8 1.1 1.8 Opah 0.5 0.5 0.6 Ray's bream 0.8 0.7 1.6 Slender barracuda 2.0 1.5 1.2 Sunfish 0.8 0.6 0.7 Wahoo 1.2 1.3 1.1 Sharks and rays Blue shark 1.3 1.4 1.4 Bronze whaler 0.6 0.9 1.0 Dusky shark 0.1 0.1 0.6 Hammerhead 0.4 0.2 0.3 Mako 0.7 0.8 0.8 Oceanic whitetip 0.7 0.8 0.7 Porbeagle 1.0 0.6 0.6 Pelagic stingray 0.9 0.9 1.1 Thresher shark 0.6 0.6 0.7 Tiger shark 0.4 0.5 0.7 For a few species (e.g. tiger shark) the poor correlation may have been a function of small sample sizes and the wide confidence intervals of the estimates. For other species the estimates were well determined, yet poorly correlated, e.g. the coefficient for short-nosed lancetfish was 0.09 (CI ±0.05) in the Western Pacific distant fishery compared to 0.01 (CI ±0.04) in the Western Pacific bigeye tuna fishery. Therefore, we urge caution in applying our estimates to the same species in longline fisheries in other areas. Ward et a!.: The effect of soak time on pelagic longlme catches 191 SP Yellowfin WP Bigeye o dusk preference dawn & dusk ^ - dusk preference dawn & du>k • Raj 's bream • • Swordfish C3 • o Oilfish . Hammerhead 4 Blue martin Oiltish • Tiger shark * sk coefficient 0.0 • • • Tiger shark ;• L ' • • • * • Swordfish Q • • l • 3 • Black marlin 9 ' • Spnped marlin • • • Black marlin Hammerhead • c nol dawn or dusk dawn preference _ not dawn or dusk dawn preference ~~ -1.0 -0.5 0.0 0.5 10 -1.0 -0.5 0.0 0.5 10 Dawn coefficient Figure 5 Pair-wise comparison of coefficients for the effects of dawn and dusk on catch rates for two fisheries. The shading of each symbol represents the sum of the standard errors of the dawn and dusk estimates (heavy shading for the lowest standard errors; light shading for large standard errors). Not all species names are shown. Underlying mechanisms The broad taxonomic groups taken by longlme each rep- resent a wide range of life history strategies and feeding behaviors. Nevertheless, the results show a tendency for soak time to have a positive effect on catch rates of most shark species (Fig. 4). It also had a positive effect on catch rates of many billfish species, including striped marlin, black marlin, and swordfish. There is no clear pattern in the effect of soak time on catch rates of tuna or other bony fish. It had a negative effect on the four seabird groups. The results imply that the ability of a species to stay alive and to escape or avoid scavengers while hooked is important in determining the catch that is actually brought on board. The effect of soak time is significantly correlated with the ability of a species to survive while hooked on the longline in the four fisheries with data on survival (Fig. 7). Soak time has a strong, positive effect on catch rates of spe- cies like blue shark, which are almost always alive when branchlines are retrieved. Species like skipjack tuna and seabirds are usually dead. Soak time had a negative effect on their catch rates. The opposite trend would be expected if escape is a significant process that affects catch rates; if escape is important, soak time should have a negative af- fect on the catch rates of the most active species. Therefore removal by scavengers is likely to be more important than escape in determining catch rates for many species. Longline branchlines are usually 20-30 m in length, al- lowing considerable room for a live, hooked animal to evade predators or scavengers. Or, scavengers may be attracted by immobile and dead animals. The scavenger avoidance hypothesis is attractive, but it is difficult to test with ob- server data. Data from hook-timer experiments may help to estimate the total number of animals that are lost or removed from the longline. Data presented by Boggs ( 1992 ) showed a large number of hook-timers that were triggered but which did not hold an animal when the branchline was retrieved, e.g. his data show that 2-4"7r of hook-timers on 10,236 branchlines that had "settled" were activated but did not have an animal. It is unclear whether the trigger- ing of hook-timers was due to equipment malfunction or whether it represents high loss rates. Of particular signifi- cance to the question of loss rates is the fact that current hook-timer technology does not identify the species that were lost and whether they were alive or dead. We noticed that soak-time coefficients tended to be poorly correlated between fisheries and that the effects of soak time on catch rates were most pronounced in the South Pa- cific bluefin tuna fishery. Our scavenging hypothesis might explain those observations as evidence that the activities of scavengers vary between fisheries. For example, blue shark might be an important scavenger. They are most abundant in temperate areas (Last and Stevens, 1994). Our analyses showed a predominance of negative soak-time coefficients 192 Fishery Bulletin 102(1) CD a. =0.10* •>•' y -0 1 ( I 2 WP Distant coefficient m o. /-0.65* -o I o o ii I ii 2 SP Yellowfin coefficient Q. ,-=oo,s -ol I 0.2 CP Bigeye coefficient r=0.15* o u •ii Xj) and r^Xj) are the autocorrelations of X and Y at lagj, defined here with the additional weighting factor proposed by Pyper and Peterman ( 1998): ^(X t -XKX l+j -X) r„U) = "-./ £«■,-*) (7) 2 Age-length keys. In Kanto Kinkai no Masaba ni tuite, Ap- pendix 1, vol. 30, 30 p. [In Japanese. Available from Kanagawa Prefectual Fisheries Research Institute. Jyogashima, Misaki. Miura. Kanagawa 238-0237. .Iapan.1 Growth model We used the modified von Bertalanffy growth model to incorporate the effects of population density and sea sur- Watanabe and Yatsu: Interannual variation in length at age of Scomber /aponicus 199 face temperature according to Millar and Myers, 3 who nvestigated three formulations of the modified von Berta- lanffv equations: 1) a reversible effect on the growth constant k; 2) a revers- ible effect on the asymptotic length L r ; and 3) an irreversible effect on L x or k. We tested two of the models, 1 and 2, to investigate the effect of population density and SST. We did not test model 3 because we did not consider that the environmental effects on growth were permanent. Mean length at age i of year-class y was estimated with the fol- lowing formulas: Model 1: reversible environmental effect on k L, v =L„(l-e"*°'-'°) (8) 4v = A-lv + ( L ~ ~ A-i.v X 1 - e~* ) ( 9 ) k lv =k + P l T, fv +P 2 D :v . 110) Model 2: reversible environmental effect on L L ,, = L^ v (l-e-*'») L lv = L,_ ly+ (L^-L,_ lv n-e- Year Figure 3 Interannual fluctuations in mean fork length (FLl at age 0, age 1, and age 2 for chub mackerel iScomberjaponicus) in 1970-97. Horizontal lines show the 28 year mean FL at age 0, 1, and 2, respectively. Vertical bars show standard deviations. (Ill (12) (13) We ran the models with all possible combinations of explanatory variables (T, D, T, and D), and compared AIC with that obtained with the base parameters (L,, r , k). Results where tr, XL, V D. = the age at length (year); = the asymptotic length; and = the growth coefficient; = L, at age i of year-classy; = k at age ;' of year-class y; = the sea surface temperature in year i+y; and = a population density presented by the number of stock at age i of year-class y. These variables were z-score standardized. The model parameters a x and /3 2 were estimated to represent the effects of T l+v and D I v on k or L v . The parameters were estimated by maximizing the like- lihood function which is represented by and L(i,y) = L : v +£,, f, -MO.cr), UL,,k,t ,p v P 2 ,o'f) = {L(/y)-L, v } 2 nnM'-p 2a; (14) (15) (16) 3 Millar, R. B., and R. A. Myers. 1990. Modeling environmen- tally induced change in growth for Atlantic Canada cod stock. ICES CM 1990/G:24. Fork length at age Mean FL at age varied substantially over the time series examined. For example, it ranged from 16.9 (Sd ±3.0) cm in 1975 to 25.9 (Sd ±1.0) cm in 1989. The mean FL for the 28 years period was 21.7 (±2.1) cm (coefficient of variation: CV=9.8%, Table 1, Fig. 3). The FL-at-age-0 values were smaller than the 28-year mean FL for the 1970s, varied around the mean in the early and mid 1980s, reached a maximum in 1989, and were at about 22-24 cm in the 1990s (Fig. 3). Mean FL at age 1 was similarly variable; it ranged from 24.3 (±1.9) cm in 1976 to 31.6 (±1.4) cm in 1995. The 28- year mean FL was 27.7 (±1.6) cm (CV=5.6%,Table 1). The trend in interannual variability was similar to that in age 0, i.e. it was smaller in the 1970s and larger in the 1990s (Fig. 3). In age-2 fish the 28-year minimum FL of 29.1 (±1.8) cm was observed in 1986 and the maximum of 34.5 (±1.3) cm was observed in 1990 (the 28-year mean FL=31.1 (±1.5) cm, CV=4.7%, Table 1, Fig. 3). In fish age 3 and older, mean FL varied year-to-year in a manner similar to that found in the younger ages ( Table 1 ). Annual mean FLs for 3-, 4-, and 5-year-olds were 33.7 (±1.3) cm (3.8%), 36.2 (CI ±1.4) cm (CV=4.0%), and 38.5 (CI ±1.5) cm (CV=3.8%), respectively (Table 1). The mean FLs for ages 0-5 of each year were significantly different among different years (one-way ANOVA, P<0.01 ). 200 Fishery Bulletin 102(1 Table 1 Total biomass, year class strength I stock number at age 1970 to 1997. Blanks show the lack of data. 0;Yats u, et al. ), SST, and mean fork length (FL> of Scomber japonicus from Year Total Biomass (10 3 t) Stock number at age (10 6 individuals I SST (°C)' Mean FL (SD) cm 1 2 3 4 5 1970 2833 10,199 11.5 19.2 12.6) 26.3 (1.8) 30.5 2.4) 34.2 (1.7) 37.7 (1.6) 40.5 1.4) 1971 3781 14.138 10.9 20.2 (2.3) 26.8 (1.9) 31.4 1.5) 34.3 (1.6) 37.7 (1.6) 40.4 1.3) 1972 4860 8342 13.2 19.3 il. 0) 27.2 (1.4) 31.1 1.6) 34.3 (1.5) 37.3 (1.7) 40.0 1.5) 1973 4650 7154 11.1 22.2 U.4) 27.9 (1.5) 29.4 1.6) 31.2 (1.8) 33.1 (2.0) 36.1 1.9) 1974 4048 7854 10.5 19.7 (1.4) 27.7 (2.5) 30.4 1.4) 31.9 (1.7) 33.9 (1.8) 37.6 1.7) 1975 3558 10,353 12.3 16.9 (3.0) 25.4 (1.8) 30.3 2.6) 32.7 (1.6) 33.8 (1.6) 35.5 1.7) 1976 3896 14,402 11.5 19.7 (2.0) 24.3 (1.9) 29.4 2.4) 33.7 (1.9) 35.3 (1.8) 38.1 1.8) 1977 5868 11.701 10.9 21.4 (1.3) 26.2 (1.8) 30.1 2.8) 33.5 (2.2) 35.7 (1.7) 37.4 1.4) 1978 5285 6249 10.0 21.5 (1.1) 28.5 (1.7) 29.8 1.6) 32.1 (2.3) 34.5 (2.D 36.1 1.9) 1979 3250 2931 12.3 19.5 (1.1) 27.1 (2.0) 30.2 2.0) 33.0 (1.7) 35.2 (1.6) 37.2 1.3) 1980 1898 2952 11.3 20.7 (1.1) 25.8 (2.6) 30.3 2.2) 32.4 (1.8) 33.9 (1.8) 35.6 1.6) 1981 1683 3374 9.4 22.7 (1.3) 27.2 (1.7) 30.5 1.5) 33.1 (2.1) 36.5 (1.8) 38.0 1.5) 1982 1567 2883 10.8 22.5 (1.8) 27.9 (1.6) 29.3 1.8) 33.6 (2.2) 36.6 (1.6) 38.3 1.4) 1983 1516 3175 11.5 19.6 (1.2) 26.7 (2.2) 30.8 1.6) 33.6 (1.5) 35.5 (2.0) 37.8 1.2) 1984 1759 3605 9.3 22.7 (1.3) 27.0 (2.4) 31.0 1.8) 34.8 (1.9) 36.6 (1.8) 38.2 2.0) 1985 1565 4998 11.4 20.1 (2.2) 27.3 (2.11 30.9 1.9) 33.3 (1.9) 37.4 (1.7) 39.0 1.8) 1986 1373 1833 9.7 21.5 (1.7) 26.4 (1.4) 29.1 1.8) 32.5 (2.4) 35.9 (2.1) 38.9 1.9) 1987 812 583 10.9 20.5 (2.1) 27.6 (1.7) 30.2 1.3) 32.8 (1.6) 36.4 (2.3) 39.2 0.8) 1988 555 236 11.4 24.9 (1.4) 28.1 (1.5) 30.5 1.4) 32.8 (1.7) 36.8 (1.6) 40.1 1.2) 1989 289 219 9.8 25.9 (1.0) 29.7 (2.3) 32.2 1.4) 34.6 (1.5) 35.7 (1.5) 39.2 1.5) 1990 185 356 11.7 24.4 (1.3) 30.3 (2.6) 34.5 1.3) 35.8 (1.5) 38.2 (1.1) 39.7 0.8) 1991 338 1017 12.2 24.1 (1.6) 28.9 (1.8) 33.5 1.9) 35.5 (1.2) 36.7 (1.9) 39.0 1.8) 1992 724 2839 9.7 24.0 (1.6) 29.0 (1.7) 32.1 1.4) 34.1 (1.5) 37.5 (1.6) 40.5 1.6) 1993 685 589 10.7 23.9 (0.9) 29.3 (1.3) 31.7 l.D 33.2 (0.5) 1994 343 547 11.3 23.7 (1.7) 28.8 (2.5) 32.8 1.0) 34.6 (0.8) 35.9 (0.7) 39.1 1.0) 1995 351 1183 11.3 22.0 (1.3) 31.6 (1.4) 32.9 1.8) 35.5 (1.8) 38.0 (1.3) 39.2 0.8) 1996 726 4452 9.9 22.5 (1.1) 28.7 (2.5) 34.1 1.2) 36.1 (1.1) 37.8 (0.9) 39.7 0.7) 1997 682 529 9.9 23.6 (1.4) 29.0 (1.5) 33.0 1.3) 35.4 (1.7) 37.6 (0.7) 38.6 0.5) 28-year mean of FLs at ages 21.7 (2.1) 27.7 (1.6) 31.1 1.5) 33.7 (1.3) 36.2 (1.4) 38.5 1.5) ' SST during ApriUJ une in the waters bounded by 38^tO°N ar d 141- 143°E. Mean growth increments I of each year class from age (6 months old) to ages 1-5 (/ _,) showed significantly nega- tive correlations (Table 2). Correlations between the two variables tended to increase with age: -0.69 for /,, _,, -0.71 for I„_.,, -0.80 for /„_.,, and -0.77 for I ^. The relative FL at age for any given year class was maintained throughout the life span. A correlation be- tween the mean FL at age and age 1 within each year class (1970 to 1996 year class) was positive and statisti- cally significant (P<0.05, Fig. 4). Similarly, the positive cor- relations between the mean FL at age and age 3 ( 1970 to 1994 year class, P<0.01, Fig. 4), and age and age 4 (1970 to 1993 year class. P<0.05, Fig. 4) were significant (P<0.05. Fig. 4). Correlation between FL and population density Population densities represented by stock in number at age and total biomass were negatively correlated to FL at age. Negative correlations between the logarithm of abundance of age (ln/V ) and FL at ages were relatively high in age to 3 (-0.69 to -0.83, Table 3) and low in age 4 and 5 (-0.63 and -0.64, Table 3). Correlations were statistically signifi- cant for ages 0, 2, and 3 (Table 3). Negative correlations between the logarithm of total biomass and FL at ages were relatively high at ages to 2 (-0.73 to -0.75) and moderate for age 3 to 5 (-0.50 to -0.52, Table 4). However, the relationships were not statistically significant for all ages (Table 4). Watanabe and Yatsu: Interannual variation in length at age of Scomber /aponicus 201 32 E 3 29 26 -- 23 15 H h 20 25 FL at age (cm) 38 36 S. 34 IB 32 -■ 30 B 15 H — H H — i- 20 25 FL at age (cm) 20 25 FL at age (cm) Figure 4 Scatter plots of FL at age 1 (A), age 3 (Bl and age 4 (C) on FL at age for chub mackerel (Scomber japonicus). Correlations between FL at age 1 with age (r=0.83. n=28, actual sample size n'=8, df=6), age 3 with age (r=0.62, ;i=26. n =11. df =9) and age 4 with age (r=0.67, u=24, n'=10) were all significant at P < 0.05. Table 2 Correlation of FL at age and growth increment after age 0. n = actual sample size, n* and degree of freedom (df) show the effective ;? and df when the data were corrected for autocorrelation (Pyper and Peterman, 1998). Signifi- cance level: **, P<0.01. Growth increment Ages 0-1 Ages 0-2 Ages 0-3 Ages 0-4 Ages 0-5 df 0.69** 0.48 27 21 19 0.71** 0.51 26 25 23 0.80** 0.64 25 23 21 0.77** 0.59 23 24 22 0.78** 0.61 22 22 20 Table 3 Correlation between the natural logarithm of the abun- dance of age and mean FL for each age. n = actual sample number, n* and degree of freedom (df) show the significant n and df when autocorrelation was considered (Pyper and Peterman, 1998). Significance levels: *, P < 0.05. Age r r 2 n n df -0.75* 0.57 28 8 6 1 -0.69 0.48 27 7 5 2 -0.83* 0.69 26 6 4 3 -0.71* 0.51 25 9 7 4 -0.63 0.40 23 8 6 5 -0.64 0.40 22 6 4 Correlation between FL and SST Growth in the first six months of life was correlated with SST. We detected significant negative correlation between FL-at-age and SST between April and June in the waters bounded by 38-40°N and 141-143°E U--0.45, r 2 =0.20, n=28, n =27, df=25, P<0.05, Fig. 5). The SST between July and September of this area was also negatively correlated with FL at age although the correlation coefficient was not significant at 5% level. Growth analysis Model 1 that incorporated SST ( T) and population density (D) gave a minimum Akaike's information criterion (AIC) of 457.68 (Table 5) and the model was expressed by L- = 43.98 1 - exp( -2.585 )exp -5X :0. 271-0. 008T -0.2LD, (17) (18) Table 4 Correlation between natural logarithm of total biomass and mean FL for each age. n = actual sample size, n* and dgree of freedom ( df ) show the effective n and df when the data were corrected for autocorrelation (Pyper and Peter- man, 1998). No correlations were significant (P>0.05). Age df 0.74 0.38 27 6 4 0.73 0.32 27 6 4 0.75 0.36 27 5 3 0.52 0.26 27 11 9 0.51 0.26 26 9 7 0.50 0.22 26 7 5 This model estimated the FL at ages 0-5 well (Fig. 6). The AIC of model 1 incorporating T and D was smaller than the AIC of model 2; therefore the environmental factors had an affect on k rather than L T . 202 Fishery Bulletin 102(1) 45 N 40 N 35 N 30 N 140N 145 N 150 B 25 -- 8> 20 + CD r =o.20 15 -I — l — l — l — i — I — i — i — i — i — I — i — i — i — i — I 8 10 12 14 Mean SST Figure 5 (A) Map to show correlation between sea surface temperatures (SST) and mean fork length (FLl at age for chub mackerel (Scomber japonicus). The dotted area indicates the negative correla- tion coefficient r above 0.4. The contour interval is 0.1 of the correlation coefficient and positive contours are shown as dashes. (B) Relationship between mean SST for the area 38°-40°N and 141-143°E from April to June and mean FL at age 0. Correlation was significant at the 5^ level (r=-0.45, n=28, n "=27, df=25). To investigate the effect of T and D, we calculated the total effect on k for year-class v according to Sinclair et al. (2002): lA^ I ft A, for T, and for D. Discussion Estimated population abundance of age-0 fish and total biomass may explain density-dependent growth. FL at age 0, 2, and 3 of the Pacific stock of chub mackerel were negatively correlated with the number of age-0 recruits. Correlations between biomass and FL at ages 0-5 were low and not significant. Therefore, year-class strength is indi- cated to have a greater negative influence on the growth of the Pacific stock of chub mackerel than total biomass, as reported for the Atlantic mackerel (Scomber scombrus) (Agnalt, 1989; Overholtz, 1989; Neja, 1995) and Atlantic herring (.CI upea harengus) (Toresen, 1990). Density-dependent growth in fish populations seems to be a common phenomenon for pelagic fishes found in the temperate waters of Japan. The FL at age of the 1963-69 year classes ranged from 16 to 20 cm, and were smaller than those of the 1970s, possibly indicating density-dependent growth ( Iizuka, 1974 ). According to Honma et al. ( 1987 ), the stock abundance of the Pacific stock of chub mackerel from 1963 to 1969 was larger than it was in the 1970s. Wada et al. (1995) and Hiyama et al. ( 1995) found negative relation- ships between total biomass and body length in the Pa- Table 5 Summary of statistics from the estimation of growth for chub mackerel (Scomber japonicus). AIC = Akaikf 's infor- mation criterion. No. of Log unknown likeli- Model Variables parameters hood AIC 1 L„, k, t n , (jj . . .a 5 9 -280.20 578.40 L,.k,t ,a 1 ...a 5 , /3, 10 -270.10 560.20 L r , k, t , CTj . . .a 5 , p 2 10 -222.38 464.77 L„, k, t , a, . . .ct s ,/S] ft 11 -217.84 457.68 2 L a ,k,t ,a 1 ...a s 9 -280.20 578.40 L,,k.t„.a x . . -cr 5 , jSj 10 -268.63 557.25 L r , k, t , a t . . .ii-, />., 10 -224.01 468.02 L x , k, t Q , (Jj . . .Or,, fi x ft 11 -220.81 463.62 cific and Tsushima Current stock of the Japanese sardine (Sarclinops melanostictus). Kishida (1990) demonstrated a density-dependent relationship between the growth and total stock density (CPUE) of Japanese Spanish mackerel (Scomberomortis nipkonius). Our results do not agree with the positive effect of sea wa- ter temperature on somatic growth that has been shown for several species, including Japanese common squid (Kidokoro, 2001). Atlantic herring ( Moores and Winters, 1981; Toresen, 1990). and Atlantic cod (Gadus morhua ) (Brander, 1995; Du- til et al, 1999; Ratz et al. 1999; Otterson et al., 2002). Watanabe and Yatsu: Interannual variation in length at age of Scomber /aponicus 203 15 I i m i ni 20 I i 70 75 80 85 90 95 70 75 80 85 90 95 35 30 Age 2 35 30 -- Age 3 25 I I I I I I I I I I I I I I I I I I II I I I I I I I I I 25 I I I I I I I I I I I I II I I I I I I I I I I I I I I I 70 75 80 85 90 95 70 75 80 85 90 95 40 35 Age 4 .. Age 5 40 -- 35 30 I I I II I I I I I I I I I I II II I I I I I I II I I 30 I I I I I I I I I I I I I I III I I I I I I I I I I I I 70 75 80 85 90 95 70 75 80 85 90 95 Year Figure 6 Time series of observed (open circles) and modeled (solid line) values of mean fork length (FL) at ages 0-5 during 1970-97 for chub mackerel iScomber japonieus). There was a positive correlation between FL at age and l°xl° block SST in the waters of 32-34°N and 144-149°E, located south of the Kuroshio Extension flowing eastward at the latitude of 35-37°N from April to June (Figs. 1 and 5A). But the correlation coefficient was not significant, and this area was not considered to be inhabited by juvenile mackerel (Watanabe, 1970). Thus, we considered that the SST in the waters of 32-34°N and 144-149°E was not a significant factor on the variation of FL at age 0. The low SST in the waters bounded by 38-40°N and 141-143°E is indicative of a large inflow of Oyashio Cur- rent waters (Hirai and Yasuda, 1988), which is a cold water current and has high productivity (Odate, 1994), into the Kuroshio-Oyashio transition zone, where is one of the main feeding grounds of mackerels (Odate, 1961; Watanabe, 1970; Watanabe and Nishida, 2002; Fig. 1). Thus, we hypothesized that the large inflow of Oyashio current waters into the Kuroshio-Oyashio transition zone improved the feeding condition and accelerated the growth of juvenile mackerel. Jobling ( 1988) suggested a parabolic relationship between water temperature and fish growth. The range of SST in this area, which was negatively cor- related with FL at age of mackerel, was 9-13°C (Table 1 ). This temperature range is near the lowest nonstressful temperatures for mackerel ( 10-12°C, Schaefer, 1986). Thus, we do not consider that the negative relationship between growth and SST was the result of suppressed growth by the high ambient temperature. In mackerel, maximum egg production appears to have shifted to later in spring during the 1990s, as compared to the late 1970s and 1980s, resulting in a shorter period of growth and thus smaller fish (Fig. 8, Mori et al. 4 ; Kikuchi and Konishi 5 ; Ishida and Kikuchi 6 ; Zenitani et al. 7 ; Kubota et al. 8 ). In the early 1970s, the main spawning period was 4 Mori, K., K. Kuroda, and Y. Konishi. 1988. Monthly egg production of the Japanese sardine, anchovy, and mackerels off the southern coast of Japan by egg censuses. Datum Collect. Tokai Reg. Fish. Res. Lab. 12:1-321. [In Japanese. Available from National Research Institute of Fisheries Science, 2-12-4 Fukuura, Kanazawa, Yokohama 236-8648, Japan.] 