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The effects of physical and biological oceanographic factors on marine growth of Fraser river sockeye… Cox, Sean Patrick 1996

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THE EFFECTS OF PHYSICAL AND BIOLOGICAL OCEANOGRAPHJC FACTORS ON MARINE GROWTH OF FRASER RIVER SOCKEYE SALMON by , SEAN PATRICK COX B. Sc. The University of Massachusetts, 1993 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE in THE FACULTY OF GRADUATE STUDIES (Department of Earth and Ocean Sciences) We accept this thesis as conforming to the required standard THE UNIVERSITY OF BRITISH COLUMBIA December 1996 © Sean Patrick Cox, 1996 In presenting this thesis in partial fulfilment of the requirements for an advanced degree at the University of British Columbia, I agree that the Library shall make it freely available for reference and study. I further agree that, permission for extensive copying of this thesis for scholarly purposes may be granted by the head of my department or by his or her representatives. It is understood that copying or publication of this thesis for financial gain shall not be allowed without my written permission. Department of <=o«ft^ OOl^ S<<WC&< The University of British Columbia ; Vancouver, Canada DE-6 (2/88) Thesis Abstract The average size at maturity of sockeye salmon {Oncorhynchus nerka) in the northeast Pacific Ocean varies considerably from year to year: It is generally accepted that the majority of variation in size at maturity of sockeye salmon is due to variation in marine growth. However, few studies have shown strong linkages between specific oceanographic factors such as temperature, ocean currents, zooplankton production, and salmon abundance and the ultimate size of returning Fraser River sockeye. Using size at maturity data specific for ten Fraser River sockeye stocks I demonstrate that i.) the amount of variation in size at maturity that is due to environment is detectable in spawning ground length samples and ii.) mean size at maturity declined in almost every stock over the period 1954-1993.1 also show that variation in marine growth is strongly associated with changes in sockeye salmon abundance and sea surface temperature in the northeast Pacific Ocean. Marine growth was not correlated to sockeye salmon abundance over the period 1959-1975; however the two were strongly associated during the period 1978-1992. Annual scale growth increments support the assumption that critical periods for density dependent growth occur during the time when Early Stuart sockeye salmon are present in the Central Gulf of Alaska. If present levels of salmon abundance are maintained during future warmer climates, major declines in size at maturity of.sockeye salmon are likely to result due to the combined effects of high temperature, high abundance, and possibly a reduction in the standing crop of prey. ii Table of Contents Thesis Abstract " Table of Contents •» List of Tables v List of Figures vii List of Appendices ix Acknowledgements x INTRODUCTION 1 Chapter 1 Changes in size at maturity of Fraser River sockeye salmon (1952-1993) and associations with temperature 3 Chapter Abstract 3 Introduction 4 Methods : 6 Size at Maturity and SST Data 6 Statistical Analyses.. 9 Results and Discussion 10 Time Trends 10 Size at Maturity and SST Relationships 16 References 19 Chapter 2 Effects of abundance and thermal habitat on marine growth of Fraser River sockeye salmon 26 Chapter Abstract 26 Introduction 27 Methods 30 Gulf of Alaska Sockeye Abundance 30 Sockeye Density Index 33 iii Marine growth data 34 Statistical Analysis 34 Results and Discussion 36 Changes in density-dependent growth relationships 45 Conclusions 52 References 53 Chapter 3 Density-dependent marine growth of Early Stuart sockeye salmon: evidence for a critical period 59 Chapter Abstract 59 Introduction 60 Methods 61 Marine Growth Data 61 Sockeye Abundance 62 Statistical Analysis 62 Results and Discussion 63 References 69 CONCLUSIONS 72 Potential effects of climate change: sockeye salmon may be in hot water 72 iv List of Tables Table 1.1. Mean and range of sample sizes used to determine within-year standard lengths for each stock over the period 1952-1993, inclusive. Mean square error (MSE; cm) of length at maturity and minimum detectable difference (MDD; cm) in among-year comparisons are based on data from 1984-1993, inclusive 9 Table 1.2 Annual mean standard length at maturity (cm), standard deviation (SD), and number of years of data (n) for age 1.2 sockeye stocks of the Fraser River. Also shown are the correlation coefficients ( and associated probabilities) between standard length and year 14 Table 2.1 Correlation coefficients between age-, sex-,and stock-specific spawning ground length and abundance indices for Bristol Bay and Fraser River sockeye. Correlations that meet the Bonferroni adjusted significance level (P = 0.05/10 = 0.005) are underlined 42 Table 2.2 Correlation coefficients between age-, sex-, and stock-specific spawning ground length and Gulf of Alaska sockeye density indices. Correlations that meet the Bonferroni adjusted significance level (P = 0.05/12 = 0.004) are underlined. Sample sizes for some comparisons may vary by n-1 or n+1 43 Table 2.3. Comparison of standardized slopes (£'), probabilities that slopes are equal to zero (P b=o), coefficients of determination (r2) and number of years of data («) for relationships between mean spawning ground length of age 1.2 female and male Fraser River sockeye and abundance of age x.2+ ^.i Bristol Bay and Fraser River sockeye during the periods 1958-1975 and 1978-1992. The last column gives the probability from ANCOVA that slopes from the two periods are equal (P b\=b2) 48 Table 3.1. Age-specific correlations between marine growth estimated from scales (Mx) and age-specific ocean abundance of sockeye. Probabilities and number of data points are included below each r value. All probabilities are controlled for comparisonwise error rate (CER) by dividing a = 0.05 by the number of comparisons for each stock/age group. The CER = (.05/2) = 0.025 in all cases. Significant correlation coefficients appear in bold type. Data obtained from 1954 -1991, inclusive. 67 vi List of Figures' Figure 1.1. Map of Fraser River watershed and major sockeye salmon production systems : 7 Figure 1.2. Mean standard lengths (cm) of female Fraser River sockeye stocks over a 42 year period. Missing data points were either not available or excluded due to low sample size (n < 20). Dashed line represents linear time trend fitted by least squares. Correlation coefficients are reported in Table 2.1. 12 Figure 1.3. Mean standard lengths (cm) of male Fraser River sockeye stocks over a 42 year period. Missing data points were either not available or excluded due to low sample size. Dashed line represents linear time trend fitted by least squares. Correlation coefficients are reported in Table 2 13 Figure 1.4. Mean sea surface temperatures (SST) calculated from monthly averages (January - July, inclusive) over the period 1952-1992, inclusive, for a region in the northern Gulf of Alaska . See text 17 Figure 2.1. Minimum ocean abundance of age x. 1+ Bristol Bay (upper panel) and Fraser River sockeye (lower panel) in the Gulf of Alaska, 1954-1990 37 Figure 2.2. Comparison of ocean abundance estimates of age x.2+ Bristol Bay and Fraser River sockeye (1958-1973) with estimates of age 4 and 5 (total age) Gulf of Alaska sockeye from Peterman and Wong (1984). The dashed line represents the 1:1 relationship between the two datasets 38 Figure 2.3. Estimated thermal habitat area for sockeye salmon in the northeast Pacific ocean, 1961-1992 39 vii Figure 2.4. Relationships between mean spawning ground body length of females (abscissa) and abundance of age sockeye (ordinate) in the Gulf of Alaska during 1958-1975 (solid line;closed circles) and 1978-1992 (dashed line; open circles). Regression relationships that were significantly different between periods are shown. See Table 2.3 for regression summary 49 Figure 2.5. Relationships between mean spawning ground body length of males (abscissa) and abundance of age sockeye (ordinate) in the Gulf of Alaska during 1958-1975 (solid line;closed circles) and 1978-1992 (dashed line; open circles). Regression relationships that were significantly different between periods are shown. See Table 2.3 for regression summary 50 Figure 3.1. Marine growth of age 1.2 Early Stuart sockeye salmon over the years 1954-1991, inclusive for ocean entry year (Ml), penultimate year (M2), and return year (M3). Growth stages of a single cohort may be found by subtracting one from the return year for M2 and subtracting two for M l . For example, growth for the cohort returning in 1990 may be found under 1990 (M3), 1989 (Ml), and 1988 (Ml) 64 Figure 3.2. Relationships between second year marine growth (Ml) of Early Stuart sockeye (sexes combined) and minimum abundance of age x. 2+ sockeye in the Gulf of Alaska during the period 1954-1975 (open circles;solid line) and 1978-1991 (closed circles; dashed line) 68 viii List of Appendices Appendix 1. Reconstructed ocean abundance of Fraser River, British Columbia sockeye salmon totaled over ten major stocks (Chapter 2; Methods; Sockeye Abundance Data) 77 Appendix 2. Reconstructed ocean abundance of Bristol Bay, Alaska sockeye salmon totaled over eight major stocks (Chapter 2; Methods; Sockeye AbundanceData) 78 Appendix 3. Minimum ocean abundance of sockeye salmon totaled over Fraser River and Bristol Bay stocks (Chapter 2; Methods; Sockeye AbundanceData) 79 ix Acknowledgements Chapter 1, Changes in size at maturity of Fraser River sockeye salmon (1952-1993) and associations with temperature is accepted for publication in the Canadian Journal of Fisheries and Aquatic Science. I wish to thank my co-author and supervisor, Dr. Scott Hinch, who provided guidance and constructive criticism through the entire research process. I also thank Drs. David Welch and Michael Healey for their insights and suggestions which prompted many of the the ideas for the paper and this thesis. My colleagues on the NSERC Strategic Grant: Biophysical