5 See next page. 6 See next page. 7 See next page. 8 See next page. 204 Fishery Bulletin 102(1) 0.015 T -0.015 0.015 i i i i i i i i i i i ii n i i 70 75 80 85 90 95 -0.015 I I I I I I I I I I I I I I 70 75 80 Year Figure 7 The total effect of I A) mean SST for the area of 38-40°N and 141-143"E from April to June, and (Bl population density on k for each year class of chub mackerel i Scomber japonicus). also in April (Kuroda 9 ). Delayed spawning in the 1990s should have resulted in a reduction in the mean FL at ages during September-December in the 1990s compared to the 1970s and 1980s; however the present study showed the op- posite result (Table 1 ). We hypothesize that the effect of the shift of spawning period on the FL at ages may have been overwhelmed by the effect of population density (Fig.7). ■"' Kikuchi, H.,andY. Konishi. 1990. Monthly egg production of the Japanese sardine, anchovy, and mackerels off the southern coast of Japan by egg censuses: January, 1987 through December, 1988, 72 p. National Research Institute of Fisheries Science. Tokyo. [In Japanese. Available from National Research Insti- tute of Fisheries Science, 2-12-4 Fukuura, Kanazawa. Yokohama 236-8648, Japan.] 6 Ishida, M. and H Kikuchi. 1992. Monthly egg production of the Japanese sardine, anchovy, and mackerels off the southern coast of Japan by egg censuses: January, 1989 through December, 1990, 86 p. National Research Institute of Fisheries Science, Tokyo. [In Japanese. Available from National Research Insti- tute of Fisheries Science, 2-12-4 Fukuura, Kanazawa, Yokohama 236-8648, Japan.]. 7 Zenitani, H., M. Ishida, Y Konishi, T Goto, Y. Watanabe, and R. Kimura. 1995. Distributions of eggs and larvae of Japanese sardine, Japanese anchovy, mackerels, round herring, jack mack- erel and Japanese common squid in the waters around Japan. 1991 through 1993. Resources Management Research Report Series A-2, 368 p. National Research Institute. Japan Fisheries Agency, Tokyo. [In Japanese. Available from National Research Institute of Fisheries Science, 2-12-4 Fukuura, Kanazawa, Yoko- hama, 236-8648 Japan] s Kubota, H.,Y Oozeki, M. Ishida, Y Konishi, T Goto, H. Zenitani, and R. Kimura. 1999. Distributions of eggs and larvae of Japanese sardine, Japanese anchovy, mackerels, round her- ring, jack mackerel and Japanese common squid in the waters around Japan, 1994 through 1996, 352 p. Resources Manage- ment Research Report Series A-2., National Research Institute, Japan Fisheries Agency, Tokyo. [In Japanese. Available from National Research Institute of Fisheries Science, 2-12-4 Fuku- ura, Kanazawa, Yokohama 236-8648, Japan.] 9 Kuroda, K. 2002. Personal commun. 1-1-3-406. Kasumi. Narashino. Chiba 275-0022, Japan. Jun 6 May 5 - - Apr 4 Mar 3 H — l — I — I — I — I— 78 80 82 84 86 88 Year —l — l — l — l — l — i — i 90 92 94 96 Figure 8 Interannual variation in the peak period (weighted monthly means) of egg production for the Pacific stock of chub mackerel (Scomber japonicus), which includes a small portion from the eggs of spotted mackerel (Scomber australasicus) (Mori et al. 4 : Kikuchi and Konishi''; Ishida and Kikuchi 1 '; Zenitani et al. 7 ; Kubota et al. 8 ). The estimated FL at age from our growth model, with the use of AIC, fitted well to the observed FL at age (Fig. 6). Mean growth increments / of each year class from age (6 months old) to ages 1-5 (/„_,) were signifi- cant and negatively correlated with FL at age (Table 2), indicating that the growth rate of mackerel had changed from year to year for a given year class. This negative correlation indicated that the effects of population density and SST was temporal, and influenced k rather than L r . The negative correlation between FL at age and growth increments also suggested that the FL at age of mack- erel approximated the asymptotic length. Thus, mackerel growth was best fitted to the modified von Bertalanffy growth model with the temporal environmental effect on k (Table 5). Watanabe and Yatsu: Interannual variation in length at age of Scomber /aponicus 205 The effect of population density on growth of mackerel was higher than the effect of SST (Fig. 7, Table 6). Our result agreed with the results for Japanese sardine ( Wada et al., 1995 ) and Atlantic cod ( Sinclair et al., 2002 ). Particu- larly, the effect of population density was significant in the late 1980s, which resulted in a remarkable increase in FL at age (Figs. 3 and 7). The relative size at age was carried over to older ages (Fig. 4), indicating that the cohorts that were small at age could not compensate for this early small size. Iizuka (1974) reported that the trend of growth established at age for chub mackerel was maintained until age 2 for the 1963-73 year classes. Toresen (1990) demonstrated from length data that a trend in rate of growth for a given year class of Norwegian herring was determined at the im- mature stage and was consistent after maturation. Total length of Hokkaido-Sakhalin herrings iClupea pallasii) at age 5 and older was positively correlated with the length at age 4 (Watanabe et al., 2002). Because fish first mature at age 4. this implied that the trend in total length of each year class was determined by the age at maturity. From these results we hypothesize that the variability in size at age in the Pacific stock of chub mackerel is largely attribut- able to growth before maturity, especially during the first 6 months after hatching. Acknowledgments We would like to thank K. Meguro of Chiba Prefecture Governmental Office and K. Kobayashi of Shizuoka Pre- fecture Governmental Office for providing insights into chub mackerel's growth and into age determination. We also thank T. Akamine, M. Suda, and N. Yamashita of the National Research Institute of Fisheries Science for advice on the statistical analysis. We also thank Y. Watanabe and C. B. Clarke of the Ocean Research Institute, University of Tokyo, for their constructive comments on this manuscript. Literature cited Agnalt, A. -L. 1989. Long-term changes in growth and age at maturity of mackerel. Scomber scombrus L.. from the North Sea. J. Fish Biol. 35 (suppl. A):305-311. Brander. K. M. 1995. The effect of temperature on growth of Atlantic cod iGadus morhua L.). ICES J. Mar. Sci. 52:1-10. Dutil. J. -D., M. Castonguay, D. Gilbert, and D. Gascon. 1999. Growth, condition, and environmental relationships in Atlantic cod iGadus morhua) the northern Gulf of St. Lawrence and implications for management strategies in the Northwest Atlantic. Can. J. Fish. Aquat. Sci. 56: 1818-1831. Haddon, M. 2001. Modelling and quantitative methods in fisheries, 406 p. Chapman&Hall/CRC, New York, NY. Hirai, M. 1991. Fisheries oceanographic study on purse-seine fish- ing-grounds for chub mackerel in the Sanriku coastal waters. Bull. Tohoku Natl. Fish. Res. Inst. 53:59-147. [In Japanese.] Hirai, M., and I. Yasuda. 1988. Interannual variability of the temperature field at 100 m depth near the east coast of Japan. Bull. Otsuchi Ocean Res. Center. Univ. Tokyo. 14:184-186. Hiyama, Y , H. Nishida. and T Goto. 1995. Interannual fluctuations in recruitment and growth of the sardine, Sardinops melanostictus, in the Sea of Japan and adjacent waters. Res. Popul. Ecol. 37(21:177-183. Honma, M., Y Sato, and S. Usami. 1987. Estimation of the population size of the Pacific mack- erel by the cohort analysis. Bull. Tokai Reg. Fish. Res. Lab. 121:1-11. [In Japanese.) Iizuka, K. 1974. The ecology of young mackerel in the north-eastern sea of Japan FY Estimation of the population size of the 0-age group and the tendencies of growth patterns on 0. I. and II age groups. Bull. Tohoku Reg. Fish. Res. Lab. 34: 1-16. [In Japanese.] Jobling, M. 1988. A review of the physiological and nutritional energet- ics of Cod, Gadus morpha L., with particular reference to growth under farmed conditions. Aquaeulture, 70:1-19. Kawasaki, T. 1966. Structure of the Pacific population of the mackerel. Bull. Tokai Reg. Fish. Res. Lab. 47:1-34. [In Japanese.] Kidokoro, H. 2001. Fluctuations in body size and abundance of Japanese common squid {Todarodes pacificus) in the Sea of Japan. GLOBEC report 15:42. Kishida. T 1990. Relationship between growth and population density of Japanese Spanish mackerel in the central and western waters of the Seto Inland Sea. Bull. Nansei Natl. Fish. Res. Inst. 23:35-41. |In Japanese.] Mace, P. M., and M. O. Sissenwine. 1993. How much spawning per recruit is enough? Can. Spec. Publ. Fish. Aquat. Sci. 120:101-118 Moores, J. A., and G. H. Winters. 1981. Growth patterns in a Newfoundland Atlantic herring iClupea harengus harengus) stock. Can. J. Fish. Aquat. Sci. 39:454-461. Moyle, P. B., and J. J. Cech Jr. 2002. Fishes: An introduction to ichthyology, 4th ed., 612 p. Prentice Hall, Englewood Cliffs. NJ. Murayama.T., I. Mitani, and I. Aoki. 1995. Estimation of the spawning period of the Pacific mack- erel Scomber japonicus based on the changes in gonad index and the ovarian histology. Bull. Jpn. Soc. Fish. Oceanogr. 59:11-17. [In Japanese.] Neja, Z. 1995. The stock size and changes in the growth rate of the northwest Atlantic mackerel [Scomber scombrus L.) in 1971-1983. Acta Ichthyologica et Piscatoria 25:113-121. Odate, K. 1994. Zooplankton biomass and its long-term variation in the western north Pacific ocean, Tohoku sea area, Japan. Bull. Tohoku Natl. Fish. Res. Inst. 56, 115-173. [In Japanese.] Odate, S. 1961. Study on the larvae of the fishes in the north-eastern sea area along the Pacific coast of Japan. Part 1. Mackerel. Pneumatophorus japonicus ( Houttuyn I. Bull. Tohoku Reg. Fish. Res. Lab. 19:98-108. [In Japanese.] Otterson, G, K. Helle, and B. Bogstad. 2002. Do abiotic mechanisms determine interannual vari- 206 Fishery Bulletin 102(1) ability in length-at-age of juvenile Arcto-Norwegian cod? Can. J. Fish. Aquat. Sci. 59:57-65. Overholtz, W. J. 1989. Density-dependent growth in the northwest Atlan- tic stock of Atlantic mackerel (Scomber scombrus). J. Northw. Atl. Fish. Sci. 9:115-121. Pauly, D. 1987. Application of information on age and growth of fish to fishery management. In Age and growth of fish (R. C. Summerfelt and G. E. Hall, eds.) p.495-506. Iowa State Univ Press, Ames, IA. Pyper, B. J., and R. M. Peterman. 1998. Comparison of methods to account for autocorrelation in correlation analyses of fish data. Can. J. Fish. Aquat. Sci. 55:2127-2140. Ratz, H. -J., M. Stein, and J. Lloret. 1999. Variation in growth and recruitment of Atlantic cod (Gadus morhua I off Greenland during the second half of the twentieth century. J. Northw. Atl. Fish. Sci. 25:161-170. Schaefer, K. M. 1986. Lethal temperature and the effect of temperature change on volitional swimming speeds of chub mackerel. Scomber japonicus. Copeia 1986:37-44. Sinclair, A. F.. D. P. Swain, and J. M. Hanson. 2002. Disentangling the effects of size-selective mortality, density, and temperature on length-at-age. Can. J. Fish. Aquat. Sci. 59:372:382. Toresen, R. 1990. Long-term changes in growth of Norwegian spring- spawning herring. J. Cons. Int. Explor. Mer 47:48-56. Usami, S. 1973. Ecological studies of life pattern of the Japanese mackerel, Scomber japonicus Houttuyn: on the adult of the Pacific subpopulation. Bull. Tokai Reg. Fish. Res. Lab. 76: 71-178. |In Japanese.] Wada, T., Y. Matsubara, Y. Matsumiya, and N. Koizumi. 1995. Influence of environment on stock fluctuations of Japanese sardine, Sardinops melanostictus. Can. Spec. Publ. Fish. Aquat. Sci. 121:387-394. Watanabe, C, and H. Nishida. 2002. Development of assessment techniques for pelagic fish stocks: applications of daily egg production method and pelagic trawl in the northwestern Pacific ocean. Fisheries Science. 68:97-100. Watanabe, C, T. Hanai, K. Meguro, R. Ogino, Y Kubota, and R. Kimura. 1999. Spawning biomass estimates of chub mackerel Scomber japonicus of Pacific subpopulation off central Japan by a daily egg production method. Nippon Suisan Gakkaishi 651 4 1:695-702. [In Japanese.] Watanabe, T. 1970. Morphology and ecology of early stages of life in Japa- nese common mackerel. Scomber japonicus Houttuyn, with special reference to fluctuation of population. Bull. Tokai Reg. Fish. Res. Lab. 62:1-283. [In Japanese.] Watanabe, Y, Y Hiyama. C. Watanabe, and S. Takayanagi. 2002. Inter-decadal fluctuations in length-at-age of Hok- kaido-Sakhalin herring and Japanese sardine in the Sea of Japan. PICES Scientific Report 20:63-67. Yatsu, A., and H. Kidokoro. 2002. Coherent low frequency variability in biomass and in body size of Japanese common squid, Tadorodes padificus. during 1964-2002, 89 p. Abstracts of PICES 11 th annual meeting. 207 Latitudinal and seasonal egg-size variation of the anchoveta (Engraulis ringens) off the Chilean coast Alejandra Llanos-Rivera Leonardo R. Castro Laboratorio de Oceanografia Pesquera y Ecologia Larval Departamento de Oceanografia Universidad de Concepcion Casilla 160-C, Concepcion, Chile E-mail address (for L. R Castro, contact author) lecastro@udeccl occur among populations of E. ringens along its distribution. In this study, we 1 ) report changes in egg size through- out the anchoveta spawning season as well as for the peak months of the spawning season, 2) evaluate whether egg size varies with respect to latitude, and 3 ) evaluate whether differences in larval length and yolksac volume occur in hatching larvae from the two major spawning stocks along Chile (central and southern stocks). The anchoveta Engraulis ringens is widely distributed along the eastern South Pacific (from 4° to 42°S; Serra et al., 1979) and it has also supported one of the largest fisheries of the world over the last four decades. However, there are few interpopulation comparisons for either the adult or the younger stages. Reproductive traits, such as fecundity or spawning season length, are known to vary with latitude for some fish species (Blaxter and Hunter, 1982; Conover, 1990; Fleming and Gross, 1990; Castro and Cowen, 1991). and latitudinal trends for some early life history traits, such as egg size and larval growth rates, have been reported for others clupeiforms and other fishes (Blaxter and Hempel, 1963; Ciechom- ski. 1973; Imai and Tanaka, 1987, Conover 1990, Houde 1989). However, there is no published information on potential latitudinal trends during the adult or the early life history of the anchoveta, even though this type of information may help in understand- ing recruitment variability, especially during recurring large scale events ( such as El Nino or La Nina) that affect the entire species range. Egg volume has been found to vary widely among species and among popu- lations of the same species. For fish that broadcast planktonic or benthic eggs, egg size often varies as the spawning season progresses (Bagenal, 1971), and the magnitude of this variation depends on the species. For instance, the egg vol- ume of the pelagic spawners Engraulis anchoita and Solea solea decreases 23% and 38%. respectively, throughout the spawning season (Ciechomski, 1973; Rijnsdorp and Vingerhoed, 1994). Ma- ternal and environmental factors may also affect egg volume (Bagenal, 1971; Thresher, 1984; Rijnsdorp and Vinger- hoed, 1994; Chambers and Waiwood. 1996; Chambers, 1997). Variations in size of the spawning females and shifts in energy allocation from reproduction to growth as the spawning season pro- gresses may influence the egg volume (Wootton, 1990). Alternatively, seasonal variations in photoperiod, seawater temperature, and food supply during the spawning season may affect the reproductive output (Wootton, 1990). Scarce information exists on the variability of egg sizes for fishes in the Humboldt Current. In this extensive area, the heavily exploited anchoveta Engraulis ringens is the dominant small pelagic species. Throughout this range, three major stocks are recog- nized: the northern stock off northern Peru ( the largest ); the central stock off southern Peru and northern Chile (mid- size), and the southern stock off central Chile (the smallest of the three). For the entire distribution of anchoveta, the main spawning season is from July through September, but may extend to December or January (Cubillos et al., 1999). The wide latitudinal range and prolonged spawning period suggest the possibility of egg-size variation, as ob- served in other clupeifoms (Blaxter and Hempel, 1963; Ciechomski, 1973; Imai and Tanaka, 1987). Egg size correlates with larval characteristics such as lar- val length at hatching, the time to first feeding, and time before irreversible starvation (Shirota, 1970; Ware, 1975; Hunter, 1981; Marteinsdottir and Able, 1992). To explore whether differences in potential early-life-stage survival would exist among populations and (or seasons ), the objective of our research was to determine whether variations in some early-life-stage characteristics Materials and methods We collected anchovy eggs from four locations along the coastal zone (<20 nmi offshore ) off northern and central Chile during the austral winter and spring spawning seasons 1995-97 (Fig. 1). Eggs were collected with a Calvet net (150 urn mesh) in Iquique and Antofagasta (northern Chile), with a standard conical net (330 um) in Valparaiso and with either a Tucker trawl (250 ; 73 Longitude West Figure 1 Areas where anchoveta eggs were collected to determine egg-size variations along the Chil- ean coast. Arrows show the locations depicted in Table 2. egg sizes measured in Iquique (<0.19 mm 3 ) did not occur in Talcahuano. Similarly, the largest sizes determined in Talcahuano (>0.30 mm 3 ) did not occur in Iquique. at the lowest latitude. Larval length at hatching determined in the rearing experiments at normal field temperatures was greater for the southernmost population (Talcahuano) (Table 3). The mean larval size for the southern location (2.70 mm noto- chord length) was 8.2% greater than the larvae hatched from eggs collected at the northern experimental location (Antofagasta, 2.50 mm). Furthermore, the yolksac volume in the recently hatched larvae in Talcahuano (0.130 mm 3 ) Note Llanos-Rivera and Castro: Egg-size variation of Engraul/s ringens 209 80 60 40 20 „ 80 & 60 c S -+- 10-0 14 15-0 19 20-0 24 0.25-0.29 0.30-0.34 0.35-0.39 0.40-0.44 Size interval (mm 3 ) Figure 3 Latitudinal variation in egg size of the anchoveta (£. ringens ) along northern and central Chile during the peak months of the spawning season. Y-axis is frequency over the total number of eggs measured at each locality. of these factors co-occur. For instance, changes in growth rates for yearly cohorts during the spawning season (low at the beginning, fast at the end) have been documented for the southernmost population (Cubillos et al., 2001). Alter- natively, variations in the population age structure during the spawning season have also been reported as the 1.5 year-old new recruits begin to spawn in early summer (late December-January, Cubillos et al., 1999, 2001 ). Changes in environmental factors affecting the spawning adults also correlate with the egg-size variations. The photoperiod and nearsurface temperatures increase as the spawning season progresses from mid-winter to late spring. Larger egg size at the beginning of the spawning season in winter may be advantageous for these offspring because the chances of survival increase with the larger sizes of the hatching larvae. According to Cushing (1967), larger size larvae should be favored over smaller larvae in seasons with variable environmental conditions. In theTalcahuano area, strong fluctuations in the hydrographic regime occur during winter as strong north wind storms alternate with short periods of south winds, and also because of the in- creased river flow to the coastal zone (Castro et al., 2000). Larval food, although variable, seems to be sufficient to support most of the larval growth demands for larger exogenous feeding larvae during winter (Hernandez and Castro, 2000). For recently hatched larvae, however, the picture might be slightly different because, in addition to food supply variability, the strong turbulent environmental conditions may jeopardize first feeding success. In these highly variable areas, therefore, larger larval size at hatch- ing and larger yolk reserves may be even more important than in other less hydrographically variable areas and seasons. A remarkable increase in egg size at the peak spawn- ing season occurred with respect to latitude. Egg from the northernmost (20°S) latitude were at a maximum 559c larger than eggs from the southernmost (36°S) lati- tude. Latitudinal variations in egg size have been previ- ously reported for other anchovies (i.e. Engraulis anchoita; Ciechomski, 1973). However, egg-size variations for fishes Note Llanos-Rivera and Castro: Egg-size variation of Engraulis nngens 211 Table 2 Width, length, and volume of anchoveta eggs collected at different latitudes along the Chilean coast during the peak months of the spawning season. SD = - standard deviations, n = number of eggs measured. Latitude and area Width (mm) Length (mm) Volume (mm 3 ] mean SD mean SD mean SD ?! 20° Iquique 0.563 0.032 1.201 0.076 0.201 0.031 1670 23° Antofagasta 0.597 0.030 1.293 0.083 0.243 0.034 425 33° Valparaiso 0.643 0.023 1.373 0.064 0.298 0.026 62 36° Talcahuano 0.657 0.027 1.377 0.063 0.312 0.030 1833 Table 3 Morphological characteristics of recently hatched Engraulis ringens larvae from rearing experiments at normal field tempera- tures in Antofagasta (15°C) and Talcahuano (12°C). SD = standard deviations. N = number of eggs measured Exp. = expe riment. Egg volume Larval length Yolksac size ( mm 3 ) at hatching (mm) at hatching (mm 3 ) Exp. 1 Exp. 2 Exp. 1 Exp. 2 Exp. 1 Exp. 2 Antofagasta 15°C Mean 0.264 0.260 2.49 2.50 0.099 0.096 SD (0.023) (0.023) (0.170) (0.1041 (0.012) (0.0121 n 358 325 30 30 30 30 Talcahuano 12°C Mean 0.302 0.292 2.71 2.69 0.126 0.134 SD (0.023) (0.026) (0.111) (0.103) (0.016) (0.017) n 254 66 30 30 30 30 are not necessarily always associated with latitude (i.e. north Atlantic herring stocks) because local environmen- tal conditions that trigger spawning (i.e. specific tempera- ture or others) may have a stronger effect in some species (Chambers, 1997). Because of the extremely wide distri- bution range of the anchoveta (4-42°S) and its residence along an almost linear coast oriented exactly north-south, we proposed that any potential differences in egg size due to specific local conditions is probably over-driven by the larger scale changes in environmental conditions associ- ated with latitude. The strong latitudinal gradient in egg size of the ancho- veta may be an adaptive measure if different egg sizes are favored at different latitudes or if there is a correlation between egg size and adult life history traits that maximize net reproductive output. Unfortunately, an analysis of the anchoveta in which fecundity, age of first reproduction, longevity, or other adult traits are compared in relation to latitude has not yet been carried out. The timing and length of the spawning season seem to be similar for the northern (Iquique, 20°S) and southern (Talcahuano, 36°S) stocks along Chile, despite the different temperatures at which anchoveta spawn (Castro et al., 2001 ). The decrease in egg size coincides with known temperature effects on physiological rates (Houde, 1989) and on ecological factors related to the need of anchoveta at early life stages to re- main in nearshore environments (Bakun. 