Controls of Sockeye 'Salmon Migration and Production also provided helpful comments and criticism of my research and early drafts of the chapters. Data used in this study was kindly provided by Jim Woodey and Mike Lapointe from the Pacific Salmon Commission, David Welch and Ron Diewert from the Department of Fisheries and Oceans, and Steve Fried from the Alaska Department of Fish and Game. Ian Jardine provided assistance with the SST data and Fraser River map. I would especially like to thank my family for their confidence and support of my education. Finally, I thank My wife, Aniko, who has been a limitless source of energy, inspiration, and love. x INTRODUCTION The objective of this study was to identify physical and biological factors that potentially affect the marine growth of Fraser River sockeye salmon (Oncorhynchus nerkd). The thesis proceeds from exploratory analyses of size at maturity data and temporal trends to tests of specific hypotheses that relate marine growth to biological factors on short time scales. The results from this study represent a significant contribution to the knowledge of marine life history of sockeye salmon and may be applied to both international and domestic salmon management as well as future high seas salmon research. Chapter 1 synthesizes spawning ground length data specific for ten Fraser River sockeye stocks to demonstrate that size at maturity has generally declined over the past 40 years for females in all stocks and for males from eight stocks. Independent of this temporal trend, size at maturity of both sexes in all stocks was smaller in years when sea surface temperatures were relatively warm. The long-term declines in size at maturity that were identified in Chapter 1 have coincided with dramatic increases in the biomass of salmon in the North Pacific Ocean. The observation that punctuated decreases in size at maturity occurred at the same time as an equally abrupt increase in salmon abundance led to the hypothesis that size at maturity of Fraser River sockeye is related to sockeye salmon density in the Gulf of Alaska. Tests of this hypothesis in Chapter 2 first involved reconstructing, by ocean age, a time series of minimum sockeye abundance in the Gulf of Alaska, 1954-1992, inclusive. Results from Chapter 2 demonstrate that size at maturity of 1 Fraser River sockeye is significantly reduced when abundance estimates of sockeye in the Gulf of Alaska are high. This result was not surprising based on other studies performed for different stocks and time periods. The most important finding in Chapter 2 is that during the period 1958-1975 marine growth of age 1.2 Fraser River sockeye was not related to population size. In contrast, Gulf of Alaska sockeye abundance from 1978-1992 explained a significantly large amount (33-81%) of variation in growth of Fraser River sockeye. The fact that the associations were not significant until abundance surpassed 100 million sockeye suggests that Bristol Bay and Fraser River stocks begin to overlap in ocean distribution beyond this level. Another important result gleaned from Chapter 2 is that tests for density-dependent growth that involve lagging abundance time series often have low power of detecting differences among the various hypotheses due to the large number of comparisons that are required. Because the conclusions from Chapter 2 rely on this type of analysis it was important to test these hypotheses using data more specific to the task. This was done in Chapter 3 by analysis of annual marine scale growth increments from the Early Stuart stock. Using the time-series of age-specific ocean abundance developed in the previous chapter, Chapter 3 demonstrates that marine growth was only reduced when sockeye abundance was high during the second year of ocean life; supporting the results obtained in Chapter 2. This result provides more direct evidence that density dependent growth occurs while Early Stuart sockeye are in the offshore regions of the Gulf of Alaska. 2 Chapter 1 Changes in size at maturity of Fraser River sockeye salmon (1952-1993) and associations with temperature Chapter Abstract Unlike other Canadian Pacific salmon (Oncorhynchus spp.) long-term declines in the size at maturity of Fraser River sockeye salmon (O. nerkd) have not been reported in past studies. Using data specific for ten Fraser River sockeye stocks, I demonstrate that size at maturity has generally declined over the past 42 years for females in all stocks and for males from eight stocks. Independent of this temporal trend, I found that size at maturity of both sexes in all stocks was smaller in years when sea surface temperatures were relatively warm. Slower growth in warmer years may be caused directly by increased metabolic demand, or indirectly by oceanic changes that influence food acquisition. I speculate that fitness of Fraser River sockeye will be reduced in the future if sea surface temperature increases and salmon abundance remains near present levels. 