1996). At lower latitudes, the sea temperature is higher and the seaward surface Ekman transport is stronger and therefore eggs and larvae in such conditions would likely develop rapidly. Alternatively, anchovy egg and larvae at higher latitudes are retained nearshore in winter (because the Ekman transport is negative, Castro et al., 2000) but are exposed to lower temperatures and to strong turbulence that may not facilitate the first feeding of recently hatched larvae and subsequent rapid larval development. Larger eggs, larger larvae at hatching, and more energy reserves may be the favored early life history strategy in southern popu- lations. How the latitudinal variations in environmental characteristics affect the rest of the life history traits of the different populations of Engraulis ringens, one of the most important fish species in the world in terms of catches, remains to be assessed. Acknowledgments We acknowledge help from R. Escribano (U. Antofagasta), G. Claramunt (U. Arturo Prat), and F. Balbontin (U. of Valparaiso) who facilitated ichthyoplankton collections. 212 Fishery Bulletin 102(1) H. Moyano (U. of Concepcion) allowed the use of his labora- tory and optical material. This study was financed by the project FONDECYT 1990470 to L. R. Castro. E. Tarifeno, and R. Escribano. Alejandra Llanos-Rivera was also par- tially supported by the Graduate School of the Universidad de Concepcion. Literature cited Bagenal, T.B. 1971. The interrelation of the size of fish eggs, the date of spawning and the production cycle. J. Fish Biol. 3: 207-219 Bakun, A. 1996. Patterns in the ocean. Ocean processes and marine population dynamics, 233 p. California Sea Grant College Publ., NOAA in Cooperation with the Centro de Investiga- ciones Biologicas del Noreste, La Paz, BCS. Mexico. Blaxter, J., and G. Hempel. 1963. The influence of egg size on herring larvae iClupea harengus L.). J. Con. Perm. Int. Explor. Mer 28: 211-240. Blaxter, J. H. S., and J. R. Hunter 1982. The biology of clupeoid fishes. Adv. Mar. Biol. 20: 3-194. Castro, L. R., and R. K. Cowen 1991. Environmental factors affecting the early life history of bay anchovy (Anchoa mitchilli) in Great South Bay, New York. Mar. Ecol. Prog. Ser. 76:235-247. Castro, L. R., G. R Salinas, and E. H. Hernandez. 2000. Environmental influences on winter spawning of the anchoveta, Engruulis ringens, off Central Chile. Mar. Ecol. Prog. Ser. 197:247-258. Castro. L. R., A. Llanos, J. L. Blanco, E. Tarifeno, R. Escribano, and M. Landaeta. 2001. Latitudinal variations in spawning habitat charac- teristics: influence on the early life history traits of the anchoveta, Engraulis ringens, off northern and central Chile. GLOBEC Report 16:42-45. Chambers. R. C. 1997. Environmental influences on egg and propagule sizes in marine fishes. In Early life history and recruitment in fish populations (R. C. Chambers and E. A. Trippel, eds.), p. 63-102. Chapman & Hall, London. Chambers, R. C, and K. Waiwood. 1996. Maternal and seasonal differences in egg sizes and spawning characteristics of captive Atlantic cod, Gadus morhua. Can. J. Fish. Aquat. Sci. 53:1986-2003. Ciechomski, J. de 1973. The size of the eggs of the Argentine anchovy, Engraulis anchoita (Hubbs & Marinil in relation to the season of the year and the area of spawning. J. Fish Biol. 5:393-398. Conover, D. 1990. The relation between capacity for growth and length of the growing season: evidence for and implications of coun- tergradient variation. Trans. Am. Soc. 119:416-430. Cubillos, L. A., D. Arcos, D. Bucarey, and M. Canales. 2001. Seasonal growth of small pelagic fish off Talcahuano, Chile (37°S, 73°W): a consequence of their reproductive strategy to seasonal upwelling? Aquat. Living Resour. 14:1-10. Cubillos, L. A., M. Canales, D. Bucarey, A. Rojas. and R. Alarcon. 1999. Reproductive period and mean size at first maturity for Strangomera bentincki and Engraulis i-ingens from 1993 to 1997, off central-southern Chile. Invest. Mar. 27:73-85. (In Spanish.] Cushing, D. H. 1967. The grouping of herring populations. J. Mar. Biol. Assoc. U.K. 47:193-208 Escribano, R., L. Rodriguez, and C. Irribarren 1995. Temporal variability of sea temperature in bay of Antofagasta, Northern Chile ( 199 1-1995 1. Estud. Oceanol. 14:39-47. [In Spanish.] Fisher. W. 1958. Huevos, crias y primeras prelarvas de la anchoveta Engraulis ringens Jenyns. Rev. Biol. Mar. 8 (1-2-31:111- 124. Fleming. I. A., and M. Gross. 1990. Latitudinal clines: a trade-off between egg number and size in pacific salmon. Ecology 71(11:1-11. Hernandez, E. H.. and L. R. Castro. 2000. Larval growth of the anchoveta, Engraulis ringens, during the winter spawning season off central Chile. Fish. Bull. 98:704-710. Houde, E. D. 1989. Comparative growth, mortality and energetics of marine fish larvae: temperature and implied latitudinal effects. Fish. Bull. 87:471^195. Hunter, J. R. 1981. Feeding ecology and predation of marine fish larvae. In Marine fish larvae (R. Lasker. ed.l. p. 34-77. Univ. Washington Press, Seattle, WA. Imai, Ch., and S. Tanaka. 1987. Effect of sea water temperature on egg size of Jap- anese anchovy. Nippon Suisan Gakkaishi 53(12): 2169- 2178. Marteinsdottir, G., and K. Able. 1992. Influence of egg size on embryos and larvae ofFundu- lus heteroclitus (L.l. J. Fish Biol. 41:883-896. Rijnsdorp, A., and B. Vingerhoed. 1994. The ecological significance of geographical and sea- sonal differences in egg size in sole Solea solea (L.). Neth. J. Sea Res. 32(3/41:255-270. Serra J., O. Rojas, M. Aguayo. F. Inostroza, and J. Canon. 1979. Anchoveta {Engraulis ringens). In Estado actual de las principales pesquerias nacionales. Bases para un desarrollo pesquero. 36 p. Corporacibn de fomento de la production. In- stituto de Fomento Pesquero. Santiago, Chile. Shirota, A. 1970. Studies on the mouth size offish in the larval and fry stages. Bull. Jap. Soc. Sci. Fish. 36:353-368. Thresher, R. E. 1984. Reproduction in reef fishes, 399 p. T.F.H. Publica- tions. Inc. Ltd. .The British Crown Colony of Hong Kong. Ware, D. M. 1975. Relation between egg size, growth, and natural mortal- ity of larval fish. J. Fish. Res. Board Can. 32: 2503-2512. Wootton. R. 1990. Ecology of teleost fishes, 404 p. Chapman & Hall. London. 213 Molecular methods for the genetic identification of salmonid prey from Pacific harbor seal (Phoca vitulina richardsi) scat Maureen Purcell Greg Mackey Eric LaHood Conservation Biology Molecular Genetics Laboratory Northwest Fisheries Science Center National Marine Fisheries Service. NOAA 2725 Montlake Blvd. E. Seattle, Washington 98112-2097 Harriet Huber National Marine Mammal Laboratory Alaska Fisheries Science Center National Marine Fisheries Service, NOAA 7600 Sand Point Way NE Seattle, Washington 98115 Linda Park Conservation Biology Molecular Genetics Laboratory Northwest Fisheries Science Center National Marine Fisheries Service, NOAA 2725 Montlake Blvd. E. Seattle, Washington 98112-2097 E-mail address (for L. Park, contact author): linda parkig'noaa gov Twenty-six stocks of Pacific salmon and trout [Oncorhynchus spp.), rep- resenting evolutionary significant units (ESU), are listed as threatened or endangered under the Endangered Species Act (ESA) and six more stocks are currently being evaluated for listing. 1 The ecological and economic consequences of these listings are large; therefore considerable effort has been made to understand and respond to these declining populations. Until recently. Pacific harbor seals (Phoca vitulina richardsi) on the west coast increased an average of 5% to 1% per year as a result of the Marine Mammal Protection Act of 1972 (Brown and Kohlman 2 ). Pacific salmon are season- ally important prey for harbor seals (Roffe and Mate, 1984; Olesiuk, 1993); therefore quantifying and understand- ing the interaction between these two protected species is important for biologically sound management strat- egies. Because some Pacific salmonid species in a given area may be threat- ened or endangered, while others are relatively abundant, it is important to distinguish the species of salmonid upon which the harbor seals are prey- ing. This study takes the first step in understanding these interactions by using molecular genetic tools for spe- cies-level identification of salmonid skeletal remains recovered from Pacific harbor seal scats. Most studies of harbor seal food hab- its rely on morphological identification of indigestible parts (e.g. otoliths and bones) from scat. Otoliths can be used to identify fish species (Ochoa-Acuna and Francis, 1995) but are not always present in scats, which can result in an underestimate of the number of species and the number offish consumed (Har- vey, 1989). Skeletal remains in scat are much more common and generally bones can be identified to the species level (Cottrell et al., 1996). Morpho- logical identification is possible to the family level only with Pacific salmonid bones; however, genetic markers have the ability to discriminate between species, and the feasibility of extracting DNA from bones has been clearly dem- onstrated (Hochmeister et al., 1991). Mitochondrial DNA (mtDNA) has been widely employed in systematic studies (reviewed by Avise, 1994) mak- ing it ideal for animal species identifi- cation. In this study, we explored three regions of the mitochondrial genome that have been previously character- ized in Pacific salmonids (Shedlock et al., 1992; Domanico and Phillips, 1995: Parker and Kornfield, 1996). DNA sequencing of these regions provided an unambiguous way to de- termine species identity. Because high throughput sequencing can be prohibi- tively expensive for laboratories with limited facilities, restriction fragment length polymorphism (RFLP) analysis was also explored as an alternative for species identification. A previous study had established a species-specific poly- merase chain reaction (PCR) test for Pacific Northwest salmon and coastal trout species (McKay et al., 1997). The PCR test is based on the initial ampli- fication of an approximately 1000-bp fragment of the nuclear growth hor- mone 2 gene. The degraded state of the DNA isolated from bones recovered from scat has generally limited suc- cessful PCR to amplicons of 300 bp or less (data not shown). Furthermore, the amount of DNA isolated from bone fragments can be quite small; mtDNA is present in higher copy number per cell than is nuclear DNA. Thus, we considered mtDNA it to be a more 1 http://www.nwr.noaa.gov/lsalmon/salmesay specprof.htm. [Accessed June 17, 2003.] - Brown, R. F. and S. G. Kohlman. 1998. Trends in abundance and current status of the Pacific harbor seal tPhoca vitulina richardsi) in Oregon: 1977-1998. ODFW (Oregon Department of Fish and Wildlife i Wildlife Diversity Program Technical Report, 98-6-01. 16 p. [Available from ODFW, 7118 NE Vandenberg Ave. Corval- lis, OR 97333.] Manuscript approved for publication 9 October 2003 by Scientific Editor. Manuscript received 20 October 2003 at NMFS Scientific Publications Office. Fish. Bull. 102:213-220 (2004). 214 Fishery Bulletin 102(1) appropriate target for our assay. We chose to explore smaller regions of the mitochondrial genome, including the d-loop (Shedlock et al., 1992), a portion of the 16s ribosomal gene (Parker and Kornfield, 1996), and a region spanning the cytochrome oxidase III, t-RNA glycine, and ND3 genes (hereafter, referred to as COIII/ND3) (Domanico and Phil- lips, 1995 ). Significant interspecific variation but not intra- specific variation was observed in the COIII/ND3 region among salmonid species in previous studies, making it a particularly good candidate region for the development of diagnostic markers (Domanico and Phillips, 1995). In the first phase of the study, we developed and vali- dated the genetic tools for species identification by using frozen or ethanol-preserved tissues collected from known species and populations. In the second phase, we applied these tools to the identification of bone remains from har- bor seal scats collected at the Umpqua River (Oregon). A number of Pacific salmonid species are present in the Umpqua River but of particular concern were the sea- run cutthroat (Oncorhynchus clarki) that were listed as endangered under the ESA during 1996 (Johnson et al., 1999). Here we report the method associated with these two phases of the project. The salmonid bones that were identified genetically were incorporated into a larger study of the harbor seal diet and are reported in a companion paper (Orr et al., 2004). Materials and methods Salmonid tissue samples of known species have been collected over the past decade by geneticists from the Conservation Biology Molecular Genetics Laboratory (NOAA/NMFS/NWFSC) or generously donated by others (see "Acknowledgments" section) and maintained either frozen at -80°C or preserved in 95% ethanol. Reference populations were chosen to represent the geographic range of chinook salmon (O. tshawytscha), coho salmon (O. kisutch), sockeye salmon (O. nerka). pink salmon (O. gorbuscha), chum salmon (O. keta), steelhead (O. mykiss), coastal cutthroat trout (O. clarki clarki), and Yellowstone cutthroat trout ( O. clarki bouvieri ) ( collection information is listed in Table 1 ). Tissues were extracted with either a stan- dard phenol and chloroform extraction (Sambrook et al., 1989) or by using the DNAeasy 96-well tissue kit (Qiagen, Valencia, CA), following the manufacturer's instruction for tissue preparations. PCR primers were either taken directly from the published studies or designed from the reported sequences (Table 2). All primers were cycled with 2.5 mM MgCl 2 , 0.8 mM dNTPs, 0.04 ,«M primers, 0.25 units of Taq DNA polymerase (Promega, Madison, WI), 20-40 ng of DNA, and cresol red loading buffer (final concentration 2' < sucrose and 0.005% cresol red) for 35-45 cycles of 94°C for 45 seconds, 55°C for 45 seconds, and 72°C for 1 minute. A single individual of each salmonid species listed in Table 1 was sequenced for both the 16s rRNA and COIII/ ND3 regions. For DNA sequencing, the PCR products were purified with an Ultrafree MC column (Millipore, Beverly, MA i and resuspended in 20 ,uL of sterile water. The puri- fied product (1-10 uL depending on band intensity) was manually sequenced by using the USB ThermoSeque- nase cycle sequencing kit (Cleveland. OH), following the manufacturer's instructions. MACDNASIS (Miraibio Inc., Alameda. CA) and SEQUENCHER (Gene Codes Corp., Ann Arbor. MI) were used for sequence alignment and identifi- cation of diagnostic restriction enzyme cut sites. RFLP analysis of the unpurified COIII/ND3 PCR product was performed in the presence of a cresol red loading buf- fer. Restriction digests were incubated for 6 to 12 hours at 37°C for Dpn II, Sau 961, Fok I, Ase I, at 50° for Apo I, and at 60°C for Bst NI with the supplied buffers (NEB, Beverly, MA) and 1-5 units of enzyme. Restricted products were electrophoresed in a 47c 3:1 high-resolution and medium- resolution agarose gel (Continental Laboratory Products, San Diego, CA). DNA bands on the agarose gels were visualized with SYBR Gold, following the manufacturer's instructions (Molecular Probes, Eugene, OR). Personnel from the National Marine Mammal Laboratory (NMML) collected and processed harbor seal scat samples from the Umpqua River (Orr et al., 2004). NMML research- ers identified bone remains to either family or species level by using morphological characteristics of skeletal remains (Orr et al., 2004). From 39 harbor seal scats, 116 bones were identified morphologically to the genus Oncorhynchus and subjected to DNA analysis for species identification. For a positive DNA extraction control, we simulated digestion by treating coastal cutthroat bones (collected from Cowlitz Trout Hatchery, Winlock, WAi in a mixture of laboratory- grade trypsin (a digestive enzyme), baking soda, and water for 1 to 2 days. These trypsin-treated bones from a coastal cutthroat trout were used as positive DNA extraction and amplification control. To prepare samples for DNA extraction, bones were soaked in 107c sodium hypochlorite for 10 minutes to destroy any contaminating DNA that may have adhered to the outside of the bone and were rinsed twice in sterile water. Bones ranged in weight from 0.1 to 105.6 mg and included teeth, vertebrae, gillrakers, radials, and bone fragments (hereafter, all bony parts and teeth will be re- ferred to as "bone"). The bones were decalcified overnight in 0.5M EDTA solution (Hochmeister et al., 1991); fragile or small fragments were not decalcified. The EDTA was removed and the decalcified samples were extracted with the QIAamp tissue extraction kit (Qiagen. Valencia. CA) according to the manufacturer's instructions with the following modifications: 1) samples were proteinase K digested overnight or until completely digested; 2) 10 mg/«L yeast t-RNA carrier was added to the extractant before placement on the QIAQuick column; and 3) DNA was eluted in a reduced volume (50-100 «L) of buffer AE. Negative controls containing no tissue were simultane- ously processed to verify that the extraction was free of contaminating DNA. The trypsin-treated coastal cutthroat bones were used as positive extraction and PCR controls. Five to ten microliters of the extracted DNA were used in each amplification reaction. Amplification success was determined by electrophoresis through a 27c agarose gel followed by staining with ethidium bromide or the more sensitive SYBR Gold i Molecular Probes). Species identifi- NOTE Purcell et al.: Genetic identification of salmonid prey from scat of Phoca vitulina nchardsi 215 Table 1 Species, locations, and sampl ; sizes (n 1 examined for RFLP analysis. Species Population Location 71 Chinook Walker Creek Upper Frasier River. British Columbia 10 Grovers Creek Hatchery Puget Sound, Washington 12 Lookingglass Hatchery Snake River. Oregon 12 Carson Hatchery Columbia River, Washington 12 Abernathy Hatchery. Columbia River, Washington 11 Upper Sacramento Mainstem Sacramento River. California 10 Coho Edison Creek Oregon Coast 13 Sandy River Columbia River, Oregon 15 North Fork Moclips River Washington Coast 15 Minter Creek Hatchery Puget Sound, Washington 15 Yakoun River Queen Charlotte Island, British Columbia 7 Sockeye Nehalem Ponds Oregon Coast 4 Redfish Lake Snake River, Idaho 4 Alturas Lake Snake River, Idaho 2 Ozette Lake Washington Coast 14 Lake Wenatchee North Cascades.Washington 10 Babine Lake Central British Columbia 2 Kamchatka River Kamchatka Peninsula, Russia 9 Chum Hamma Hamma River Hood Canal. Washington 11 Frosty Creek Alaskan Peninsula 12 Utka River Chucotka Peninsula, Russia 9 Miomote River West Honshu. Japan 11 Pink Nisqually River South Puget Sound. Washington 6 Snohomish River Even Year North Puget Sound, Washington 12 Skagit River North Puget Sound, Washington 7 Hood Canal Hatchery Hood Canal, Washington 9 Steelhead Gaviota Creek South California Coast 4 Coquille River Oregon Coast 8 Upper Tucannon River Snake River, Washington 12 Finney Creek Puget Sound, Washington 12 Quinault Hatchery Washington Coast 12 Tigil River Kamchatka Peninsula. Russia 12 Cutthroat' Alsea River Oregon Coast 2 Alsea Hatchery Oregon Coast 3 Duwamish River Puget Sound Washington 12 Yellowstone River Yellowstone River. Montana 5 ' Cutthroat trout from the Yellowstone River are a different subspecies (O. clarki bouvieri) from the Washington and Oregon coastal cutthroat trout (O. clarki clarki). cation was accomplished by sequencing of either the d-loop or the COIII/ND3 region. RFLP analysis was performed as described above with the following modifications: Bst NI was excluded because it is redundant with Dpn II, the enzyme amount was reduced to 0.4-1.0 units per reaction, and incubation time did not exceed 2 hours. The COIII/ND3 primers are specific to the family Salmonidae. To test the possibility that the failure to obtain amplifica- tion with the COIII/ND3 primers was due to morphologi- cal misidentification of an Oncorhynchus species we used the 16s primers that are conserved across a broad set of taxa from Platyhelminthes through Chordata ( Parker and Kornfield, 1996). Results The COIII/ND3 and 16s sequences were confirmed for all seven salmonid naturally present in the Pacific Northwest (Figs. 1 and 2) and deposited in Genbank (COIII/ND3: AF294827-AF294833; 16S: AF296341-AF296347). Two chinook salmon were sequenced representing two Dpn II 216 Fishery Bulletin 102(1) Primer sequences size of amplified product in base Table 2 Dairs, and references for mitochondria] loci used in this study. Locus Primer sequences (5' to 3') Product size Reference d-loop COIII/ND3 16sV P2: tgt taa ace cct aaa cca g P4: gec gaa tgt aaa gca tct ggt F: tta caa teg ctg acg gcg R: gaa aga gat agt ggc tag tac tg F: tac ata aca cga gaa gac c R: gtg att gcg ctg tta tec 230 368 260 Shedlocketal.. 