3 Introduction The size at maturity of Pacific salmon (Oncorhynchus spp.) has been decreasing in recent decades (Ricker 1982; Ogura et al. 1991; Helle and Hoffman 1995; Ishida et al. 1995; Ricker 1995; Bigler et al 1996). From 1951 to 1975, average weight of adult pink (O. gorbuschd), coho (O. kisutch), and chinook (O. tshawytscha ) salmon caught in coastal waters of British Columbia decreased by 5-25% (Ricker 1995). This reduction in weight has slowed somewhat for chinook salmon in recent years, however declines in weight of pink and coho salmon have continued (Ricker 1995). Declines of similar magnitudes have been observed for adult chum salmon (O. keta) captured in Asian and Alaskan waters (Ogura et al. 1991; Helle and Hoffman 1995). Sockeye salmon (O. nerkd) are the second most abundant salmon species in British Columbia waters and the most economically valuable (Healey 1993). Unlike other species, long-term declines in length or weight at maturity of Canadian sockeye salmon have not been detected (Ricker 1995). One reason may be that mixed-stock commercial catch data obscure individual stock trends. Age and size at maturity of Fraser River sockeye salmon can vary substantially among breeding populations (stocks), a result of both oceanic and genetic factors (Healey 1986; Blackbourn 1987; Burgner 1991). My first objective was to determine if stock-specific time trends exist for Fraser River sockeye salmon, and whether some or all of them are consistent with those of other Pacific salmon. I focus on Fraser River sockeye stocks. 4 The ocean life history of Fraser River sockeye salmon is typical of most British Columbia sockeye. In their second year of life, they enter the ocean and move northward along the coast between April and June (Groot et al. 1989; Burgner 1991). During autumn they move offshore into the open waters of the Gulf of Alaska where they typically remain for two years before maturing and returning to the Fraser River in their fourth year (French et al. 1976). Considerable among-year variation in size at maturity exists within most sockeye stocks (Healey 1986). Because size at maturity is not related to smolt size (Henderson and Cass 1991), oceanic environmental conditions must be largely responsible for variation in size at maturity. One of the main factors that may be responsible for interannual changes in size at maturity is temperature. Temperature affects growth directly through changes to metabolic costs (Nikolsky 1963; Furnell and Brett 1986; Jobling 1994; Hinch et al. 1995a), or indirectly through alteration of features that affect food acquisition (e.g. high seas distribution, population density, or migration routes; Ricker 1982; Laevestu 1984; Blackbourn 1987; Hsieh et al. 1991; Ishida et al 1995; Welch et al 1995). Hinch et al. (1995a, 1995b) found a negative relationship between sea surface temperature (SST) and size at maturity of Early Stuart sockeye salmon, a relatively small Fraser stock, however, these results may be too specific to a single stock to be generally applicable to Fraser River sockeye as a whole. Ricker (1982) found associations between SST and size of Fraser River sockeye salmon using mixed-stock commercial catch data collected from 1951 to 1974. However, SST regimes in the north Pacific Ocean have changed dramatically since 1974 (Hourston 1992) so SST-size correlations may also have changed; another problem is that mixed-stock data 5 may obscure or bias general species relationships between size at maturity and environmental factors if a small number of stocks have a dominant influence. My second objective was to examine the associations between SST and size at maturity of Fraser River sockeye salmon using stock-specific information. Methods Size at Maturity and SST Data As a measure of size at maturity, I used the average lengths of sockeye salmon measured on the major spawning grounds in the Fraser River drainage (Figure 1.1).- Although weight may be the best measure of size, large losses in weight occur during the up-river spawning migrations. Length changes very little during this migration so it is a better measure of size when dealing with spawning ground data. Average standard lengths (SL) of male and female age 1.2 sockeye from the spawning grounds of the Adams, Horsefly, Chilko, Early Stuart, Late Stuart, Raft, Late Nadina, Stellako, Birkenhead and Gates stocks were obtained from the archives of the Canadian Department of Fisheries and Oceans and the Pacific Salmon Commission for the years 1952-1993, inclusive (Appendix 1-10). The 1.2 age class accounts for up to 95% of Fraser River sockeye production in most years (Gable and Cox-Rogers 1993). The ages of spawning ground samples were determined by scales from 1952 to 1968 and by otoliths from 1968-1993 (Mike Lapointe, Pacific Salmon Commission, Vancouver, BC, pers. comm.). 6 7A Figure 1.1. Map of Fraser River watershed and major sockeye salmon production systems. 