1992 Domanico and Phillips Parker and Kornfield, 1995 1997 Table 3 Restriction fragment length polymorphisms of the cytochrome oxidase III a id ND3 region digested w ith six restriction ?nzymes. The "A" haplotype does not cut with the enzyme, "B" cuts with the enzyme, and "C" cuts with the enzyme but at a different site than "B." Species Dpn II Sau 961 Fok I Asel Apo I Bst NI Chinook A/B ; B B A A A Coho A A B A A A Sockeye A A A A C B Chum A A A B C A Pink C A A B C C Steelhead A A A B B A Cutthroat A A A A A A 1 Spring-running chinook from the Columbia and Snake Rivers were polymorphic foi the Dpn II cut site. Spring chinook from Carson Hatchery (derived from the upper Columbia River spri ng-running ESU [evolutionary significam unit] I had the "A" haplotype at a frequency of 0.91 ( n=12) and spring chinook from Lookingglass Hatchery (Snake River spring-summer- ■unning ESU) had the "A" haplotype at a frequency of 0.83 (n = 12). All other chinook samples from Table 1 were invariant for the "B" h£ plotvpe. haplotypes (A and B) and their sequences are presented in Figure 1; the chinook salmon individuals were from the Upper Columbia River summer and fall ESU (Methow River, WA). A second intraspecific polymorphism in chi- nook salmon was observed at position 341 between our ND3 sequence and the published sequence (Domanico and Phillips, 1995) (Fig.l). Sufficient nucleotide varia- tion exists in the d-loop (Shedlock et al., 1992) and in the COIII/ND3 region ( Fig. 1 ) to distinguish among the salmon species by sequencing; both regions were used for bone identification. Six restriction enzymes were selected from the COIII/ ND3 sequence that appeared to distinguish among all the species (Dpn II, Sau 961, Fok I, Ase I, Apo I, and Bst NI) (Fig. 1). The Dpn II and Bst NI cut patterns are redundant in that only one of these enzymes is required for species identification when used in conjunction with the other four enzymes (however, only Dpn II exhibits the intraspecific chinook polymorphism, see below). Haplotype patterns for all species are listed in Table 3. The haplotypes were scored with a simple alphabetic system: "A" was uncut (368 base- pair (bp) band) and "B" was cut (the size differed depending on enzyme). A few of the enzymes had an alternative cut site, and the resulting haplotype we labeled "C." The "B" haplotype produced by Apo I occurs in steelhead and the bands migrate at 300 and 68 bp, whereas the bands of the "C" haplotype in sockeye, chum, and pink salmon migrate at 250 and 118 bp. The enzyme Bst NI also has two cut pat- terns: the sockeye salmon "B" haplotype bands migrate at 282 and 87 bp and the "C" haplotype bands in pink salmon migrate at 271 and 98 bp. The Dpn II "B" haplotype in chinook salmon creates two fragments, 290 and 80 bp; the "C" haplotype in pink salmon creates three fragments, 292, 53, and 24 bp. To confirm that the restriction enzyme polymorphisms were diagnostic within each species, we surveyed all seven Pacific salmon species representing multiple populations spanning a large geographic range (Table II. No intra- specific polymorphisms were detected among populations with the exception of chinook salmon (Tables 1 and 3). A single intraspecific polymorphism was found with the Dpn II enzyme in chinook salmon lineages in the Columbia and Snake River basins (Tables 1 and 3). Chinook salmon from the Snake River spring-summer run (Lookingglass NOTE Purcell et al.: Genetic identification of salmonid prey from scat of Phoca vitulina nchardsi 217 Chinook A Chinook B Coho Sockeye Chum Pink Steelhead Cutthroat Chinook A Chinook B Coho Sockeye Chum Pink Steelhead Cutthroat Chinook A Chinook B Coho Sockeye Chum Pink Steelhead Cutthroat Chinook A Chinook B Coho Sockeye Chum Pink Steelhead Cutthroat Chinook A Chinook B Coho Sockeye Chum Pink Steelhead Cutthroat Chinook A Chinook B Coho Sockeye Chum Pink Steelhead Cutthroat Chinook A Chinook B Coho Sockeye Chum Pink Steelhead Cutthroat 20 DpnII 40 60 * * * * TTACAATCGCTGACGGCGTGTACGGCTCTACTTTCTTTGTCGCCACCGGATTCCATGGCC . . . . A. .T. .A. .T. .A. DpnII 80 100 Apol/ Sau96I TACACGTGATTATTGGCTCAACCTTTCTAGCCGTTTGCCTTCTGCGACAGGTCCAATACC A . . . . A. . . . . A. .T. .A. :. .G. . . .G. .T.G. .A. .T. . AA . T . . AA.T. . AA.T. Fokl 140 160 180 ********** ACTTTACATCCGAACATCATTTTGGCTTTGAAGCTGCTGCTTGATATTGACACTTTGTAG .T. . . . .T. . . . .T. .G. 200 220 start tRNA glycine --> ACGTTGTGTGACTCTTCCTATACGTCTCTATTTACTGATGAGGCTCATAATCTTTCTAGT .A. .G. . A. . . . Asel ****** 260 BSTNI 280 Start ND3 — > ATTAACACGTATAAGTGACTTCCAATCACCCGGTCTTGGTTAAAATCCAAGGAAAGATAA . .G . TGA . TTA .TTA. . .CG. .T Apol DpnII 340 360 ****** **** TGAACTTAATTACAACAATCATCACTATTACCATCACATTRTCCGCAGTACTAGCCACTA .CG. .C.G. .CG. . . .A. . . .G. TTTCTTTC Figure 1 Aligned sequences of the 3' region of the cytochrome oxidase III gene (COM I, the tRNA glycine gene, and the 5' region of the ND3 gene for seven species of the genus Oncorhynchus. The cutthroat trout sequence is represented by the coastal cutthroat subspecies (O. clarki clarki). Chinook "A" refers to the "A" Dpn II haplotype; chinook "B" refers to the "B" Dpn II haplotype. Sequence identity relative to the chinook salmon "A" sequence is denoted by dots; nucleotide substitutions are indicated. The arrow at basepair (bp) 230 is the start of the tRNA glycine gene and the arrow at bp 300 is the start of the ND3 gene. Stars above the sequence correspond to restriction enzyme cut sites used in this study. At position 341 in chinook. the R represents an A or G. 218 Fishery Bulletin 102(1) Chinook Coho Sockeye Chum Pink Steelhead Cutthroat Chinook Coho Sockeye Chum Pink Steelhead Cutthroat Chinook Coho Sockeye Chum Pink Steelhead Cutthroat Chinook Coho Sockeye Chum Pink Steelhead Cutthroat 20 40 60 GGAGCTTTAGACACCAGGCAGATCACGTCAAACAACCTTGAATTAACAAGTAAAAACGCAGT G 80 100 120 GACCCCTAGCCCATATGTCTTTGGTTGGGGCGACCGCGGGGGAAAATTAAGCCCCCATGTGG 140 160 180 ATGGGGGCATGCCCCCACAGCCAAGAGCCACAGCTCTAAGCACCAGAATATCTGACCAAAAA T T...A 200 220 TGATCCGGCAAACGCCGATCAACGGACCGAGTTACCCTAG. . . Figure 2 Aligned sequences of a variable portion of the 16s gene for seven species of the genus Oncorhynchus. Sequence identity in relation to the chinook salmon "A" sequence is denoted by dots; nucleotide substitutions are indicated. Hatchery) and hatchery stocks descended from the Upper Columbia River spring run (Carson Hatchery) had the "A" (uncut) haplotype at a frequency of 83% and 91%, respec- tively, whereas those from the Lower Columbia River ESU were invariant for the "B" (cut) haplotype. The "B" hap- lotype was also invariant in the other lineages examined (Sacramento River, CA; Puget Sound, WA; and the Fraser River, BC). Despite this Dpn II polymorphism, the haplo- type patterns were still chinook-specific. Extractions from the trypsin-treated cutthroat trout bones, used as positive controls, were amplified consis- tently, but of the 116 salmonid bones from harbor seal scats, only 78 (67%) were amplified. Failed samples were repeated several times with all possible primer sets. Be- cause each scat contained multiple bones, we were able to amplify bones representing 35 of the 39 scats (90%). The smallest bone we successfully amplified was a O.'2-mg tooth and the largest was a 21.8-mg vertebra. There did not appear to be a relationship between bone size and DNA extraction success; no significant difference in mean bone size was detected between 32 bones that either amplified or failed (P=0.280; unpaired t-test; SYSTAT 8.0 [Chicago, IL| ). The bone samples that failed to amplify repeatedly were also tested by using the evolutionarily conserved 16s primers. Some samples were still refractory to PCR, indicating that the overall DNA quality or quantity was insufficient for this assay; however, those samples that did amplify were identified by sequencing as salmon. In an un- related study using river otter bones (data not presented), one bone sample morphologically identified as salmonid yielded a sequence with 100% identity to the published 16s sequence available for Northern squawfish {Ptychocheilus oregonensis) (Simons and Mayden, 1998). After verifying the specificity of the RFLP analysis for differentiating the Pacific salmon species, the assay was applied to the bone samples. Restriction enzyme digestion required some modification when applied to bone. On occa- sion, the restriction enzyme protocol developed for the fresh tissue resulted in degradation of the amplified bone PCR product. Enzyme amount and digestion times were scaled back for the analysis of the bone samples. The Fok I enzyme proved the most difficult for the bone samples, which was likely due to nonspecific restriction that occurs when the enzyme is present at a high concentration in relation to its target or if the reaction is allowed to digest for more than two hours. In some cases, only very weak amplification was achieved with the bone samples and it was difficult to get digestion without degradation. Although sequencing was the main technique used for bone identification. 23 bones in this study were identified by using the RFLP technique. Fourteen of these 23 bones were additionally confirmed by sequencing and the two techniques gave matching results. NOTE Purcell et al.: Genetic identification of salmonid prey from scat of Phoca vitulina nchardsi 219 Discussion This study focused on the development of tools for the genetic identification of Pacific salmon skeletal remains recovered from harbor seal scats. These tools help to deter- mine the diet of marine mammals and can also be used to address direct management questions regarding interspe- cific interactions in rivers such as the Umpqua River where salmonid species of concern (cutthroat trout (occur with pro- tected marine mammal species. The harbor seal diet in the Umpqua River consisted of nonsalmonid fish and chinook. coho, and steelhead; no cutthroat trout were observed in the scat samples (Orr et al., 2004). The majority of salmonid species identifications were possible only by using genetic methods because very few otoliths were recovered in the Umpqua River scats. A number of other sites exist were this technology may also be applicable. In Hood Canal ( WA) the summer chum salmon run is listed as threatened under the ESA. A report of seal diets in Hood Canal determined that 2T7c of the fish consumed by harbor seals were salmonids (Jeffries et al. 3 ). The study used both bones and otoliths, but only 25% of the samples contained otoliths that allowed species-level identification. In the Alsea River (OR), coho salmon are listed as threatened. A report by Riemer et al. 4 indicated that 69r of fish consumed by pinnipeds in the Alsea River are salmonids; none of the salmonid remains were morphologically identifiable to species. Extraction of DNA from bones can be done with a com- mercially available kit with minor modifications. In our study, only 67% of the bone DNA extracts could be ampli- fied by PCR. PCR failure could be due to DNA degradation during the digestive process or to environmental exposure after defecation. However, multiple bones are often present in scats and we were able to amplify DNA from at least one bone representative from 35 out of the 39 scats examined. Sequencing or RFLP analyses of the COIII/ND3 locus are both viable methods of identifying the seven common On- corhynchus species. This study used manual sequencing with radioactivity and we did have better results using this method compared to the RFLP method. A recently published study also identified restriction enzymes in the cytochrome B gene that distinguish among the salmonid species (Russell et al., 2000). The study reported diagnostic RFLP differences among these species but did not confirm the lack of intraspecific variation in a wide geographic sur- vey of each species. The goal of the cytochrome B RFLP as- say designed by Russell et al. (2000) was to identify salmon species found in processed food products but the primers 3 Jeffries, S. J., J. M. London, and M. M. Lance. 2000. Obser- vations of harbor seal predation on Hood Canal summer chum salmon run 1998-1999. Annual progress report to Pacific States Marine Fisheries Commission, 39 p. [Available from WDFW, Marine Mammals Investigations, 7801 Phillips Rd. SW, Tacoma, WA 98498.] 4 Riemer, S. D., R. F. Brown, B. E. Wright and M. I. Dhruv. 1999. Monitoring pinniped predation on salmonids at Alsea River and Rogue River, Oregon: 1997-1999. Oregon Depart- ment of Fish and Wildlife, Marine Mammal Research Program, Corvallis, OR, 36 p. [Available from ODFW, 7118 NE Vanden- berg Ave., Corvallis, OR 97333.] may also prove useful in species identification of bone re- mains. The 16s primer set is also valuable for bones that are morphologically unidentifiable. However for salmonid species identification, the 16s region contains fewer diag- nostic nucleotide substitutions in relation to the d-loop and the COIII/ND3 region. Overall, the techniques established here would be useful for further study of marine mammal diets and may have the potential for forensic application. Acknowledgments The authors acknowledge Robert Delong for suggesting this study. Jon Baker at the Northwest Fisheries Science Center and Paul Spruell at the University of Montana kindly provided cutthroat DNA. James Shaklee at the Washington Department of Fish and Wildlife kindly provided pink salmon samples. 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Phylogenetic relationships of the western North Amer- ican phoxinins (Actinopterygii: Cyprinidae I as inferred from mitochondrial 12S and 16S ribosomal RNA sequences. Mol. Phylogenet. Evol. 9:308-329. 221 Diel vertical migration of the bigeye thresher shark (Alopias superci/iosus), a species possessing orbital retia mirabilia Kevin C. Weng Barbara A. Block Tuna Research and Conservation Center Hopkins Marine Station of Stanford University 120 Oceanview Boulevard Pacific Grove, California 93950 E-mail address (for K. C. Weng): kevin cm wengia'stanford edu The bigeye thresher shark {Alopias superciliosus, Lowe 1841) is one of three sharks in the family Alopiidae, which occupy pelagic, neritic, and shallow coastal waters throughout the tropics and subtropics (Gruber and Compagno, 1981; Castro, 1983). All thresher sharks possess an elongated upper caudal lobe, and the bigeye thresher shark is distinguished from the other alopiid sharks by its large upward-looking eyes and grooves on the top of the head (Bigelow and Schroeder, 1948). Our present under- standing of the bigeye thresher shark is primarily based upon data derived from specimens captured in fisheries, including knowledge of its morpho- logical features (Fitch and Craig, 1964; Stillwell and Casey, 1976; Thorpe, 1997), geographic range as far as it overlaps with fisheries (Springer, 1943; Fitch and Craig, 1964; Stillwell and Casey, 1976; Gruber and Compagno, 1981; Thorpe, 1997), age, growth and maturity (Chen et al., 1997; Liu et al., 1998), and aspects of its reproductive biology (Gilmore, 1983; Moreno and Moron, 1992; Chen et al.. 1997). Limited information on the move- ment patterns of bigeye thresher sharks has been obtained from mark- recapture studies by using conven- tional tags. The longest straight-line movement of a conventionally tagged bigeye thresher shark to date is 2767 km from waters off New York to the eastern Gulf of Mexico (Kohler and Turner, 2001). The bigeye thresher shark has been captured on longlines set near the surface at night (0 m to 65 m, Fitch and Craig, 1964; Stillwell and Casey, 1976; Thorpe, 1997; Buencuerpo et al., 1998) and at 400 m to 600 m during the day (Nakamura 1 ). There is no published information available regarding its habitat and behavior, al- though Francis Carey tracked a bigeye thresher with an acoustic tag for six hours (Carey 2 ). Endothermy is a rare trait in fishes and has been demonstrated only in tunas (Thunnini), billfishes (Xiphiidae, Istiophoridae), and lamnid sharks (Lamnidael (Carey and Teal, 1969; Carey, 1971, 1982a; Block, 1991). In all endothermic fishes, the blood supply to aerobic tissues such as slow-twitch swimming muscle, visceral organs, extraocular muscles, retina, and brain occurs by counter-current heat exchangers known as retia mirabilia. The vascular supply reduces heat loss to the environment and enables heat conservation in metabolically active tissues (Carey, 1971). Lamnid sharks have retia mirabilia in the circulatory anatomy supplying the slow-oxidative swimming muscles, viscera, brain, and eyes (Burne, 1924; Block and Carey, 1985; Tubbesing and Block, 2000). In many lamnid species, tissue tempera- tures significantly above ambient have been recorded from freshly captured specimens and through telemetry stud- ies of swimming animals (Carey, 1971; Carey et al., 1981, 1982, 1985; McCos- ker, 1987; Goldman, 1997; Tubbesing and Block, 2000). The anatomy of alopiid sharks sug- gests that endothermy may occur in this family. The bigeye thresher and the common thresher (Alopias vulpinus) have centrally located slow-oxidative muscle and primitive retia mirabilia supplying blood to them (Carey, 1982b: Bone and Chubb, 1983). Burne (1924) noted a coiling of the pseudobranchial artery supplying the orbit and cranial regions in the common thresher. No internal tissue temperature measure- ments have been taken for free-swim- ming thresher sharks to ascertain whether heat is conserved in oxidative tissues. A freshly caught bigeye thresh- er shark was found to have a body-core thermal excess of 4°C (Carey, 1971); thus the species may have the ability to conserve metabolic heat. In this study we present electronic tagging data on the movements, div- ing behavior, and habitat preferences of the bigeye thresher shark based on two individuals studied with pop-up satellite archival tags. In addition, we provide a brief description of the orbital rete mirabile of the species. The presence of this highly developed rete mirabile within the orbital sinus suggests a physiological mechanism to buffer the eyes and brain from the large temperature changes associated with diel vertical migration, potentially conferring enhanced physiological per- formance. Materials and methods The movements of two bigeye thresher sharks were monitored with pop-up satellite archival tags (PAT tag version 2.00, Wildlife Computers, Redmond, WA; Gunn and Block, 2001; Marcinek et al., 2001). The first shark was cap- tured on a longline set in the Gulf of Mexico at 26.5°N, 91.3°W on 12 April 1 Nakamura. I. 2002. Personal commun. Institut National des Sciences et Technolo- gies de la Mer. 28 rue 2 Mars 1934, 2025 Salammbo. Tunisia. 2 Carey. F. G. (deceased). 1990. Personal commun. Woods Hole Oceanographic Institution, Woods Hole, MA 02543. Manuscript approved for publication 15 August 2003 by Scientific Editor. Manuscript received 20 October 2003 at NMFS Scientific Publications Office. Fish. Bull. 102:221-229 (2004). 222 Fishery Bulletin 102(1) 2000 in waters with a surface temperature of 21.9°C. The longline set contained 184 hooks set at depths between 70 m and 90 m and was made at 06:00 h and retrieved at 09:00 h. Circle hooks (L2045 20/0 circle hook, Eagle Claw, Denver, CO) were used to avoid hooking of the gut, and the shark in this study was hooked in the corner of the jaw. Hooks were baited with squid, and chemical light sticks were attached to every other line. The mass of the shark was visually estimated at 170 kg by an experienced commercial longline fisherman, which corresponds to a fork length of 229 cm, and a total length of 377 cm, based on the weight-length relationship of Kohler et al. (1995). According to this size estimation and the published size-at- maturity data (Chen et al., 1997; Liu et al., 1998), the shark was mature. The sex of the shark was not determined. The second shark was captured by hook-and-line gear near Hawaii at 19.5°N, 156.0°W on 13 May 2003 in waters with a surface temperature of 25.5°C. A baited circle hook set at a depth of 40 m was taken by the shark at 02:00 h. The mass of the shark was estimated at 200 kg by an experienced sportfishing captain, which corresponds to a fork length of 242 cm, and a total length of 400 cm (after Kohler et al., 1995). Given this size, the shark was mature (Chen et al., 1997; Liu et al., 1998), but its sex was not determined. Each pop-up satellite archival tag was attached to a tita- nium dart (59 mm x 13 mm) with a 17 cm segment of 136- kg monofilament line ( 300-lb test extra-hard Hi-Catch, Mo- moi Fishing Net Mfg. Co. Ltd., Ako City, Hyogo prefecture, Japan). The dart was inserted into the dorsal musculature of the shark at the base of the first dorsal fin, such that the tag trailed behind the fin. Following attachment of each tag, the fishing line was cut near the hook and both sharks swam away vigorously. Tagging locations were recorded by using the vessel's global positioning system. After the Gulf of Mexico shark was tagged, a depth-temperature recorder (ABT-1, Alec Electronics, Kobe, Japan) was used to deter- mine the temperature-depth profile of the upper 200 m of the ocean at the release site, at a resolution of 1 m. The pop-up satellite archival tag deployed in the Gulf of Mexico was programmed to collect pressure and tem- perature data at two-minute intervals, which the on-board software (PAT software version 1.06, Wildlife Computers, Redmond, WA) summarized into six-hour bins. This version of PAT software did not permit light-based geolocation. The summary data for each time interval comprised percentage distributions of time-at-depth and time-at-temperature, and profiles of temperature-at-depth. Temperature-depth profiles for this generation of software were recorded at intervals by measuring a single temperature at depths of 0, 25, 50, 75, 100, 125, 150, 200, 250, 300, 350, and 400 me- ters for the deepest dive. A mean temperature-depth profile was obtained by calculating the mean temperature at each specified depth for all profiles taken during the track. The endpoint position of the shark's track was obtained from the tag's radio transmissions to the Argos satellites. The six-hour bins were later combined into 12-hour bins repre- senting day (06:00 to 17:59 h local time) and night ( 18:00 to 05:59 h local time). At the time and place of tag deployment, sunrise occurred at 05:45 h and sunset at 18:28 h; whereas at the popup time and position, sunrise occurred at 05:02 h and sunset at 18:55 h (U.S. Naval Observatory), such that the day and night bin cutoffs were always within one hour of true sunrise and sunset. The pop-up satellite archival tag deployed off Hawaii col- lected data at 30-second intervals and summarized them into four-hour bins (PAT software version 2.08e, Wildlife Computers, Redmond, WA). The data were later combined into day and night bins as for the first tag, and the actual sunrise and sunset times were within one hour of 06:00 h and 18:00 h, respectively (U.S. Naval Observatory). The tag measured the minimum and maximum temperature at the surface, maximum depth, and six intermediate depths, for the deepest dive in each time interval. Temperature-depth profiles for each time interval were later constructed by us- ing the maximum temperature at each depth for all profiles taken during the track, and a curve was fitted by using a LOWESS (locally weighted regression smoothing) function (Cleveland, 1992). Version 2.08e PAT software collected light data for geolocation; however the diel dive pattern of the shark prevented the calculation of accurate positions. The vascular circulation to the brain and eyes was exam- ined in two bigeye thresher sharks: one common thresher shark and one pelagic thresher shark iAlopias pelagicus). A female bigeye thresher (1.5 m fork length) was captured off Cape Hatteras, North Carolina, and a male (1.4 m fork length) was captured in the Gulf of Mexico. The circula- tory systems of the bigeye threshers were injected with latex to aid in identifying the blood vessels. A male com- mon thresher (1.3 m fork length) was captured off Cape Hatteras, North Carolina, and was examined without being frozen or preserved. An immature female pelagic thresher shark (1.37 m fork length) was captured in the Indian Ocean. The orbital retia mirabilia were prepared from casts of the vascular circulation that were removed from the orbit. Results One bigeye thresher shark was tracked in the Gulf of Mexico for 60 days, and another in the Hawaiian Archi- pelago for 27 days, by using pop-up satellite archival tags. Both tags released from the sharks as programmed and transmitted summary information to Argos satellites. The tag deployed in the Gulf of Mexico popped up on 10 June 2000 at 27.95°N, 89.54°W (Fig. 1A). The shark moved a straight-line distance of 320 km during the track, start- ing from the central Gulf in depths exceeding 3000 m and moving to waters 150 km south of the Mississippi Delta where depths were approximately 1000 m. The second shark was tagged off the Kona coast of Hawaii and the tag released on 9 June 2003 at 24.2°N, 165.6°W. northeast of French Frigate Shoals, a straight-line distance of 1125 km from the deployment position (Fig. IB). The depth and temperature distributions of the bigeye thresher sharks showed a strong diel movement pattern (Fig. 2). The Gulf of Mexico shark spent the majority of the daytime (84 f * (±2.39H. mean [±1 SE]) below the ther- mocline between 300 m and 500 m and the majority of nighttime (809? [±4.7%], mean (±1 SE] ) in the mixed layer NOTE Weng and Block: Diel vertical migration in Alopias superaliosus 223 30° N 82°W 24°N 166 164 162 160 158 156°W Figure 1 Deployment (A) and end-point (•) positions for the two pop-up satellite archival tags attached to bigeye thresher sharks. Both tags surfaced on the programmed dates and transmitted data to Argos satellites. Pressure sensors in the tags confirmed that the tags remained attached to the sharks for the duration of the tracks. (A) In the Gulf of Mexico a shark was tagged and released on 12 April 2000 and the tag surfaced on 10 June 2000. The shark moved a straight-line distance of .320 km during the 60-day track. (B) In the Hawaiian Archipelago a shark was tagged on 13 May 2003 off Kona, Hawaii, and the tag surfaced on 9 June 2003 northeast of French Frigate Shoals. The shark moved a straight-line distance of 1125 km during the 27-day track. and upper thermocline between 10 m and 100 m (Fig. 2A). The shark spent most of the daytime in deeper waters of 6°C to 12°C (70% [±4.4%], mean [±1 SE]), and most of the nighttime in shallower waters from 20°C to 26°C (70% [±2.7%], mean [±1 SE]) (Fig. 2B). A temperature-depth profile taken by the tag during the first day of the shark's track closely matched a profile taken from the vessel with a bathythermograph (Fig. 3A). The mean temperature-depth profile for the 60-day track (Fig. 3B), when compared with the shark's depth preferences (Fig. 2A), indicated that 224 Fishery Bulletin 102(1) Percent time 00 75 50 25 25 50 75 100 0-5 5-10 10-50 50-100 ~ 100-150 g 150-200 200-250 250-300 300-500 500-700 700-1000 ,r Percent time 50 25 25 50 75 45 25 Percent time 5 25 28-30 26-28 24-26 22-24 20-22 18-20 16-18 14-16 10-14 10-12 6-10 <6 _i i . i i_ 45 j i Percent time 50 25 25 50 75 Figure 2 Depth and temperature distributions of two bigeye thresher sharks showing diel vertical migration. The tags recorded depth and temperature at two-minute (A, B> or 30-second (C, Di intervals; data are summarized into a series of bins for the full duration of each track. (Al Depth distribution for the Gulf of Mexico shark is shown as the percentage of day (□> and night spent within depth bins ranging from the surface to 1000 m. Error bars are 1 SE. (B) Temperature distribution for the Gulf of Mexico shark is shown as the percentage of day (□) and night spent within temperature bins ranging from 6°C to 30°C. The shark occupied cool waters during the day and warm waters during the night, a consequence of its deep daytime and shallow nighttime habitats. Error bars are 1 SE. (Cl Depth distribution for the Hawaii shark showing diel vertical migration. The shark spent most of the daytime at the base of the thermocline and must of the nighttime in the mixed layer and upper thermocline. iD) Temperature distribution for the Hawaii shark showing cool daytime and warm nighttime water temperatures. NOTE Weng and Block: Diel vertical migration in Alopias superaliosus 225 10 15 20 25 Temperature (C) 10 15 20 25 5 10 15 20 25 30 50 100-1 -jT 150 n Q_ q 200 -I 250 300 -I c 350 Figure 3 Temperature-depth profiles characterizing the thermal habitat of two bigeye thresher sharks. (Al Profiles of the Gulf of Mexico taken with a bathythermograph ( ) sampling at 1-m intervals deployed from the fishing vessel after the tagging event, and by the pop-up satellite archival tag (O) during the first day it was attached to the bigeye thresher shark. The two profiles are similar, indicating that the pop-up satellite archival tag is capable of characterizing thermal habitat. (B) Average temperature-depth profile for the 60-day track of the bigeye thresher shark in the Gulf of Mexico, showing a mixed layer shallower than 50 m and a thermocline extending beyond 400 m where waters were 10°C. The curve was fitted by using a LOWESS function and error bars are 1 SD, because 1 SE bars are invisible at this scale. (C) Average temperature-depth profile for the 27-day track of the bigeye thresher shark in the Hawaiian Archipelago, showing a shallow mixed layer a thermocline extending to approximately 600 m where waters were 6°C. Curve was fitted by using a LOWESS function and error bars are 1 SD, because 1 SE bars are invisible at this scale. the shark spent most of the daytime below the maximum gradient of the thermocline where temperatures were ap- proximately 10°C. On 25 April and 25 May 2000 the shark spent two hours of the day in waters between 4°C and 6°C. The Hawaii shark showed a similar diel vertical migration, with a lesser contrast between day and night (Fig. 2, C and D). The shark's modal nighttime depth was between 10 m and 50 m, whereas its modal daytime depth was between 400 m and 500 m (Fig. 2C). The temperature-depth profile for the Hawaii shark ( Fig. 3C ) indicated that it spent night- time above the thermocline and daytime below it. The bigeye thresher shark possesses a large arterial plexus between the posterior part of the eye and the wall of the orbital sinus, which appears to be a rete mirabile (Fig. 4). The orbital rete is bathed in venous blood from the orbital sinus and its anterior surface is contoured to the posterior surface of the eye. The sources of venous input to the orbital sinus remain unknown but are most likely within the surrounding extraocular muscles, which are large and comprise numerous aerobic muscle fiber types, and the retina. The rete shown in Figure 4 measures 72 mm by 49 mm by 19 mm. A reduced structure of similar form is also found in the pelagic thresher shark, but is not present in the common thresher. The orbital rete of the bigeye and pelagic threshers is larger in absolute size and occupies a greater cross sectional proportion of the orbital sinus than the lamnid orbital rete noted by Burne (1924). The arterial vessels form a finer and more orderly mesh- work than those in the lamnid sharks (Block and Carey, 1985; Tubbesing and Block, 2000) and appear similar in physical structure to the mammalian carotid rete used for brain cooling (Baker, 1982). Discussion Observations of the biological features of the bigeye thresher shark are rare and our knowledge of the species is based primarily on incidental catches in fisheries. Using pop-up satellite archival tags we were able to record behav- ior for a total of 87 days, and for individual periods up to 60 days without recapturing or following the study animals. We observed a pronounced diel alternation between warm shallow waters and cool deep waters and a rete mirabile that may confer physiological benefits during deep dives by stabilizing brain and eye temperatures. The depth data obtained for the bigeye thresher shark shows a striking pattern of diel vertical migration. The big- eye thresher shark's vertical movement pattern is distinct from those of most other sharks for which observations 226 Fishery Bulletin 102(1) Figure 4 Orbital rete of a bigeye thresher shark, showing the highly developed arterial network. The rete was injected with latex so that the arterial structure (72 mm by 49 mm by 19 mm) could be photographed. The structure of the rete and its position in the orbital sinus suggest that it may be a heat exchanging vascular plexus. Retention of metabolic heat in the eyes and brain would buffer these sensitive organs from the large ambient temperature swings that occur as a result of the bigeye thresher shark's diel vertical migrations. A smaller but similar structure is found in A. pelagicus but not in A. vulpinus. exist. In satellite or acoustic tracks, diel vertical migra- tion was not observed for white sharks (Carcharodon car- charias; Carey et al., 1982; Goldman and Anderson, 1999; Boustany et al., 2002), salmon sharks (Lamna ditropis; Block et al. 3 ), shortfin mako (Isurits oxyrhynchus; Carey, 1982b; Holts and Bedford, 1993), blue (Prionace glauca, Carey, 1982b; Carey and Scharold, 1990), sixgill (Hexan- chus griseus; Carey and Clark, 1995), tiger (Galeocerdo cuvier; Tricas et al., 1981; Holland et al., 1999), Pacific angel (Squatina californica; Standora and Nelson, 1977), whale [Rhincodon typus; Gunn et al., 1999), or scalloped hammerhead sharks (Sphyrna lewini; Klimley, 1993). Diel vertical migration has been observed in the sword- fish (Xiphias gladius; Carey and Robison, 1981; Carey 4 ), the megamouth shark (Megachasma pelagios; Nelson et al., 1997), and the school shark iGaleorhinus ga/eus; West Block, B.A., K.G.Goldman, and J. A. Musick. 1999. Unpubl. data. Hopkins Marine Station of Stanford University. 120 Oceanview Boulevard, Pacific Grove, CA 93950. Carey, R G. 1990. Further acoustic telemetry observations of swordfish. In Planning the future of billfishes; proceedings of the second international billfish symposium, 1-5 August 1988, Kailua-Kona, Hawaii (R. H. Stroud, ed.), p. 103-122. National Coalition for Marine Conservation, 3 North King St., Leesburg, VA 20176. and Stevens, 2001). Carey and Robison ( 1981) and Carey 4 studied swordfish in both the Pacific and Atlantic Oceans, acoustically tracking fish that moved from the surface at night to over 600 m during day. A megamouth shark showed a strong diel vertical migration when tracked acoustically off southern California (Nelson et al., 1997) with shallow nighttime and deep daytime distribution in a vertical range of 20 m to 160 m. West and Stevens (2001) studied school sharks in southern Australia using archival tags and noted that they ascended in the water column at night. The ambient temperature at the modal day- and night- time depths of the two bigeye thresher sharks differed by 15° to 16°C, requiring them to be eurythermal. The sharks spent most of the nighttime in shallow waters warmer than 20°C and commonly spent 8 or more hours during the daytime in deep waters cooler than 10°C. The coolest waters occupied had temperatures between 4°C and 6°C. The bigeye thresher sharks tracked in our study spent a higher proportion of their time in waters below 10°C than did white sharks (Carey et al., 1982; Boustany et al., 2002) and mako sharks (Carey and Scharold, 1990; Klimley et al.,2002). The presence of a rete mirabile in the cranial region may indicate a mechanism for heat conservation. Heat conservation in the brain and eyes would enable the big- NOTE Weng and Block: Diel vertical migration in Alopias superaliosus 227 eye thresher shark to prolong its foraging time beneath the thermocline, as we observed for both of the sharks tagged in our study. The retina and brain are extremely temperature sensitive in most vertebrates and the large changes in depth and temperature recorded would impose significant effects on the biochemical processes occurring in these tissues (Block and Carey, 1985; Block, 1994). Delayed responses to retinal stimulation can be caused by cooling, whereas increased noise and random firing of neurons can be caused by warming — both responses having adverse affects on sensory function (Konishi and Hickman, 1964; Friedlander et al., 1976; Prosser and Nelson, 1981). Anatomical and physiological adaptations to warm the brain and eyes have evolved independently in divergent pelagic fish lineages, including the lamnid sharks (Block and Carey, 1985), billfishes of the Xiphiidae and Istiophori- dae (Carey, 1982a; Block. 1983) and some scombrid fishes (Linthicum and Carey, 1972). A cranial rete mirabile also has been identified in mobulids (Schweitzer and Notarbar- tolo di Sciara, 1986) and is thought to be a heat exchanger (Alexander, 1995, 1996). Although it is premature to sug- gest that the orbital rete of the bigeye thresher shark is a heat exchanger without direct evidence of elevated tissue temperatures in the brain and eyes, the structure is larger than the rete mirabile of lamnid sharks, for which elevat- ed brain and eye temperatures have been demonstrated (Block and Carey, 1985). The anatomical arrangement of an arterial plexus in an orbital sinus is correlated with heat conservation strategies in other vertebrates (Baker, 1982). The phylogenetic relationships of the alopiid and lamnid sharks (Compagno, 1990; Naylor et al., 1997) sug- gest that endothermic traits evolved independently in the two families. This note presents new information on the depth and ambient temperature preferences of the bigeye thresher shark based on observations of two individuals, as well as the anatomy of the orbital rete mirabile, which appears to function as a vascular heat exchanger. Behavior of many organisms varies with ontogeny, season and location; therefore the present study should be considered as only the beginning of an understanding of the bigeye thresher shark's physical habitat preferences and adaptations to temperature change. Further studies on individuals of different sizes and in different regions will enhance our understanding of the behavior, and morphological and physiological adaptations, of the bigeye thresher shark to variations in temperature. Acknowledgments This research was supported by grants from the National Marine Fisheries Service, the National Fish and Wildlife Federation and the Packard Foundation. The authors wish to thank Captain David Price and crew of the FV Allison, and Captain John Bagwell and crew of the FY Silky. Shana Beemer provided scientific assistance on the cruise and Captain McGrew Rice assisted in tagging and releasing the Gulf of Mexico shark. This research was conducted under Scientific Research Permit TUNA-SRP-2000-002, issued by the Office of Sustainable Fisheries, National Marine Fisheries Service, Silver Spring, MD 20910. Literature cited Alexander, R. L. 1995. Evidence of counter-current heat exchanger in the ray, Mobu la tarapacana (Chondrichthyes: Elasmobranchii: Batoidea: Myliobatiformes). J. Zool. (Lond) 237:377-384. 1996. Evidence of brain-warming in the mobulid rays, Mobula tarapacana and Manta birostris (Chondrichthyes: Elasmobranchii: Batoidea: Myliobatiformes). Zool. J. Linn. 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Highly directional swimming by scalloped hammer- head sharks, Sphyrna lewini, and subsurface irradiance. temperature, bathymetry, and geomagnetic field. Mar. Biol. 117:1-22. Klimley, A. P., S. C. Beavers, T. H. Curtis, and S. J. Jorgensen. 2002. Movements and swimming behavior of three species of sharks in La Jolla Canyon, California. Environ. Biol. Fishes 63:117-135. Kohler, N. E., J. G. Casey, and P. A. Turner. 1995. Length-weight relationships for 13 species of sharks from the western North Atlantic. Fish. Bull. 93:412-418. Kohler, N. E., and P. A. Turner. 2001. Shark tagging: A review of conventional methods and studies. Environ. Biol. Fishes 60:191-223. Konishi, J., and C. P. Hickman. 1964. Temperature acclimation in the central nervous system of rainbow trout [Salmo gairdnerii). Comp. Bio- chem. Physiol. 13:433-442. Linthicum, D. S., and F. G. Carey. 1972. Regulation of brain and eye temperatures by the bluefin tuna. Comp. Biochem. Physiol. A Comp. Physiol. 43:425-433. Liu. K.-M.. P. -J. Chiang, and C.-T Chen. 1998. Age and growth estimates of the bigeye thresher shark, Alopias superciliosus. in northeastern Taiwan waters. Fish. Bull. 96:482-491. Marcinek, D. J., S. B. Blackwell, H. Dewar. E. V. Freund. C. Farwell, D. Dau, A. C. Seitz. and B. A. Block. 2001. Depth and muscle temperature of Pacific bluefin tuna examined with acoustic and pop-up satellite archival tags. Mar. Biol. 138:869-885. McCosker, J. E. 1987. The white shark, Carcharodon carcharias. has a warm stomach. Copeia 1987:195-197. Moreno, J. A., and J. Moron. 1992. Reproductive biology of the bigeye thresher shark Alopias superciliosus Lowe 1839. Aust. J. Mar. Freshat. Res. 43:77-86. Naylor, G. J. P., A. P. Martin, E. G. Mattison, and W. M. Brown. 1997. Interrelationships of lamniform sharks: Testing phv- logenetic hypotheses with sequence data. In Molecular systematics of fishes (T. D. Kocher and C. A. Stepien, eds.), p. 199-218. Academic Press, San Diego, CA. Nelson. D. R., J. N. MeKibben. W. R. Strong Jr., C. G. Lowe, J. A. Sisneros, D. M. Schroeder. and R. J. Lavenberg. 1997. An acoustic tracking of a megamouth shark, Mega- chasma pelagios: A crepuscular vertical migrator. Envi- ron Biol. Fishes 49:389-399. NOTE Weng and Block: Diel vertical migration in Alopias superahosus 229 Prosser, C. L., and D. O. Nelson. 1981. Role of nervous systems in temperature adaptation of poikilotherms. Annu. Rev. Physiol. 43:281-300. Schweitzer. J., and G. Notarbartolo di Sciara. 1986. The rete nurabile cranica in the genus Mobula: a com- parative study. J. Morphol. 188:167-178. Springer, S. 1943. A second species of thresher shark from Florida. Copeia 1943:54-55. Standora, E. A., and D. R. Nelson. 1977. A telemetric study of the behavior of free swimming Pacific angel sharks Squatina californica. Bull. South. Calif. Acad. Sci. 76:193-201. Stillwell, C. E., and J. G. Casey. 1976. Observations on the bigeye thresher shark, Alopias superciliosus, in the western North Atlantic. Fish. Bull. 74:221-225. Thorpe, T. 1997. First occurrence and new length record for the bigeye thresher shark in the northeast Atlantic. J. Fish Biol. 50: 222-224. Tricas, T. C. L. R. Taylor, and G. Naftel. 1981. Diel behavior of the tiger shark Galeocerdo cuvier at French Frigate Shoals Hawaiian Islands USA. Copeia 1981:904-908. Tubbesing, V. A., and B. A. Block. 2000. Orbital rete and red muscle vein anatomy indicate a high degree of endothermy in the brain and eye of the salmon shark. Acta Zool. (Stockh.) 81:49-56. West, G. J., and J. D. Stevens. 2001. Archival tagging of school shark, Galeorhinus galeus. in Australia: Initial results. Environ. Biol. Fishes 60: 283-298. Fishery Bulletin 102(1) 231 Superintendent of Documents Publications Order Form *5178 I I YrLo, please send me the following publicatic tions: Subscriptions to Fishery Bulletin for $55.00 per year ($68.75 foreign) The total cost of my order is $ . 