7 There was considerable variations, in the number of fish sampled for length on the spawning grounds. To ensure that average SL values from low sample years did not unduly affect results of analyses, I excluded years in which I did not have at least 20 SL values to create a mean for each combination of stock and sex. This criterion was chosen because of a natural gap in the data; in most years numbers of samples were well in excess of 20 but in a few years samples were less than 10. After excluding some data, annual sample sizes ranged from 72 to > 500 , depending on the stock (Table 1.1) . A summary of stock- and sex-specific mean SL is presented in Table 1.2. SST data came from the Comprehensive Ocean-Atmospheric Dataset which is described in Woodruff et al. (1987). Annual SST values were calculated by averaging the mean monthly SSTs for the region bounded by 142° to 146°W and 52° to 56°N. This geographic region was selected because it reflects the general area of the Gulf of Alaska that Fraser River sockeye inhabit (French et al. 1976). I used only January to July monthly temperatures because this period represents a portion of sockeye's life history that is half-way through their ocean residency when they are probably largely in the area where SST was estimated. In order to assess associations between SSTs encountered during their high-seas residency and SL at maturity, SST data were lagged by one year before carrying out any statistical analyses. 8 Table 1.1. Mean and range of sample sizes used to determine within-year standard lengths for each stock over the period 1952-1993, inclusive. Mean square error (MSE; cm) of length at maturity and minimum detectable difference (MDD; cm) in among-year comparisons are based on data from 1984-1993, inclusive. Females Males Stock mean range MSE MDD mean range MSE MDD. Adams 142 20 513 4.11 0.68 108 35- 337 4.72 0.83 Birkenhead 229 39 543 5.25 0.57 102 20- 314 16.32 1.56 Chilko 253 32 587 3.98 0.49 113 35 226 5.42 0.83 Early Stuart 106 28 203 4.25 0.78 72 24 145 5.16 1.01'-Gates 141 29 236 4.81 0.73 103 22 229 7.47 1.09 Horsefly 134 21 •408 4.59 0.73 105 22 254 3.96 0.91 Late Nadina 135 20 -290 4.17 0.71 93 20 228 4.63 0.89 Late Stuart 98 20 -200 4.31 0.88 91 20 420 6.54 1.12 Raft 143 20 -491 4.29 0.71 78 20 118 4.56 0.87 Stellako 164 79 -314 5.08 0.67 118 34 -299 5.42 0.83 Stock Average 155 4.48 0.70 98 6.42 0.99 Statistical Analyses Long-term trends in SL were determined by regressing SL on year (PROC REG; SAS Institute 1988). Among-stock regressions were compared using analysis of covariance (ANCOVA) with stock as the class variable (PROC GLM; SAS Institute 1988). ANCOVA was carried out separately for males and females. The presence of a long-term trend in sea surface temperature (SST) was assessed by regressing SST on year. 9 In order to examine the influence of within-year variability in SL on among-year trends I performed within-stock power analyses on each sex and determined among-year minimum detectable differences (MDD) in mean SL (Zar 1984). MDD reflect an estimate of measurement error. Stock- and sex-specific MDD were calculated using the mean sample size from each spawning area (1952 - 1993, inclusive) and the mean square errors (MSE) of length at maturity (1984 - 1993, inclusive). Only mean SL and sample size were available from the data archives prior to 1984.1 used the MDD as a check on the statistical significance of sex- and stock-specific SL versus year relationships. I removed existing linear time trends before relationships between SL and SST were determined, in order to reduce spurious correlations caused by similar underlying time trends. Residuals from the stock- and sex-specific regressions of SL and SST on year were then regressed on each other to examine potential effects of temperature on size at maturity. To assess the generality of these relationships, among-stock regressions were compared using ANCOVA separately for each sex. Results and Discussion Time Trends The slopes of the regressions of SL on year did not differ among stocks for females (ANCOVA; P = 0.17). This interaction term was then removed from the ANCOVA . revealing a significant effect of year (P<0.01) and stock (P<0. 01). In all stocks, female SL declined in a similar fashion over time (Figure 1.2; Table 1.2). Females from Adams, 10 Gates, and Raft stocks tended to have relatively large SL at maturity whereas Late Nadina had a relatively small SL at maturity. The slopes of the regressions of SL on year differed among stocks for males (ANCOVA; P < 0.01); the differences were attributable to Birkenhead and Gates stocks where size at maturity showed no time trend (Figure 1.3; Table 1.2). After removing these two stocks from the analysis, the remaining regression slopes did not differ among stocks (ANCOVA; P = 0.17). This interaction term was then removed from the ANCOVA revealing a significant effect of year (P < 0. 01) and stock (P < 0. 01). Among the remaining eight stocks, male SL declined similarly over time (Figure 1.3; Table 1.2). Males from Adams and Raft stocks tended to have relatively large SL at maturity whereas the Late Nadina stock had a relatively small SL at maturity. With the exception of males from Birkenhead and Gates stocks, mean length at maturity of Fraser River sockeye salmon declined over time (Figures 1.2 and 1.3; Table 1.2) and the 1990's produced the smallest Fraser River sockeye salmon out of the previous five decades for both males and females. 