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It is also available limited numbers to libraries, research institutions, Stale and Federal agencies, and in exchange for other scientific publicat ii U.S. Department of Commerce Seattle, Washington Volume 102 Number 2 April 2004 Fishery Bulletin Contents The conclusions and opinions expressed in Fishery Bulletin are solely those of the authors and do not represent the official position of the National Marine Fisher- ies Service (NOAAi or any other agency or institution. The National Marine Fisheries Service iNMFS) does not approve, recommend, or endorse any proprietary product or pro- prietary material mentioned in this pub- lication. No reference shall be made to NMFS, or to this publication furnished by NMFS. in any advertising or sales pro- motion which would indicate or imply that NMFS approves, recommends, or endorses any proprietary product or pro- prietary material mentioned herein, or which has as its purpose an intent to cause directly or indirectly the advertised product to be used or purchased because of this NMFS publication. Articles 233-244 Archer, Frederick, Tim Gerrodette, Susan Chivers, and Alan Jackson Annual estimates of the unobserved incidental kill of pantropical spotted dolphin (Stenella attenuata attenuata) calves in the tuna purse-seme fishery of the eastern tropical Pacific 245-250 Chernova, Natalia V., and David L. Stein A remarkable new species of Psednos (Teleostei: Liparidae) from the western North Atlantic Ocean 251-263 Chiang, Wei-Chuan, Chi-Lu Sun, Su-Zan Yeh, and Wei-Cheng Su Age and growth of sailfish Ustiophorus platypterus) in waters off eastern Taiwan 264-277 Clark, Randall D., John D. Christensen, and Mark E. Monaco, Philip A. Caldwell, Geoffrey A. Matthews, and Thomas J. Minello A habitat-use model to determine essential fish habitat for juvenile brown shrimp (Farfantepenaeus aztecus) in Galveston Bay, Texas 278-288 Delgado, Gabriel A., Claudine T. Bartels, Robert A. Glazer, Nancy J. Brown-Peterson, and Kevin J. McCarthy Translocation as a strategy to rehabilitate the queen conch (Strombus gigas) population in the Florida Keys 289-297 Lage, Christopher, Kristen Kuhn, and Irv Kornfield Genetic differentiation among Atlantic cod (Gadus morhua) from Browns Bank, Georges Bank, and Nantucket Shoals 298-305 Lenihan, Hunter S., and Charles H. Peterson Conserving oyster reef habitat by switching from dredging and tonging to diver-harvesting Fishery Bulletin 102(2) 306-327 Macewicz, Beverly J., John R. Hunter, Nancy C. H. Lo, and Erin L. LaCasella Fecundity, egg deposition, and mortality of market squid (Loli/go opalescens) 328-348 Orr, James W., and James E. Blackburn The dusky rockfishes (Teleostei: Socrpaeniformes) of the North Pacific Ocean resurrection of Sebastes variabilis (Pallas, 1814) and a redescnption of Sebastes ci/iatus (Tilesius, 1813) 349-365 Powers, Joseph E. Recruitment as an evolving random process of aggregation and mortality 366-375 Szedlmayer, Stephen T., and Jason D. Lee Diet shifts of juvenile red snapper (Lut/anus campechanus) with changes in habitat and fish size 376-388 Webb, Stacey, and Ronald T. Kneib Individual growth rates and movement of juvenile white shrimp (Litopenaeus setiferus) in a tidal marsh nursery Notes 389-392 Forsythe, John, Nuutti Kangas, and Roger T. Hanlon Does the California market squid (Loligo opalescens) spawn naturally during the day or at night? A note on the successful use of ROVs to obtain basic fisheries biology data 393-399 Kotas, Jorge E., Silvio dos Santos, Venancio G. de Azevedo, Berenice M. G. Gallo, and Paulo C. R. Barata Incidental capture of loggerhead (Caretta caretta) and leatherback (Dermochelys conacea) sea turtles by the pelagic longline fishery off southern Brazil 400-405 Yang, Mei-Sun Diet changes of Pacific cod (Gadus macrocephalus) in Pavlof Bay associated with climate changes in the Gulf of Alaska between 1980 and 1995 406 Subscription form 233 Abstract— We estimated the total number of pantropical spotted dolphin (Stenella attenuata) mothers killed without their calves ("calf deficit") in all tuna purse-seine sets from 1973-90 and 1996-2000 in the eastern tropical Pacific. Estimates were based on a tally of the mothers killed as reported by color pattern and gender, several color-pattern-based frequency tables, and a weaning model. Over the time series, there was a decrease in the calf deficit from approximately 2800 for the western-southern stock and 5000 in the northeastern stock to about 60 missing calves per year. The mean deficit per set decreased from approxi- mately 1.5 missing calves per set in the mid-1970s to 0.01 per set in the late-1990s. Over the time series exam- ined, from 75% to 95% of the lactating females killed were killed without a calf. Under the assumption that these orphaned calves did not survive with- out their mothers, this calf deficit rep- resents an approximately 14% increase in the reported kill of calves, which is relatively constant across the years examined. Because the calf deficit as we have defined it is based on the kill of mothers, the total number of mis- sing calves that we estimate is poten- tially an underestimate of the actual number killed. Further research on the mechanism by which separation of mother and calf occurs is required to obtain better estimates of the unob- served kill of dolphin calves in this fishery. Annual estimates of the unobserved incidental kill of pantropical spotted dolphin {Stenella attenuata attenuato) calves in the tuna purse-seine fishery of the eastern tropical Pacific Frederick Archer Tim Gerrodette Susan Chivers Alan Jackson Southwest Fisheries Science Center National Marine Fisheries Service 8604 La Jolla Shores Dr. La Jolla, California 92037 E-mail address (for F Archer): enc.archeriainoaa.gov Manuscript approved for publication 7 January 2004 by Scientific Editor. Manuscript received 20 January 2004 at NMFS Sceintific Publications Office. Fish. Bull. 102:233-244 (2004). In the eastern tropical Pacific (ETP), yellowfin tuna (Thunnus albacares) are frequently found swimming under schools of pantropical spotted ( Stenella attenuata) and spinner (S. longirostris) dolphins. For the past four decades, the ETP yellowfin tuna fishery has made use of this association by chasing the more visible dolphins at the sur- face and using purse-seines to encircle the schools "carrying" the tuna (NRC, 1992). The large bycatch of dolphins in this fishery has become widely known as the "tuna-dolphin issue" (Gerro- dette, 2002). During the 1960s, the number of dolphins killed by the fishery was estimated to be 200,000-500,000 per year (Wade, 1995), and two stocks of spotted and spinner dolphins were reduced to fractions of their previous sizes (Smith, 1983; Wade et al. 1 ). Along history of technological innovations by fishermen, laws and fishing regula- tions, dolphin quotas, eco-labeling of "dolphin-safe" tuna, and a comprehen- sive international observer program (Gosliner, 1999; Hall et al, 2000; Ger- rodette, 2002) has reduced the dolphin bycatch to less than 1% of its former level. The reported bycatch in recent years is less than 2000 dolphins per year for all species combined (IATTC, 2002). Although the reported kill has dra- matically decreased, recent studies suggest that there is little evidence that the stocks are growing close to expected rates (Wade et al. 1 ). One hy- pothesis for this lack of recovery has been that there are unobserved kills of dolphins during tuna purse-seine sets. Archer et al. (2001) presented evidence of an under-representation of suckling spotted and spinner dolphin calves in a sample of tuna purse-seine sets in the eastern tropical Pacific. Given that some of these missing calves are still dependent on their mothers for nutri- tion, it is likely that once separated they would die and this under-repre- sentation represents some degree of unobserved kill. In Archer et al. (2001), the sample of sets examined was limited to those sets in which all of the animals killed had biological data collected by techni- cians aboard the tuna vessel. Calves still dependent on their mothers in the kill were identified by five intervals of body length, chosen to cover a range of 1 Wade, P. R.. S. B. Reilly. and T. Gerro- dette. 2002. Assessment of the popula- tion dynamics of the northeastern offshore spotted and the eastern spinner dolphin populations through 2002. National Oceanographic and Atmospheric Admin- istration Administrative Report LJ-02- 13. 58 p. Southwest Fisheries Science Center. 8604 La Jolla Shores Dr., La Jolla, CA 92037. 234 Fishery Bulletin 102(2) calf sizes. Because of this approach, it was not possible to derive a single estimate of the number of missing calves or to extrapolate their estimate to sets not used in this analysis. In the current study, we present a different method of estimating the number of missing calves in each set where offshore spotted dolphins (S. attenuate! attenuata) were killed. For brevity, we call the shortage of calves in the kill in relation to the number of lactating females in the kill the "calf deficit." We examined the western-southern and northeastern offshore stocks separately according to the geographic boundaries described by Dizon et al. (1994). As they age, spotted dolphins change color through five color phases (Perrin, 1970). We used the color-phase frequency distribution of the kill in conjunction with age- and color-based frequency distributions from a sample of the kill to estimate the total number of missing calves in each stock, along with confidence intervals derived from bootstrap replications. This method also allowed us to examine the calf deficit from sets in recent years from which we did not have biological samples and to examine the time series of available years for evidence of a trend in the calf deficit. Methods Since 1973, observers have been randomly placed on tuna purse-seine vessels. For each spotted dolphin killed during an observed set, observers attempted to record the sex and the color phase of the dolphin ( neonate, two-tone, speckled, mottled, and fused, see Perrin, 1970). From the National Marine Fisheries Service (NMFS) set log database, we obtained the number of northeastern and western-south- ern offshore spotted dolphins (by gender and color phase) killed in every observed set from 1973 to 1990. The Inter- American Tropical Tuna Commission (IATTC) provided the same data from 1996 to 2000. Proration In each set, color phase or gender (or both) may not have been recorded for some dolphins. Assuming that the distri- bution of the demographic composition of this missing data is equivalent to the overall demographic composition of the kill, we allocated the number of dolphins cf unknown color phase (nu) to unknown gender in each color phase (jigu) according to the following formula, ngu : = ngu, + N. I", (1) where c = one of the five color phases (neonate to fused I; N c = the total number of dolphins in each color phase in the entire data set; and ngu\. = the new number of dolphins in each color phase where gender is unknown, including the indi- viduals of prorated unknown color phase The number of male (nm' c ) or female (nf' c ) dolphins in a color phase was calculated as nm,. = nm + ngu, Nm. Nni + Nf\ j nf c '=nf t + ngu w Nm c +Nf r (2) (3) where Nm c and Nf c are the total number of males and females, respectively, observed in that color phase in the entire data. Table 1 gives the sample size of sets for both stocks by year, as well as the fraction of the kill of unknown gender and color phase that were prorated as described above. Number of suckling calves As time permitted, NMFS observers would also collect biological data from a subset of the kill. For this study, we used ages estimated from teeth collected for a study of spotted dolphin growth and reproduction (Myrick et al., 1986 ). The specimens used were a random sample of all male and female spotted dolphins collected between 1973 and 1978 for which total body length was recorded and teeth were collected. However, additional specimens with lengths less than 150 cm were selected in order to match as closely as possible the length distribution of the aged sample to the underlying length distribution of the spotted dolphins in the kill. This was necessary because observ- ers did not generally collect teeth from smaller, younger animals. Later, another sample of female spotted dolphins was selected from specimens collected in 1981. Specimens were aged as described in Myrick et al. ( 1986 ). The final data set used in our analyses included age estimates for 1094 female spotted dolphin specimens and 798 male specimens. Of these, 649 females and 457 males belonged to the northeastern stock and had color phase re- corded. These 1 106 dolphins were used to generate the age frequency distribution for each color phase (F , Table 2). (4) '""Is,, where S ac = the number of samples of age a in color phase c. The oldest age recorded was 36 years. To derive an age distribution for the dolphins killed in each tuna set, we estimated the number of dolphins in each age class (n a ) as »,,=x^„ i 5) where n' the sum of nm' c and «/' (the number of males and females in each color phase after prora- tion from Equations 2 and 3). Archer et al.: Estimates of the incidental kill of Stenella attenuata attenuata calves in the tuna purse-seine fishery 235 Table 1 Sample sizes of NMFS (1973-1990) and IATTC (1996-2000) observed sets with spotted dolphin kill made on two stocks of pan- tropical spotted dolphins iStenella a ttenuata) by yea r. Northeastern stock Western-southern stock Fraction of Fraction of Fraction of Fraction of kill of kill of kill of kill of Number of Observed unknown unknown Number of Observed unknown unknown Year sets with kill kill color phase gender sets with kill kill color phase gender 1973 332 5242 0.09 0.31 75 1199 0.17 0.34 1974 515 5864 0.16 0.23 92 1715 0.10 0.31 1975 554 8073 0.31 0.19 75 1702 0.30 0.20 1976 239 2376 0.24 0.25 356 6293 0.27 0.23 1977 467 2146 0.23 0.26 528 3358 0.18 0.32 1978 224 1016 0.18 0.41 329 3998 0.37 0.34 1979 218 1045 0.38 0.27 168 1262 0.40 0.14 1980 165 1132 0.45 0.28 106 1206 0.73 0.13 1981 121 815 0.46 0.13 112 1346 0.48 0.12 1982 171 1696 0.51 0.22 159 1966 0.37 0.38 1983 12 177 0.80 0.08 35 148 0.32 0.35 1984 43 294 0.37 0.25 71 961 0.48 0.15 1985 186 2625 0.39 0.40 54 381 0.49 0.13 1986 150 1816 0.48 0.28 132 1818 0.60 0.22 1987 630 3327 0.25 0.31 175 1768 0.62 0.14 1988 207 1142 0.18 0.27 107 479 0.36 0.34 1989 293 1096 0.29 0.25 323 2793 0.48 0.14 1990 157 515 0.16 0.31 121 829 0.35 0.13 1996 273 724 0.27 0.44 161 374 0.18 0.54 1997 163 393 0.15 0.42 274 738 0.24 0.48 1998 161 260 0.21 0.51 125 236 0.19 0.46 1999 189 317 0.18 0.58 88 159 0.11 0.56 2000 146 291 0.23 0.47 115 250 0.20 0.61 In Equation 4, an age distribution was generated for each color phase, and then the number of dolphins in each age class was summed across all color phases. To estimate the number of calves in each set, we used this age distribution in conjunction with a weaning model developed from a study of the stomach contents and ages of calves (Archer and Robertson, in press). The model predicts the probability that an animal of a given age (a) will be suckling: Pi milk) (6) 1 + e 1 The estimated number of calves (JV„„; f ) in a set is then N. calf IK calf Pmilk). (7) In our estimate of N cal ? we chose to use only the first four age classes (0 to 3) because P(milk) 4 was extremely small (2xl0~ 4 ). These age classes allowed us to decrease computational time without significantly affecting the estimates. Number of lactating females Observers visually examined the mamillaries of the 649 females used in the age distribution above (Eq. 4) for the presence of milk as part of the suite of biological data collected. Using these data in conjunction with the color phase of these females, we calculated the fraction of lactat- ing females in each color phase (Flac v ), Flac ■S/ac Sfem, (8) where Slac v and Sfem c the number of females that were lactating and the total number of females in color phase c of the samples examined. Flac c was 0.00, 0.01, 0.04, 0.22, and 0.50 for neonate, two- tone, speckled, mottled, and fused specimens, respectively. The estimated number of lactating females (N lac ) in a set was then N lai . = ^(nf; Flac v (9) 236 Fishery Bulletin 102(2) Calf deficit As described in Archer et al. (2001), the calf deficit (D) in each set was calculated by subtracting the number of calves (iV ca ;J from the number of lactating females (N [ac ). If this value was zero or less, then D was set to zero to indicate that there were enough calves to account for all lactating females killed ( Fig. 1 1, D- if7V„„ EstLacKill (11) (12) (13) where ZD = the total observed calf deficit in each year; ObsSets = the number of observed sets used in the analysis, including those sets without a dolphin kill; ObsKill = the number of dolphins killed in the observed sets; and EstLacKill = the total estimated number of lactating females killed. The above analysis was conducted each year. Estima- tion error was evaluated with 20,000 bootstrap replicates for each year. For each replicate, the sets within that year were randomly resampled. The frequency tables F ni . and Flac t were also recalculated by resampling the list of bio- logical specimens. The parameters for the weaning model, P(milk) a , were estimated again by resampling the 29 calves and by fitting the logistic model to the new data set as described in Archer and Robertson (in press). All resa- mpling was done with replacement. N ral p N lac , and D were estimated as described above for each set, and D s , D h , and Dj were calculated for the replicate. The 95°; confidence intervals for Af n// , N lac , D, D s , D k , and D/ were estimated from the 2.5'; and 97.5% quantiles of the distributions of the bootstrap replicate values. The total calf deficit (D total ) was estimated as the deficit per dolphin killed (D k ) multiplied by the total number of dolphins killed [N kiUed ) by stock each year, Table 2 Age- class frequency distribution for e ich color phase CF ac ). Age Two- (yr) Neonate tone Speckled Mottled Fused 0.80 0.12 1 0.20 0.32 2 0.31 0.04 3 0.16 0.18 0.01 4 0.05 0.14 0.02 5 0.02 0.13 0.03 6 0.13 0.04 0.01 7 0.06 0.05 8 0.10 0.06 9 0.06 0.07 0.01 10 0.01 0.10 0.01 11 0.01 0.14 0.03 12 0.01 0.08 0.02 13 0.04 0.07 0.03 14 0.03 0.07 0.03 15 0.06 0.06 16 0.01 0.01 0.06 0.07 17 0.01 0.03 0.07 18 0.01 0.07 19 0.03 0.09 20 0.03 0.07 21 0.01 0.08 22 0.06 23 0.01 0.07 24 0.01 0.04 25 0.01 0.04 26 0.04 27 0.01 0.03 28 0.01 0.02 29 0.01 30 0.01 0.02 31 0.01 32 33 0.01 34 35 36 0.01 For the period 1973-84, annual values of N hlllcil for each stock were provided by the IATTC (Joseph 2 ). For 1984-90 and 1996-2000. values were published by IATTC (2002). In the bootstrap estimation of the 959? CI around D lntal , for the 1973-90 period, each replicate was randomly sampled from a normal distribution by using the estimated total kill standard error. For 1996-2000, the total kill was reported to be exact; therefore the total kill was used without variance in all replicates. D total D l; * N kmd (1 li - Joseph. J. 1994. Letter of September 6 to Michael Tillman. 2 p. Southwest Fisheries Science Center. 8604 La Jolla Shores Dr., LaJolla. CA 92037. Archer et al.: Estimates of the incidental kill of Stene/la attenuata attenuate/ calves in the tuna purse-seine fishery 237 Fraction of females lactating, by color (1973-78, 1981): Flac Number of lactating females killed: N h „ Tally of females, by color: nj ' Tally of dolphins killed, by color and sex, from set log ( 1973-90. 1996-2000) Tally of dolphins, by color: n\ Fraction of dolphins in age class, by color (1973-78, 1981): F at Number of dolphins killed, by age: N a Probability of suckling, by age (1989-91): P(milk) a Calf deficit: D Number of suckling calves killed: N ca y Figure 1 Diagram of the analytical method used to estimate the spotted dolphin (Stenella attenuata attenuata) calf deficit in each set as described in the text. Boxes identify original data that were bootstrapped to produce confidence intervals. Values in parentheses are years for which data were available. In a subset of the sets that we examined, every indi- vidual killed had been examined and biological samples had been collected from it; therefore, we knew the actual number of lactating females killed. There were 1108 of these "100% sampled" sets on the northeastern stock, and 697 on the western-southern stock from 1973 to 1990. We evaluated the accuracy of our frequency-based method by conducting a paired /-test between our estimate of the number of lactating females and the number observed in each of these sets. Stomach-content data were not available for every animal in these 100% -sampled sets; therefore, we did not know the actual number of suckling calves. However, we also used paired /-tests to compare our estimate of the number of suckling calves in each set with the number of animals smaller than 122 cm, which was the estimated length at which the probability of milk in the stomach was 0.5, given the weaning model of Archer and Robertson (in press). Likewise, our estimate of the calf deficit was compared with the deficit as estimated by using a cutoff length of 122 cm. These tests were done to determine if the method in the present study would produce significantly different results from the method used in the previous study Paired /-tests were conducted for each year sepa- rately, as well as for all years combined. A power analysis was also performed for these paired /-tests to determine the minimum detectable difference at which we could re- ject the null hypothesis of no difference between methods given observed sample sizes and variability. Results The calf deficit as a fraction of the number of dolphins killed (D k ) increased slightly during the mid-1970s but remained relatively constant throughout the rest of the time series at approximately 0.14 missing calves per dol- phin killed for both stocks (Fig. 2). The total calf deficit (D total ) as estimated from the annual kill decreased from highs of approximately 5000 in the mid-1970s down to 2000-3000 by the early 1980s (Fig. 3). In the late 1980s, this value increased to approximately 5000 in northeast- ern spotted dolphins (Table 3A) and approximately 2800 in the western-southern stock (Table 3B), reflecting an increase in the reported kills. In the last five years of the time series (1996-2000), the estimated total deficit was approximately 60 missing calves. The mean deficit per set (Z),) for northeastern spotters over all years was 1.03 missing calves per set, and the me- dian was 0.30 (Fig. 4). For western-southern spotted dol- phins, the mean was 1.28 missing calves per set, and the median was 0.33. The estimated mean deficit per set was approximately 1.5 in the mid-1970s and decreased over time to 0.01-0.02 at the end of the time series (Fig. 4). For both stocks, 75- 95% of lactating females killed were not killed with their calf (Fig. 5). In the sets that were 100% -sampled, for all years com- bined, there was no significant difference between the observed and the estimated number of lactating females killed in either stock (Table 4). The results of paired /-tests 238 Fishery Bulletin 102(2) 0.3- Northeastern 0.2- •:.[•• " "»"..| 1" 0.1 - \\- |t " "" f ^T ll' o.o- 0.3- Western-southern 0.2- 1 1 I " } ll|ttftf ll . i 0.1 - o.o- — 1 1 1 1— 1970 1980 1990 2000 Year Figure 2 Calf deficit per spotted dolphin (Stenella attenuata attenuata) killed (D /; ) by year. Vertical lines indicate 95% confidence intervals. 12000 8000 -- 4000 = 12000 8000 4000 "- +■ Northeastern ••At Western-southern »t Air * -+- -i- 1970 1980 1990 Year 2000 Figure 3 Total estimated calf deficit ^D lotal ) by year. Vertical indicate 95% confidence intervals. by year indicated that the observed number of lactating females in each set was significantly greater (P<0.05) than the estimated number in 1977 for the northeastern and the western-southern stocks and in 1979 for the west- ern-southern stock. The difference was significantly less in 1984 for the western-southern stock. Using 0.1 as our type-2 error level, we determined through power analysis that the minimum detectable difference («=0.05) between the mean observed and estimated number of lactating females per set across all years was approximately 0.08 and 0.09 in the northeastern and western-southern stocks respectively. The observed number of calves per set, defined as the number of dolphins less than 122 cm, was significantly greater for both stocks, for all years combined, than the values estimated in this paper ( Table 5 ). The overall mean difference was 0.17 calves per set for the northeastern stock and 0.12 for the western-southern stock. About half of the years showed a significant difference for each stock. In the comparison of the calf deficit by year, only a few years showed significant differences in either stock (Table 5). However, the estimated deficit tended to be larger than the observed deficit. The paired t-test for all years combined was significant for the northeastern stock, although the mean difference was only -0.06 missing calves per set. The minimum detectable difference from the power analysis for the mean number of calves per set and mean calf deficit per set across all years was 0.06 and 0.08 respectively for both stocks. Discussion In the present study, we present an estimate of the number of missing dependent northeastern and western-southern offshore spotted dolphin calves in the tuna purse-seine kill from 1973 to 1990 and from 1996 to 2000. The total number of missing calves decreased through the time series, which, because we estimated the calf deficit as a function of the size of the kill, was a direct result of the large reduction in the annual dolphin kill by the fishery. Between 1973 and 2000, the shortage of calves in the kill remained at a relatively constant fraction of the kill, about 14 r i , for both stocks of pantropical spotted dolphins (Fig. 2). On the assumption that suckling calves do not survive separation from their mother ( Archer et al., 2001; Archer et al.: Estimates of the incidental kill of Stenella attenuata attenuate calves in the tuna purse-seine fishery 239 3.0 2.5 2.0 1.5 1.0 2° 0.5 CD if) I 0.0 I 3.0 a 1 2.5 c a | 2.0 f 1.5 1.0 0.5" 0.0" -+- Northeastern • ( .tt It • * Western-southern 1 1 ■+- -H -t- 1970 1980 1990 Year 2000 Figure 4 Mean calf deficit per set (D s ) by year. Vertical lines indicate 959? confidence intervals. 1.0" 1 0.9" ,, .1 ",, " ii ii ti ' 0.8" '< " 0.7- Q § 0.6" 5 Northeastern CD ;? 0.5- CD "5. 10- c J? 0.9 - i 1 ' ,, Deficit per o co , ". ti ,, 0.7 1 0.6" Western-southern 0.5- 970 1980 1990 2000 Year Figure 5 Calf deficit per lactating female killed (D,) by year. Vertical lines indicate 95^ confidence intervals. Edwards 3 !, the estimated calf deficit represents an approx- imately 147c underestimate of the reported kill. The calf deficit in the present study was estimated from the number of dependent calves and lactating females killed by using age-color frequency tables and data on the stomach contents of weaning calves. Specimens used to derive the age and color table were collected from 1973 to 1978 and 1981, and specimens used for the weaning model were collected between 1989 and 1991. If the distributions of these samples were not representative of all years that we examined, then our results may be biased. However, the results of a study to construct the annual age distribution of the kill (Archer and Chivers 4 ) indicated that there is no sig- nificant difference in the age-color frequency table across years. The sample size for the stomach data ( 29 calves) was too small to examine differences between years. Our finding of no significant difference between our esti- mates of the number of lactating females and the observed tally of lactating females in sets where the entire kill was sampled validates this portion of our estimation proce- dure. However, because the number of suckling calves present in these 100% -sampled sets was not recorded, we were unable to validate the method used to generate these estimates in a similar manner. The results of our paired Ntests indicated that the ob- served number of animals smaller than 122 cm tended to be greater than the number we estimated. This is most likely a result of the difference between how calves were counted in each method. Archer et al. ( 2001 ) considered all animals under a series of cutoff values to be calves that were dependent on suckling for survival. In the present study, the weaning model that we used (Archer and Rob- 3 Edwards, E. F. 2002. Behavioral contributions to separa- tion and subsequent mortality of dolphin calves chased by tuna purse-seiners in the eastern tropical Pacific Ocean. National Oceanographic and Atmospheric Administration Administra- tive Report LJ-02-28, 34 p. Southwest Fisheries Science Center, 8604 La Jolla Shores Dr., La Jolla, CA 92037. 4 Archer. F.. and S. J. Chivers. 2002. Age structure of the northeastern spotted dolphin incidental kill by year for 1971 to 1990 and 1996 to 2000. National Oceanographic and Atmo- spheric Administration Administrative Report LJ-02-12, 18 p. Southwest Fisheries Science Center, 8604 La Jolla Shores Dr., La Jolla. CA 92037. 240 Fishery Bulletin 102(2) Table 3 Estimated calf deficit per kill (D t ) and total calf deficit Total number of spotted dolphins killed reported by the I ATTC ( 2002 ) and Joseph (footnote 2 in the general text). Values in parentheses are 95% lower and upper confidence intervals. Mean calf Total number Estimated calf deficit of NE spotted Estimated Stock and deficit in Observed per kill dolphins killed total calf year observed sets dolphin kill (D k ) (±SE) deficit A Northeastern (NE) stock 1973 599 5242 0.11 49928 ±8899 5709 (464,964) (3947,6820) (0.10,0.16) (3972,9532) 1974 634 5864 0.11 37410 ±4222 4046 (583,10271 (4943,6916) (0.10,0.16) (3573,6708) 1975 1014 8073 0.13 49399 ±8809 6206 1618,12691 (6578,9965) (0.08,0.14) (3297.8254) 1976 300 2376 0.13 20443 ±4721 2583 (196,408) (1786.3079) (0.09,0.15) (1284.3903) 1977 341 2146 0.16 5937 ±690 943 (249,416) (1743.26221 (0.13,0.18) (656,1167) 1978 148 1016 0.15 4226 ±827 616 (83,209) (684,1431) (0.11,0.16) (336,8361 1979 138 1045 0.13 4828 ±817 640 (96.226) (680,1629) (0.11,0.17) (428,963) 1980 178 1132 0.16 6468 ±962 1016 (107,239) (724.1637) (0.12,0.18) (622,13001 1981 137 815 0.17 8096 ±1508 1366 (84,173) (560,1122) (0.12,0.18) (753,1774) 1982 212 1696 0.12 9254 ±1529 1155 (155,347) (1126,23951 (0.11,0.17) (833,1840i 1983 27 177 0.15 2460 ±659 377 (7,59) (35,410) (0.11,0.23) (169.678) 1984 38 294 0.13 7836 ±1493 1017 (26,57) (191,417) (0.10,0.17) (608,1602) 1985 337 2625 0.13 25975 ±3210 3338 (235,508) (1839.3529) (0.11,0.16) (2447,4748) 1986 290 1816 0.16 52035 ±8134 8297 H19.478) (859.3440) (0.10,0.17) 14496,9935) 1987 497 3327 0.15 35366 ±4272 5280 (397,667) (2777,4002) (0.13.0.18) (3949.71061 1988 182 1142 0.16 26625 ±2744 4234 (122,215) (880,1462) (0.12.0.17) (2825.4907) 1989 165 1096 0.15 28898 ±3108 4357 (120.217) (871,1371) (0.12.0.17) (3186,54921 1990 65 515 0.13 22616 ±2575 2875 (53.90) (421,632) (0.11,0.17) (2176,4085) 1996 88 724 0.12 818 99 (76.142) (568,926) (0.12.0.17) (96.139) 1997 49 393 0.13 721 91 (42,69) (331,461) (0.11,0.17) (81,121) 1998 33 260 0.13 298 38 (26,41) (230,296) (0.10.0.16) (30,46) 1999 36 317 0.11 358 40 (30,48) (282,357) (0.10.0.15) (35,53) 2000 43 291 0.15 295 44 (32.58) (247.342) (0.12,0.18) (35.541 continued Archer et al.: Estimates of the incidental kill of Stenella attenuata attenuate calves in the tuna purse-seine fishery 241 Table 3 (continued) Stock and year Mean calf Total number Estimated calf deficit of NE spotted Estimated deficit in Observed per kill dolphins killed total calf observed sets dolphin kill CD*) (±SE) deficit 141 1199 0.12 51,712 ±10.721 6076 (110,229) (836,1638) (0.10,0.17) (3993-10,633) 254 1715 0.15 35,499 ±10.309 5254 (100,318) (939,2733) (0.07.0.15) (1554,6890) 197 1702 0.12 48,837 ±10,055 5664 (123.322) 11104,2434) (0.09,0.15) (3285,9121) 795 6293 0.13 52,206 ±8883 6595 (524,1036) (4925,7860) (0.09,0.15) (3833,9223) 491 3358 0.15 11.260 ±1186 1647 (345,563) (2860,3906) (0.11.0.16) (1098,1959) 660 3998 0.17 11.610 ±2553 1917 (342,949) (2508,5922) (0.12.0.18) (932.2614) 157 1262 0.12 6.254 ±1229 776 1104.216) (939.1643) (0.09,0.15) (438.1138) 144 1206 0.12 11.200 ±2430 1339 (59.3441 (411.2542) (0.10,0.17) (831,2320) 191 1346 0.14 12.512 ±2629 1775 (90,340) (577.2416) (0.11.0.17) (1010,2682) 306 1966 0.16 9869 ±1146 1536 (198,474) (1337,2734) (0.13,0.19) (1156,2088) 23 148 0.16 4587 ±928 724 (15.33) (99.206) (0.12.0.20) (418,1087) 114 961 0.12 10.018 ±2614 1183 (80.224) (526,1513) (0.12,0.18) (712,2352) 52 381 0.14 8089 ±951 1105 (32,791 (225.5701 (0.11.0.17) (781,1524i 275 1818 0.15 20,074 ±2187 3037 (143,373) (1065.2784) (0.10.0.17) (1776,3617) 271 1768 0.15 19,298 ±2899 2959 (147,374) (1068,2661) (0.11,0.16) (1754,3695) 75 479 0.16 13,916 ±1741 2166 (51,96) (368,605) (0.12,0.18) (1453,2785) 392 2793 0.14 28,560 ±2675 4011 (242,589) (1819,4277) (0.11,0.16) (2861.4977) 123 829 0.15 12,578 ±1015 1864 (78,160) (582.1128) (0.11,0.17) (1283,2236) 53 374 0.14 545 77 (42,711 (308.448) (0.12,0.18) (64,97) 89 738 0.12 1044 126 (72,132) (598.931) (0.11.0.16) (112,165) 31 236 341 44 0.13 (25,42) (192.288) (0.11,0.17) (38,58) 22 159 0.14 253 35 (16.32) (123,209) (0.11,0.18) (28,44) 28 250 0.11 435 48 (22.44) (189,330) (0.10.0.15) (42.67) B Western- 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1996 1997 1998 1999 2000 southern (WS) stock 242 Fishery Bulletin 102(2) Table 4 Annual mean observed and mean estimated are 95% lower and upper confidence intervals ference from zero (P<0.05) in the paired t-test number of lactating females per assuming a normal distribution s. set in 100% sampled sets. Values in parentheses of differences. Bold type indicates significant dif- Year Northeastern stock Western-southern stock No. of sets Observed Estimated Difference (959S CI) No. of sets Observed Estimated Difference (95% CD 1973 116 0.55 0.61 -0.06 1-0.17.0.051 21 1.19 1.30 -0.11 (-0.63,0.421 1974 98 0.51 0.54 -0.03 1-0.13.0.07) 16 0.75 0.81 -0.061-0.36.0.24) 1975 99 0.57 0.48 0.09 (-0.05,0.22) 14 1.07 0.92 0.15 (-0.46.0.77) 1976 51 0.28 0.35 -0.08 1-0.18.0.02) 90 0.500 0.502 -0.002 (-0.119.0.115) 1977 167 0.55 0.46 0.09 (0.01.0.15) 163 0.49 0.37 0.12 (0.03,0.21) 1978 82 0.37 0.40 -0.03 1-0.14,0.08) 93 0.50 0.52 -0.02 (-0.19,0.13) 1979 75 0.47 0.46 0.01 (-0.13,0.14) 61 0.64 0.47 0.17 (0.01,0.33) 1980 54 0.39 0.38 0.01 (-0.11.0.13) 34 0.50 0.44 0.06 1-0.09,0.20) 1981 41 0.53 0.74 -0.21 (-0.81,0.38) 38 0.66 0.64 0.02 1-0.16.0.19) 1982 36 0.62 1.18 -0.56 (-1.40,0.27) 33 0.30 0.44 -0.14 1-0.37,0.10) 1983 33 1.33 2.14 -0.8K-7.89.6.28) 6 0.17 0.57 -0.40 (-1.57,0.77) 1984 4 0.25 0.49 -0.24 1-0.67,0.18) 29 0.48 1.08 -0.60 (-0.96,-0.23) 1985 70 0.34 0.50 -0.16 1-0.36,0.061 17 0.35 0.50 -0.15 1-0.49,0.20) 1986 45 0.71 0.47 0.24 1-0.04,0.51) 28 0.61 0.42 0.19 1-0.01.0.38) 1987 121 0.43 0.46 -0.03 (-0.18,0.11) 30 0.27 0.46 -0.19 1-0.44.0.06) 1988 6 0.44 0.57 -0.13 (-0.59,0.35) — — — — 1989 24 0.96 1.03 -0.07 1-0.59,0.44) 15 0.93 0.96 -0.03 (-0.68,0.64) 1990 16 0.56 0.47 0.09 1-0.25,0.44) 9 0.67 0.93 -0.26 1-0.94,0.42) All 1108 0.50 0.53 -0.03 1-0.08,0.02) 697 0.545 0.546 -0.001 (-0.053,0.051) ertson, in press) estimated the probability that a calf of a given age class was still suckling. Given that body length has a near linear relationship with age in these young age classes (Perrin, 1976), this meant that for any chosen length of independence, each individual smaller than that cutoff value would only be counted fractionally, in effect correcting for the probability that an animal of a given age is not suckling. This procedure caused the method in this paper to tally fewer "calves" in each set than in the previous study. A secondary result of this effect was that the mean deficit per set estimated in the present study tended to be slightly higher than that presented by Archer etal. in 2001. We estimated the total number of missing calves as a function of the number of dolphins killed in each stock (Table 3). Prior to 1995, only a fraction of the purse-seine trips carried scientific observers. To estimate the number killed in each stock, kill rates from the observed trips were applied to unobserved trips, stratified by area and stock (IATTC, 2002; Joseph, 1994 2 ). Since 1995 it has been re- ported that all dolphin sets have been observed, and that the number of dolphins killed is therefore known without error (IATTC, 2002). The total calf deficit could also be estimated as a function of the number of sets by multiplying the total number of sets made on each stock by D s (Fig. 4). In the only study to estimate the number of sets made on each stock annually. Archer et al. 5 used a relatively simple proration scheme of unobserved sets derived from ratios of the number of sets made on each stock in observed sets. However, because Archer et al. 5 did not stratify unobserved sets by area, bas- ing the total calf deficit on these estimates would produce a different result from that presented in Table 3. Because the estimates of the kill by stock included stratification by area, estimates of the total calf deficit calculated by multiplying the kill estimates by D,. are likely to be more accurate. It is important to realize that the deficit that we present is directly related to the kill observed in the sets that we used. In other words, if proration schemes for un- observed sets were the same for the number of sets made and the number of dolphins killed, estimates of the total calf deficit with either D^ or D k would be equivalent. Wade et al. 1 explored the effects of 50% and 100' < ad- ditional fisheries-related mortality on the assessment of the northeastern spotted dolphin stock. The assumption of additional mortality led to higher estimates of maximum Archer. F.. T. Gerrodette. and A. Jackson. 2002. Prelim- inary estimates of the annual number of sets, number of dolphins chased, and number of dolphins captured by stock in the tuna purse-seine fishery in the eastern tropical Pacific. 1971-2000. National Oceanographic and Atmospheric Admin- istration Administrative Report LJ-02-10. 26 p. Southwest Fisheries Science Center, 8604 La Jolla Shores Dr., La Jolla, CA 92037. Archer et al.: Estimates of the incidental kill of Stenella attenuata attenuata calves in the tuna purse-seine fishery 243 Table 5 Annua 1 mean number of dolphins killed sl22 cm (calves killed based on length) and estimated number of suckling calves (calves based 3n weaning model 1 per set in 100 r t sampled sets (first line for each year!. Mean deficit per set using .22 cm as cutoff length (calf deficit based on length ) and calf deficit as estimated in this article (calf deficit based on weaning model) on second line for each year. Values in parentheses are 959! lower and upper confidence intervals assuming a normal dist •ibution of differences. Differences in bold indicate significant difference from zero (PsO.05) in the paired Mest. Northeastern stock Western-southern stock Calves killed Calves killed Calves killed Calves killed based on based on based on based on length weaning model length weaning model No. Calf deficit Calf deficit No. Calf deficit Calf deficit of based on based on Difference of based on based on Difference Year sets length weaning model (95% CD sets length weaning model (95% CD 1973 116 0.54 0.21 0.33 (0.18,0.50) 21 0.33 0.06 0.27 (0.01,0.55) 0.35 0.48 -0.13 (-0.26,-0.03) 1.00 1.25 -0.25 1-0.79.0.29) 1974 98 0.39 0.05 0.34 (0.20,0.47) 16 0.56 0.09 0.47 1-0.53.1.47) 0.36 0.50 -0.14 (-0.26,-0.03) 0.56 0.74 -0.181-0.61,0.25) 1975 99 0.57 0.15 0.42 (0.20,0.64) 14 0.29 0.11 0.18(-0.03.0.39) 0.46 0.40 0.04 1-0.05.0.161 0.93 0.83 0.10(-0.45,0.66i 1976 51 0.18 0.11 0.07 1-0.01,0.15) 90 0.13 0.07 0.06 (0.001,0.13) 0.28 0.31 -0.031-0.14.0.06) 0.49 0.47 0.02 1-0.10.0.15) 1977 167 0.10 0.03 0.07 (0.02,0.12) 163 0.17 0.06 0.11 (0.06,0.16) 0.51 0.45 0.06 (-0.01,0.14) 0.46 0.35 0.11(0.03,0.20) 1978 82 0.17 0.03 0.14(0.05,0.23) 93 0.18 0.05 0.13 (0.04,0.23) 0.35 0.39 -0.04 (-0.14.0.07) 0.43 0.50 -0.07 1-0.22.0.09) 1979 75 0.09 0.04 0.05 (-0.02,0.13) 61 0.31 0.13 0.18(0.04,0.32) 0.44 0.43 0.01 (-0.11,0.13) 0.51 0.37 0.14 1-0.03,0.31) 1980 54 0.16 0.03 0.13 (0.02,0.25) 34 0.00 0.01 -0.01 (-0.02,-0.003) 0.373 0.371 0.002-0.115,0.119) 0.50 0.44 0.061-0.08.0.21) 1981 41 0.105 0.110 -0.005 1-0.194,0.185) 38 0.05 0.04 0.01 (-0.04.0.07) 0.53 0.65 -0.121-0.57,0.31) 0.63 0.62 0.01 (-0.17,0.20) 1982 36 0.44 0.21 0.23 (-0.10.0.55) 33 0.06 0.02 0.04 1-0.04,0.12) 0.44 1.00 -0.56(-1.27,0.14i 0.27 0.42 -0.15 (-0.37,0.08) 1983 33 0.00 0.14 0.14 1-0.64.0.36) 6 0.17 0.04 0.13 1-0.31.0.57) 1.33 2.00 -0.67 (-7.25.5.91) 0.17 0.56 -0.39 1-1.56,0.76) 1984 4 0.00 0.02 -0.02 1-0.08,0.04) 29 0.14 0.04 0.10 1-0.01,0.21) 0.25 0.49 -0.24 1-0.67,0.18) 0.35 1.04 -0.69 (-1.13,-0.26) 1985 70 0.13 0.04 0.09(0.02,0.15) 17 0.06 0.04 0.02 1-0.06.0.10) 0.29 0.47 -0.181-0.39,0.03) 0.35 0.49 -0.14 (-0.48,0.21) 1986 45 0.13 0.04 0.09 (0.01,0.17) 28 0.04 0.03 0.01 (-0.04,0.06) 0.64 0.44 0.20 1-0.04.0.44) 0.57 0.39 0.181-0.02,0.38) 1987 121 0.14 0.02 0.12 (0.05,0.20) 30 0.23 0.08 0.15(0.02,0.30) 0.38 0.45 -0.07 1-0.22,0.07) 0.27 0.43 -0.16 (-0.41,0.09) 1988 6 0.11 0.33 0.12 0.50 -0.01 (-0.23.0.22) -0.17 1-0.62,0.28) — — — — 1989 24 0.22 0.13 0.09 (-0.11,0.29) 15 0.47 0.20 0.27 (0.05,0.49) 0.87 0.95 -0.08 (-0.60,0.43) 0.73 0.82 -0.09 1-0.66,0.48) 1990 16 0.31 0.21 0.10 (-0.18,0.38) 9 0.89 0.17 0.72 1-0.18,1.62) 0.56 0.41 0.15 (-0.20.0.51) 0.33 0.77 -0.44 (-1.15,0.27) All 1108 0.25 0.08 0.17 (0.13,0.20) 697 0.18 0.06 0.12 (0.09,0.16) 0.42 0.48 -0.06 (-0.10,-0.01) 0.49 0.51 -0.02 (-0.08,0.03) 244 Fishery Bulletin 102(2) growth rates and lower estimates of the current size of the population in relation to carrying capacity. Wade et al. 1 did not model the calf deficit estimated in our present study, but the effect of 14/r additional mortality would probably be less than the 50 f > additional mortality that was modeled. The 50^ mortality was spread over all age classes, and additional mortality due to missing calves should be assigned to the first two year classes only. The important question is whether the calf deficit in the kill represents the main effect of mother-calf separation by the fishing process. As outlined in Archer et al. (2001t, the mechanism by which suckling calves are separated from their mothers is unknown. If separation is simply a function of the number of lactating females killed, then the deficit presented here is an accurate representation of the number of "missing" calves. However, there is some evidence that separation can occur without the mother being killed. In the early days of the backdown procedure, purse-seine skippers reported that "Babies swim around the outside of the net pushing to get back in probably because their mothers are still inside" i Gehres p (. It is unclear whether these calves were sepa- rated prior to encirclement or were released early during backdown, prior to their mothers. Regardless, given that dolphins exhibit some of their fastest swimming during a set immediately upon release from the net tChivers and Scott' ), separated calves waiting immediately outside the net may risk separation if their mothers join the rest of the school rapidly swimming away from the net. If this, or any of the other scenarios regarding the manner in which perma- nent separation can occur without the mother being killed i Archer et al.. 2001 1. then the calf deficit underestimates the actual number of orphaned calves. Future research should focus on the mechanism of calf separation because a better understanding of this process is the only way we will be able to estimate the magnitude of the unobserved calf mortality and its subsequent effects on the population. Acknowledgments The authors wish to thank Michael Scott and Xick Vogel of the IATTC for providing data as well as Jay Bar- B Gehres. L. E. 1971. Letter of July 2 to Alan R. Longhurst. 2 p. Southwest Fisheries Science Center, 8604 La Jolla Shores Dr.. La Jolla. CA 92037. 7 Olivers. S. J., and M. D. Scott. 2002. Tagging and tracking of Stenella spp. during the 2001 Chase Encirclement S Studies cruise. National Oceanographic and Atmospheric Administration Administrative Report LJ-02-33. 21 p. South- west Fisheries Science Center, 8604 La Jolla Shores Dr.. La Jolla. CA 92037. low and Bill Perrin for helpful reviews and analytical suggestions. Literature cited Archer. F.. T. Gerrodette, A. Dizon. K. Abella and S. Southern. 2001. Unobserved kill of nursing dolphin calves in a tuna purse-seine fishery Mar Mamm. Sci. 17:540-554. Archer. F.. and K. M. Robertson. In press. Age and length at weaning and development of prey preferences of pantropical spotted dolphins. Stenella attenuata, from the eastern tropical Pacific Mar Mamm. Sci. Dizon. A. E.. W. F. Perrin. and P. A. Akin. 1994. Stocks of dolphins iStenella spp. and Delphmux delphis) in the eastern tropical Pacific: a phylogeographic classification. NOAA Tech. Rep. NMFS-119. 20 p. Gerrodette. T. 2002. Tuna-dolphin issue. In Encyclopedia of marine mammals (W. F. Perrin. B. Wursig. and J. G. M. Thewis- sen, eds.l. p. 1269-1273. Academic Press. San Diego. CA. Hall. M. A., L. A. Dayton, and K. I. Metuzals. 2000. Bycatch: problems and solutions. Mar. Poll. Bull. 41:204-19. IATTC i Inter-American Tropical Tuna Commission). 2002. Annual report of the Inter-American Tropical Tuna Commission 2000, 171 p. IATTC. La Jolla. CA. Gosliner, M. L. 1999. The tuna-dolphin controversy. In Conservation and management of marine mammals (J. R. Twiss Jr.. and R. R. Reeves, eds.l, p. 120-155. Smithsonian Institution Press. Washington and London. Myrick. Jr.. A. C, A. A. Hohn. J.. Barlow, and P. A. Sloan. 1986. Reproductive biology of female spotted dolphins. Stenella attenuata, from the eastern tropical Pacific. Fish. Bull. 84:247-259. NRC t National Research Council I. 1992. Dolphins and the tuna industry. 176 p. National Academy Press. Washington. D.C. Perrin. W. F. 1970. Color patterns of the eastern Pacific spotted por- poise Stenella graffmani LbnnbeglCetacea, DelphinidaeL Zoologica NY) 54:135-149. Perrin. W, F.. J. M. Coe, and J. R. Zweifel. 