11 Figure 1.2. Mean standard lengths (cm) of female Fraser River sockeye stocks over a 42 year period. Missing data points were either not available or excluded due to low sample size (n < 20). Dashed line represents linear time trend fitted by least squares. Correlation coefficients are reported in Table 2.1. 12 1950 1960 1970 1980 1990 2000 1950 1960 1970 1980 1990 2000 1950 . 1960 1970 1980 1990 2000 1950 '1960 1970 1980 1990 2000 1950 1960 1970 1980 1990 2000 1950 1960 1970 1980 . 1990 2000 1950 1960 1970 1980 1990 2000 1950 1960 1970 1980 1990 2000 46 1960 . 1970 1980 1990 . 2000 1950 1960 1970 1980 1990 2000 12A Figure 1.3. Mean standard lengths (cm) of male Fraser River sockeye stocks over a 42 year period. Missing data points were either not available or excluded due to low sample size. Dashed line represents linear time trend fitted by least squares. Correlation coefficients are reported in Table 2. 13 1950 1960 1970 1 9 8 0 1990 2 0 0 0 1950 1960 1970 1 9 8 0 1 9 9 0 2 0 0 0 1 9 5 0 1 9 6 0 1 9 7 0 1980 1990 . 2 0 0 0 1 9 5 0 1 9 6 0 1 9 7 0 1980 1 9 9 0 2 0 0 0 1 9 5 0 1960 1970 1980 1990 2 0 0 0 1950 1 9 6 0 1 9 7 0 1980 1 9 9 0 2 0 0 0 1950 1960 1970 1980 1990 2000 . 1950 1960 1970 1 9 8 0 1990 2 0 0 0 1 9 6 0 1970 1980 1990 2 0 0 0 1950 1960 .1970 . 1 9 8 0 1990 2 0 0 0 13A Table 1.2 Annual mean standard length at maturity (cm), standard deviation (SD), and number of years of data (n) for age 1.2 sockeye stocks of the Fraser River. Also shown are the correlation coefficients ( and associated probabilities) between standard length and year. Female Males s Stock Mean SD n r P Mean SD n r P Adams 54.12 1.32 38 -0.35 0.03 58.61 1.74 36 -0.39 0.02 Birkenhead 53.11 1.50 38 -0.35 0.03 54.32 2.44 37 0.20 0.21 Chilko 52.29 1.61 41 -0.55 <0.01 54.98 1.47 41 -0.37 0.01 Early Stuart 52.80 1.31 33 -0.62 <0.01 55.73 1.12 31 -0.41 0.01 Gates 53.61 1.63 34 -0.35 0.04 57.56 1.87 32 -0.10 0.60 Horsefly 53.22 1.31 29 -0.42 0.02 57.00 1.64 28 -0.42 0.02 Late Nadina 48.76 1.19 34 -0.71 <0.01 50.33 1.48 34 -0.75 <0.01 Late Stuart 50.57 1.81 25 -0.66 <0.01 48,94 1.96 25 -0.54 <0.01 Raft 52.44 1.59 30 -0.71 <0.01 57.11 1.48 30 -0.57 <0.01 Stellako 51.31 1.42 40 -0.42 <0.01 53.86 1.37 40 -0.37 0.02 Stock Average 52.22 1.47 34 54.84 1.66 33 14 Power analyses indicated that minimum detectable differences (MDD) among-years in stock-specific size at maturity ranged from 0.83 - 1.56 cm for males , and 0.49 - 0.88 cm for females (Table 1.1). Each of the statistically significant stock- and sex-specific regression relationships between SL and year predicted a decline in size that exceeded the MDD (see Figures 1.2 and 1.3) suggesting that the declines are not the result of low sample size or measurement error in some years. The relatively larger MSE (and MDD; Table 1.1) of males implies that they varied more in size at maturity than females. This sex-specific difference in size variability has been found in other Pacific salmon species (Beacham and Murray 1985; Healey 1986). Greater within-stock variation in male size, at maturity may be due to the presence of alternative mating strategies (e.g. satellite and dominant behaviours) which exist for male Pacific salmon (Hanson and Smith 1967). Size related variability in female sockeye salmon mating strategies is less well defined. Mixed-stock commercial catch data have previously been used to examine trends in size at maturity of Canadian salmon (IPFSC 1963; Ricker 1982; Bigler et al 1996). With the exception of sockeye, Pacific salmon species have demonstrated a decline in size at maturity from the 1950's to the present (Ricker 1995). It is possible that variability in the relative abundance of sockeye salmon stocks could mask a general trend in size at maturity because size at maturity data will reflect the mean size at maturity of the most abundant stocks. This phenomenon is evident in sockeye salmon catch data (Ricker 1995); peaks in size at maturity of Fraser River sockeye caught in commercial fisheries coincide with peaks in the abundance of the Adams River stock which has one of the largest size at maturity (Table 1.2). Thus, their large size combined with relatively high abundance may 15 have resulted in a general species trend being obscured in past analyses that used mixed-stock catch data (i.e. Ricker 1995). I conclude that the size at maturity of Fraser River sockeye salmon has exhibited the same general decline over the past four decades that the other major Pacific salmon stocks have displayed. Size at Maturity and SST Relationships Average SST from January to July in the northeast Gulf of Alaska was positively associated with year; SST rose by almost 1°C from the early 1950's to the early 1990's. This temperature increase was first reported by Namias et al. (1988) who identified that a large-scale climate shift, resulting from changes to positions of the main high and low pressure areas, occurred over