1976. Growth and reproduction of the spotted porpoise. Stenella attenuata, in the offshore eastern tropical Pa- cific. Fish. Bull. 74:229-269. Smith, T. 1983. Changes in size of three dolphin [Stenella spp. 1 populations in the eastern tropical Pacific. Fish. Bull. 81:1-13. Wade, P. R. 1995. Revised estimates of incidental kill of dolphins I Del- phinidae 1 by the purse-seine tuna fishery in the eastern tropical Pacific. 1959-1972. Fish. Bull. 93:345-354. 245 Abstract— Psednos rossi new species (Teleostei: Liparidaei is described from two specimens collected in the North Atlantic Ocean off Cape Hatteras, North Carolina, at depths of 500- 674 m. Psednos rossi belongs to the P. christinae group, which includes six other species and is characterized by 46-47 vertebrae and the absence of a coronal pore. Psednos rossi dif- fers from those six species by having characters unique within the genus: straight spine, body not humpbacked at the occiput, and a very large mouth with a vertical oral cleft. Other distin- guishing characters include a notched pectoral fin with 15-16 rays, eye 17-19% SL, and color in life orange- rose. With P. rossi, the genus Psednos as currently known includes 26 de- scribed and five undescribed species of small meso- or bathypelagic liparids from the Atlantic. Pacific, and Indian Oceans. A remarkable new species of Psednos (Teleostei: Liparidae) from the western North Atlantic Ocean Natalia V. Chernova Zoological Institute Russian Academy of Sciences Unlversitetskaya nab- 1 St. Petersburg 199034. Russia David L. Stein NOAA/NMFS Systematlcs Laboratory Smithsonian Institution P.O. Box 37012 National Museum of Natural History, MRC-0153 Washington, DC. 20013-7012 E-mail address (for D L. Stem, contact author): david.stenvanoaa gov Manuscript approved for publication 7 January 2004 by Scientific Editor. Manuscript received 20 January 2004 at NMFS Scientific Publications Office. Fish. Bull. 102:245-250 (2004). The liparid genus Psednos Barnard 1927 is a group of meso- and bathype- lagic snailfishes distinguished from the genus Paraliparis by having the infra- orbital canal of the cephalosensory system interrupted behind the eye and usually having a pronounced dorsal curvature of the spine, producing a "humpbacked" body. Psednos are small, easily damaged, and often misidenti- fied as juvenile Paraliparis. Until 1978, the genus was known only from two specimens of a single species (Psednos micrurus Barnard 1927) collected off Cape Point, South Africa. Two addi- tional specimens were collected in the southern Indian Ocean and reported by Stein (1978). No further specimens or species were described until Andria- shev (1992) described another new species. Since then, active searches for material from collections around the world have yielded many specimens from the Atlantic. Pacific, and Indian Oceans. To date, 25 species have been described (Andriashev, 1992, 199.3; Chernova. 2001; Stein et al.. 2001; Chernova and Stein, 2002) and an additional five are undescribed (one in Stein et al., 2001, three in Chernova and Stein, 2002, all in poor condition; and another that is currently being described by Stein). In this article, we describe an especially noteworthy spe- cies of the genus from two specimens collected from the North Atlantic off Cape Hatteras, North Carolina. Materials and methods All characters available for both speci- mens were studied. Characters and terms used were described by Andria- shev (1992), Chernova (2001), Stein et al. (2001), and Chernova and Stein (2002 1. Counts were made from a radio- graph of the holotype and from each specimen where possible; vertebral counts include the urostyle. The first caudal vertebra is that with the haemal spine supporting the first anal-fin ray. The posterior tip of the lower jaw in Psednos forms a distinct and promi- nent ventrally directed angle, the ret- roarticular process (Chernova, 2001). Counts and proportions are given as a percentage of standard length ( SL) and head length (HL). Nonstandard mea- surements are the following: distance from mandible to anus (from ante- rior tip of mandible to center of anus); distance from anus to anal-fin origin (from center of anus to anal-fin origin); interorbital width (measured between upper margins of eyes); postocular head length (distance from posterior margin of eye to tip of opercular flap). 246 Fishery Bulletin 102(2) Figure 1 Psednos rossi n.sp., paratype, USNM 372727. Adult, 51.8 mm SL, 57.2 mm TL. Sta. CH-01-047, off Cape Hatteras. Scale 5 mm. Infraorbital pore 6 not shown owing to damage. We selected the smaller specimen to serve as the holo- type owing to its better condition (skin, pores, shape of head) and the availability of more characters. Unfortu- nately, it is distorted and does not look natural; therefore the undistorted larger (adult) specimen, the paratype, is illustrated. It is also more useful to have a drawing of an adult for comparison with other Psednos specimens. In these small fishes, precise counts of number of tooth rows are possible only in disarticulated cleared and stained specimens; thus, we provide approximate counts. Similarly, the drawing of the gill arch of the paratype was made without dissection by viewing through an opening in the branchiostegal membrane. Although Andriashev (1986) and Andriashev and Stein (1998) demonstrated the importance of the pectoral girdle in distinguishing among species and in explain- ing liparid relationships, we did not dissect, clear, and stain a pectoral girdle from these specimens owing to the high probability of damaging them and destroying other characters (Chernova, 2001; Chernova and Stein, 2002). The new species is so easily distinguished from congeners that it is not necessary for a diagnosis of the species to look at additional characters that the pectoral girdle can provide. Future specimens should be used to study these characters. The holotype and paratype are permanently deposited in the Division of Fishes, Smithsonian Institution, Na- tional Museum of Natural History (USNM collection). Results Psednos rossi, n.sp. Holotype USNM 372726, juvenile, 37.2 mm SL. TL?, Sta. EL-00-033, off Cape Hatteras (The Point), 35°30.036'N, 74°46.497'W, 500-674 m over about 900 m depth, 23 July 2000, Tucker trawl. Good condition but distorted. Paratype USNM 372727, adult (sex not identified), 51.8 mm SL, 57.2 mm TL, Sta. CH-01-047, off Cape Hatteras (The Point), 35°28.93'N, 74°45.93'W, 628-658 m over 1090-704 m depth, 24 Aug. 2001, Tucker trawl. Throat slightly damaged, head slightly compressed, skin on head partly missing. Diagnosis Vertebrae 47, dorsal-fin rays 42-44, coronal pore absent. Mouth vertical, symphysis of upper jaw above level of eye. Body not humpbacked, vertebral column not curved behind cranium. Gill cavity enlarged. Anus on vertical behind head. Pectoral fin notched, rays 8+2+5-6. Eye 17-19% HL. Description Counts and proportions are given in Table 1. Head large, about one-third SL, its depth less than, and its width equal to or a little greater than, its length (Fig. 1). Head depth slightly greater than its width. Mouth very large, distinctly superior. Jaws almost vertical, at angle of about 90° to horizontal. Symphysis of upper jaw above level of eye. Ascending process of premaxilla horizontal, its distal end almost above center of eye. Posterior tip of lower jaw- exactly below symphysis of upper jaw. Posterior (lower) end of mouth cleft well below level of lower margin of eye. When mouth closed, ventral surface of lower jaw forms entire frontal surface of head. Lower jaw included. Sym- physeal process present at lower jaw symphysis, projecting forward prominently; retroarticular processes of lower jaw large, acute, directed anteroventrally (Fig. 2 A I. Teeth large, sharp, spear-shaped, strongly curved inward (Fig. 2B), in (smaller) holotype in approximately 22 and 24 (32 and 35) rows on upper and lower jaw; 5 (8-9) teeth in first full row near symphyses of both jaws. Snout short, 1.5 ( 1.0) times eye diameter. Olfactory rosette (7 lobes) and nostril above anterior third of eye. Eyes not large, close to upper Chernova and Stein: A new species of Psednos from the western North Atlantic Ocean 247 Table 1 Counts and proportions for the holotype and paratype of Psednos rossi new species. Proportions are in % of standard length (SL) followed by % head length (HL, in parentheses). Vertebrae Dorsal-fin rays Anal-fin rays Pectoral-fin rays Caudal-fin rays Gill rakers Head length Head width Head depth Body depth Body depth at anal-fin origin Predorsal-fin length Preanal-fin length Mandible to anus Anus to anal fin origin Upper pectoral-fin lobe length Pectoral-fin notch ray length Lower pectoral-fin lobe length Eye diameter Snout length Interorbital width Postocular head length Upper jaw length Lower jaw length Gill opening length Opercle length USNM 372726 Holotype 37.2 mm SL 47 44 35 16 [L] 15 [R] 6 32.3 22.0(68.1) 23.7(73.4) 21.5(66.6) 13.4(41.5) 29.6(91.6) 47.8(148.0) 34.9(108.0) 23.7(73.4) 13.4(41.5) 8.1(25.1) 9.4(29.1) 5.4(16.7) 8.1(25.0) 13.4(42.0) 18.8(58.0) 16.1(49.8) 16.1(49.8) 5.4(16.7) 13.4(41.5) USNM 372727 Paratype 51.8 mm SL 42 33 15 [L, R] 6 10 29.9 13.5(45.2) 17.4(58.2) 25.1(83.9) 17.0(56.8) 26.6(89.0) 48.3(161.5) 36.7(122.7) 21.2(70.9) 13.5(45.2) 5.8(19.4) 7.7(25.8) 11.2(37.4) 19.3(64.5) 12.5(41.8) 13.5(45.2) 5.4(18.1) 12.5(41.8) contour of head. Interorbital space flat, 2.5 (1.9) times eye diameter. Gill opening short, 1.0 (0.9) times eye diameter, at 45° angle, entirely above pectoral-fin base and slightly anterior to it (distance between ventral end of gill opening and base of upper pectoral ray about equal to length of gill opening). Opercular flap small, acute. Opercle very long, directed ventrally and posteriorly, its tip below level of pos- terior end of lower jaw. Interopercle of similar length, vis- ible externally, its anterior tip projecting anteriorly from ventral contour of head (Fig. 1). Long opercle, interopercle and elongated branchiostegal rays support membranes of enlarged branchial cavity that appears externally as a black posterior part of head. Branchial cavity length slightly more than half head length. Branchiostegal rays (4+2) long and distinctly visible externally. Gill rakers modified, closely but irregularly set, mostly alternating (especially on gill arch one), often paired on the outer and inner sides of each gill arch (central part of arches two and three); plates flattened, triangular, similar in shape to those in P. pallidus or Psednos sp.l of Chernova and Stein (2002, Figs. 9 and 13). spinule-bearing surface directed internally, flat and longitudinally oval. Spinules closely set, usually in two longitudinal rows, each of five to eight spinules, often with a few additional spinules in between (Fig. 2C). Sensory pores difficult to see because of thin transpar- ent skin (damaged in paratype). Nasal pores 2, the poste- rior on a vertical through center of eye. Paired nasal bones (through which the nasal canals run) long, tubular, and visible externally. Coronal pore absent. Lacrimal bones (bearing anterior portion of infraorbital canal) large, vis- ible externally, slightly prominent anteriorly. Infraorbital canal (better preserved in holotype) interrupted behind eye, infraorbital pores 6 (5+1), posteriormost above poste- rior margin of eye (Fig. 2A). In paratype, skin behind eye missing. Preoperculomandibular pores 6 (3 on lower jaw + 3 on preopercular area). Two temporal pores present: t x a short distance behind posterior margin of eye, and t sb , the suprabranchial pore, above and in front of gill opening (Fig. 2A). 248 Fishery Bulletin 102(2) Pectoral fin notched, of 16 (15) rays. Upper lobe of 8 (8) rays, the 2 (2) notch rays more widely spaced and placed exactly at middle of fin base. In holotype, left lower pec- toral lobe with 6, on right 5, rays. In paratype, 5 rays on each side. Bases of lower-lobe rays stronger and thicker than those of upper-lobe rays. Level of uppermost pectoral ray below horizontal through lower end of upper jaw. Base of pectoral fin close to vertical, lowest ray almost directly below uppermost. Upper-lobe rays not reaching anal fin origin, lower-lobe rays not reaching vertical through ends of upper lobe rays. In holotype, length of notch rays 1.7 times in upper pectoral-fin lobe length, lower pectoral-fin lobe 1.4 times in it. Body not humpbacked, dorsal contour of back almost straight; spine horizontal, its anterior end not dorsally "'Vt B Figure 2 Details of anatomy of Psednos rossi. (A) Cephalic pores and prominent features of head. Portions of sensory canals passing through bones are stippled. N = nostril and olfac- tory rosette; io = infraorbital pores, n = nasal pores, t = temporal pores; S = symphyseal knob; R = retroarticular process. (B) Teeth of paratype: (leftl frontal view; (right) lateral view. Tooth length about 0.25 mm. (C) First gill arch of paratype, USNM 372727. right side; view from inside of gill cavity. Raker height about 0.3 mm. curved (Fig. 3). Neural spines of vertebrae 1-4 neither longer nor broader than those posterior, unlike other spe- cies (see Fig. 5 in Chernova, 2001). Maximum body depth 4.2 (4.0) times in standard length and 1.6(1.5) times depth at anal-fin origin. In holotype, occiput slightly swollen (Fig. 3); in paratype, dorsal outline of head and back in front of dorsal fin origin almost perfectly flat (Fig. 1), pos- sibly an age-related difference. Abdominal part of body long, preanal length almost half of standard length. Inter- neural of first dorsal-fin ray between neural spines 3 and 4. Dorsal and anal fins moderately deep, maximum depth of erect dorsal fin in paratype 8.9 times in SL, 2.7 times in head length (damaged in holotype). Dorsal and anal fins overlapping about one-third of caudal-fin length. Anus on vertical behind head, slightly behind base of uppermost pectoral ray. Skin transparent. Gelatinous subcutaneous tissue weakly developed. In holotype (smaller specimen) body not as deep and jaws longer than in the paratype (larger specimen). Differences in head width and interor- bital width are great because head of paratype was slightly compressed during fixation. Other proportions similar to those of holotype. Body color in alcohol pale; under magnification, slightly dusky blotches of dots present caudally in paratype and absent in holotype. Head musculature pale. Black perito- neum visible through body wall. Mouth and gill cavities, gill arches, tongue, and both jaws black; gill rakers pale. Musculature of pectoral girdle appears pale on lateral surface of belly. Color in life orange-rose. Distribution Western North Atlantic off Cape Hatteras, mesopelagic at depths of 500-674 m. Etymology The patronym "rossi" after Steve W. Ross, who initially notified us of the captures and furnished the specimens to us for examination. Comparative notes Psednos rossi seems to belong to the P. christinae group (see Chernova, 2001; Chernova and Stein, 2002), includ- ing P. andriashevi, P. barnardi, P. christinae. P. dentatus, P. groenlandicus, and P. harteli. Species of this group are characterized by vertebrae 46-47, dorsal-fin rays 38-42, anal-fin rays 33-35, and coronal pore absent (versus the P. micrurus group having vertebrae 40-44. dorsal-fin rays 34-38, anal-fin rays 28-33, and coronal pore present) (Chernova, 2001). Psednos rossi distinctly differs from the other species of the christinae group in at least having occiput not swollen (vs. greatly swollen), not humpbacked because the vertebral column is straight (vs. humpbacked owing to the greatly curved anterior part of the spine), mouth vertical with jaws at 90° to horizontal, symphysis of upper jaw above level of eye (vs. a more or less oblique mouth at an angle of 30-45° and the upper jaw. symphysis on a horizontal with the lower half of the eve); and anus Chernova and Stem: A new species of Psednos from the western North Atlantic Ocean 249 Figure 3 Radiograph of Psednos rossi n.sp., holotype. USNM 372726. Juvenile, 37.2 mm SL. Sta. EL-00-033, off Cape Hatteras. behind the head (vs. anus below the posterior third of the head). The very oblique, almost vertical mouth occurs often in species of the P. micrurus group, five of which have the mouth at 75-85° to the horizontal (P. anoderkes, P. cathetostomus, P. microps, P. mirabilis, P. sargassicus). However, they all differ as described above. Discussion The physical features of Psednos rossi are unique in the genus. The straight vertebral column and body are outside the previous diagnosis of the genus, because all previously known species are humpbacked owing to the curved spinal column. Nevertheless, P. rossi clearly belongs in Psednos rather than Paraliparis because it has the other generic characters of Psednos (Chernova, 2001); particularly, its sensory canal system and pores are of Psednos type, having an interrupted infraorbital canal behind the eye. We suggest that its remarkable body shape is an extreme transformation of the usual Psednos body shape and is associated with the change of the mouth from oblique and of normal size to vertical and very large. In this process the anterior movement of the bony elements of the jaws greatly enlarges the branchial cavity. The morphology of Psednos rossi invites speculation about its ecology. The very large superior mouth with verti- cal jaws, eyes located close to the dorsal contour of the head and oriented to look forward and up, and straight body sug- gest adaptation to feeding on detritus and animals (such as copepods) above it in the water column. These adaptations, similar to those of hatchetfishes (family Sternoptychidae), are highly advantageous for a mesopelagic mode of life. Sudden opening of the very large vertical lower jaw could produce a strong orobranchial suction, simultaneously bringing food into the mouth and thus saving energy for this fish, which is probably a poor swimmer. Work over the last several years has made it clear that Psednos species exist at mesopelagic depths in the North Atlantic, Indian, North Pacific, and South Pacific Oceans. We confidently expect discovery of additional species from meso- and bathypelagic waters. Acknowledgments We wish to thank S. W. Ross, K. J. Sulak, and J. V. Gartner Jr. for collecting the specimens, bringing them to our attention, and loaning them to us for description. Collections were supported by the U.S. Geological Survey, State of North Carolina, North Carolina Coastal Reserve Program, and the Duke/UNCW Oceanographic Consor- tium. The figures are drawn by the senior author, who was supported by the Russian Science Foundation Grants 02-04-48669 and 00-15-07794. Literature cited Andriashev, A. P. 1986. Review of the snailfish genus Paraliparis (Scorpaeni- formes: Liparididae) of the Southern Ocean, 204 p. The- ses Zoologicae 7, Koeltz Scientific Books, Koenigstein 1992. Morphological evidence for the validity of the anti- tropical genus Psednos Barnard ( Scorpaeniformes, Lipari- didae) with a description of a new species from the eastern North Atlantic. UO, Tokyo 41:1-18. 1993. The validity of the genus Psednos Barnard (Scor- paeniformes, Liparidae) and its antitropical distribution area. Vopr. Ikhtiol. 33(11:5-15 [in Russian] J. Ichthyol. 33 (5):81-98. [English translation.] Andriashev, A. P., and D. L. Stein. 1998. Review of the snailfish genus Careproctus (Lipari- dae, Scorpaeniformes) in Antarctic and adjacent waters. Contr. Sci. Nat. Hist Mus. Los Angeles Cty. 470:1-63. 250 Fishery Bulletin 102(2) Chernova. N. V. 2001. A review of the genus Psednos (Pisces, Liparidae) with description often new species from the North Atlantic and southwestern Indian Ocean. Bull. Mus. Comp. Zool. 155:477-507. Chernova, N. V., and D. L. Stein. 2002. Ten new species of Psednos (Pisces, Scorpaeni- formes: Liparidae) from the Pacific and North Atlantic Oceans. Copeia 2002 (3):755-778. Stein, D. L. 1978. The genus Psednos a junior synonym of Paraliparis, with a redescription of Paraliparis mierurus (Barnardi (Scorpaeniformes: Liparidae). Matsya 4:5-10. Stein, D. L., N. V. Chernova, and A. P. Andriashev. 2001. Snailfishes (Pisces: Liparidae) of Australia, includ- ing descriptions of 30 new species. Rec. Austr. Mus. 53:341-406. 251 Abstract— Age and growth of sailfish (Jstiophorus platypterus) in waters off eastern Taiwan were examined from counts of growth rings on cross sections of the fourth spine of the first dorsal fin. Length and weight data and the dorsal fin spines were collected monthly at the fishing port of Shinkang (southeast of Taiwanl from July 1998 to August 1999. In total. 1166 dorsal fins were collected, of which 1135 (97 r £> (699 males and 436 females) were aged suc- cessfully. Trends in the monthly mean marginal increment ratio indicated that growth rings are formed once a year. Two methods were used to back- calculate the length of presumed ages, and growth was described by using the standard von Bertalanffy growth function and the Richards function. The most reasonable and conserva- tive description of growth assumes that length-at-age follows the Rich- ards function and that the relationship between spine radius and lower jaw fork length ( LJFL I follows a power function. Growth differed significantly between the sexes; females grew faster and reached larger sizes than did males. The maximum sizes in our sample were 232 cm LJFL for female and 221 cm LJFL for male. Age and growth of sailfish Ustiophorus platypterus) in waters off eastern Taiwan Wei-Chuan Chiang Chi-Lu Sun Su-Zan Yeh Institute of Oceanography National Taiwan University No 1, Sec. 4, Roosevelt Road Taipei, Taiwan 106 E-mail address (for C L. Sun, contact author): chilufiintu edu.tw Wei-Cheng Su Taiwan Fisheries Research Institute No. 199, Ho-lh Road Keelung, Taiwan 202 Manuscript approved for publication 22 December 2003 by Scientific Editor. Manuscript received 20 January 2004 at NMFS Scientific Publications Office. Fish. Bull. 102(2): 251-263 (2004). The sailfish (Istiophorus platypterus) is distributed widely in the tropical and temperate waters of the world's oceans. According to data from longline catches, sailfish are usually distributed between 30°S and 50°N in the Pacific Ocean, and h