the northeast Pacific Ocean in 1976. The significant trend that I observed in the SST data indicates a similar punctuated change rather than linear increase (Figure 1.4). Since then, average annual SSTs have increased by 1°G in coastal areas and by 0.5°C in high seas areas. (Hourston 1992). ANCOVA revealed that slopes of the regressions of residual SL on residual SST did not differ among the 10 stocks for males (P = 0.07) or females (P = 0.18). These interaction terms were removed and the ANCOVA recomputed. Regression intercepts did not differ among stocks for males (P = 0.99) or females (P = 0.99). However, slopes differed from zero for both males (P = 0.01) and females (P < 0.01). The common regression equation between residual SL and residual SST was, for males: residual SL = -0.02 - 0.51 residual SST; and for females: residual SL = -0.01 - 0.32 residual SST. The negative slopes associated with these relationships suggest that the growth of Fraser River sockeye salmon is reduced during relatively warm years of their high-seas residency. My multi-stock 16 Figure 1.4. Mean sea surface temperatures (SST) calculated from monthly averages (January - July, inclusive) over the period 1952-1992, inclusive, for a region in the northern Gulf of Alaska . See text. 17 findings extend the single-stock results of Hinch et al. (1995a, 1995b) who found a negative association between SST and weight at maturity of the Early Stuart stock of Fraser River sockeye. Ricker (1982), using mixed-stock data collected from several British Columbia river systems before the climate shift of the late 1970s, also found that warmer SSTs were associated with smaller sockeye salmon. My results indicate that this relationship was consistently evident at the individual stock level, including the two stocks which did not show a decline in mean size with time, and that the relationship has continued in the two "warm" decades following the climate shift. The slower growth of sockeye salmon may result from increased metabolic demand under warmer ocean conditions which reduces growth potential (Jobling 1994). Hinch et al. (1995a), concluded that increased metabolic costs associated with SST increases of the magnitude observed over the past several years could account for observed declines in weight at maturity of the Early Stuart stock. A complimentary hypothesis is that slower growth under warmer ocean conditions may result from reductions in the amount of ocean habitat available, thereby increasing competitive interactions (Welch et al 1995), because in warm years the southern limit of sockeye salmon distribution is situated farther north than in cool years. Fraser River sockeye stocks vary in oceanic residence time (IPSFC 1990) and possibly in oceanic distribution (Blackbourn 1987; Welch and Parsons 1993). The fact that all stocks grew more slowly in warmer years indicates that SST may have powerful, broad-scale influences on sockeye salmon growth. However, size at maturity could be influenced by 18 environmental factors correlated with SST. When the abundance of salmon in the northeast Pacific Ocean is high, size at maturity may be reduced due to density-dependent growth (Peterman 1984, 1985, 1987; Ogura et al. 1991; Helle and Hoffman 1995; Ishida et al. 1995; Bigler et al 1996). Although the abundance of sockeye salmon in the Gulf of Alaska doubled over the past, relatively warm, 15 years (Beamish and Bouillon 1993), macrozooplankton biomass has approximately doubled during this same time (Brodeur and Ware 1995). Hindi et al. (1995b) showed that zooplankton biomass was correlated to size at maturity of Early Stuart sockeye in cool years, but stock abundance also helped explain variation in weight in warm years. The role of SST in mediating density dependent growth needs to be more fully explored. References Beacham, T.D., and Murray C.B., 1985. Variation in length and body depth of pink salmon (Oncorhynchus gorbuscha) and chum salmon (O. keta) in southern British Columbia. Can. J. Fish. Aquat. Sci. 42: 312-319. Beamish, R.J., and Bouillon, DR. 1993. Pacific salmon production trends in relation to climate. Can. J. Fish. Aquat. Sci. 50: 1002-1016. Bigler, B.S., Welch, D.W., and Helle, J.H. 1996. A review of size trends among north Pacific salmon (Oncorhynchus spp.). Can. J. Fish. Aquat. Sci. (in press). 19 Blackbourn, D. J. 1987. Sea surface temperature and the pre-season prediction of return timing in Fraser River sockeye salmon (Oncorhynchus nerka). In: Sockeye salmon (Oncorhynchus nerka) population biology and future management. Edited by H.D. Smith, L. Margolis, and C C . Wood Can. Spec. Publ. Fish. Aquat. Sci. 96: pp. 296 -306. Brodeur, R. D., and Ware, D. M . 1995. Interdecadal variability in distribution and catch rates of epipelagic nekton in the Northeast Pacific Ocean. In: Climate change and northern fish populations. Edited by R J . Beamish. Can. Spec. Publ. Fish. Aquat. Sci. 121. pp. 329-356. Burgner, R.L. 1991. Life Flistory of Sockeye Salmon. In: Pacific Salmon Life Histories. Edited by C. Groot and L. Margolis. UBC Press, Vancouver, p. 3-117. French, R., Bilton, H , Osako, M. , and Hartt, A. 1976. Distribution and origin of sockeye salmon in offshore waters of the North Pacific ocean. International North Pacific Fisheries Commission Bull. 34: 113 pp. Furnell, D.J., and Brett, JR. 1986. Model of monthly marine growth and natural mortality for Babine Lake sockeye salmon (Oncorhynchus nerka ). Can. J. Fish. Aquat. Sci. 43: 999-1004. 20 Gable, J., and Cox-Rogers, S. 1993. Stock Identification of Fraser River Sockeye Salmon: Methodology and Management Application. Pacific Salmon Commission Technical Report 5: 36 pp. Groot, C , Bailey, R.E., Margolis, L., and Cooke, K. 1989. Migratory patterns of sockeye salmon (Oncorhynchus nerka) smolts in the Strait of Georgia, British Columbia, as determined by analysis of parasite assemblages. Can. J. Zool. 67: 1670-1678. Hanson, A.J., and Smith, H.D. 1967. Mate selection in a population of sockeye salmon (Oncorhynchus nerka) of mixed age groups. J. Fish. Res. Board. Canada. 24: 1955-1977 Healey, M.C. 1986. Optimum Size and Age at Maturity in Pacific Salmon and Effects of Size-Selective Fisheries. In: Salmonid age at maturity. Edited by D.J. Meerburg. Can. Spec. Publ. Fish. Aquat. Sci. 89: pp. 39-52. Healey, M.C. 1993. The management of Pacific salmon fisheries in British Columbia. In: Perspectives on Canadian marine fisheries management. Edited by L.S. Parsons and W.H. Lear. Can. Bull. Fish. Aquat. Sci. 226: pp. 243-266. Helle, J.H., and Hoffman, M.S. 1995. Size decline and older age at maturity of two chum salmon (Oncorhynchus keta) stocks in western North America. In: Climate change and northern fish populations. Edited by R.J. Beamish. Can. Spec. Publ. Fish. Aquat. Sci. 121. pp. 245-260. 21 Henderson, M.A., and Cass, A.J. 1991. Effect of smolt size on smolt-adult survival for Chilko Lake sockeye salmon (Oncorhynchus nerka). Can. J. Fish. Aquat. Sci. 48: 988-994. Hindi, S.G., Healey, M.C., Diewert, R.E., and Henderson, M. A. 1995a. Climate change and ocean energetics of Fraser River sockeye (Oncorhynchus nerka). In. Climate change and northern fish populations. Edited by R.J. Beamish.Can. Spec. Publ. Fish. Aquat. Sci. 121. pp. 439-445 Hindi, S.G., Healey, M.C., Diewert, R.E., Thomson, K.A., Hourston, R., Henderson, M.A., and Juanes, F. 1995b. Potential effects of climate change on marine growth and survival of Fraser River sockeye. Can. J. Fish. Aquat. Sci. 52: 2651-2659. Hourston, R.A. 1992. Variability of North Pacific Ocean surface sensible and latent heat fluxes. M.Sc. Thesis, University of British Columbia, Vancouver, B.C. Hsieh, WW., Lee, W.G., and Mysak, L.A. 1991. Using a numerical model of the Northeast Pacific Ocean to study the interannual variability of the Fraser River sockeye salmon (Oncorhynchus nerka). Can. J. Fish. Aquat. Sci. 48: 623-630. 22 Killick, S.R., and Clemens, W.A. 1963. The age, sex ratio and size of Fraser River sockeye salmon, 1915 to 1960. International Pacific Salmon Fisheries Commission Bull. XIV: 140 p. Gilhousen, P. 1990. Prespawning mortality of sockeye salmon in the Fraser River system and possible causal factors. International Pacific Salmon Fisheries Commission Bull. X X V I : 51 p. Ishida, Y., Welch, D.W., and Ogura, M . 1995. Potential influence of North Pacific sea-surface temperatures on increased production of chum salmon (Oncorhynchus keta) from Japan. In. Climate change and northern fish populations. Edited by R.J. Beamish.Can. Spec. Publ. Fish. Aquat. Sci. 121. pp. 271-275. Jobling, M. 1994. Fish Bioenergetics. Chapman & Hall. London. Laevastu, T. 1984. The effects of temperature anomalies on the fluctuation of fish stocks. J. de Conseil pour Exploration de la Mer 185: 214-225. Namias, J., Yuan, X., and Cayan, D.R. 1988. Persistence of North Pacific sea surface temperature and atmospheric flow patterns. J. Clim. 1: 682-703. Nikolsky, G.V. 1963. The Ecology of Fishes. Academic Press, London. 23 Ogura, M. , Ishida, Y., and Ito, S. 1991. Growth variation of coho salmon Oncorhynchus kisutch in the Western North Pacific. Nippon Suisan Gakkaishi 57: 1089-1093 Peterman, R.M. 1984. Density-dependent growth in early ocean life of sockeye salmon (Oncorhynchus nerka). Can. J. Fish. Aquat. Sci. 41: 1825-1829. Peterman, R.M. 1987. Review of the components of recruitment of Pacific salmon. American Fisheries Society Symposium 1: 417-429. Ricker, W.E. 1982. Size and age of British Columbia sockeye salmon (Oncorhynchus nerka) in relation to environmental factors and the fishery. Can. Tech. Rep. Can. Fish. Aquat. Sci. 1115 . Ricker, W. E. 1995. Trends in the average size of Pacific salmon in Canadian catches. In: Climate change and northern fish populations. Edited by R.J. Beamish.Can. Spec. Publ. Fish. Aquat. Sci. 121. pp. 593-602 SAS Institute. 1988. SAS/STAT Users Guide, version 6.03. SAS Institute, Cary, North Carolina. Welch, D.W., Chigirinsky, A.I., and Ishida, Y. 1995. Upper thermal limits on the oceanic distribution of Pacific salmon (Oncorhynchus spp.) in the spring. Can. J. Fish. Aquat. Sci. 52:489-503. 24 Welch, D.W., and Parsons, T.R. 1993. 5 1 3 C and 8 N isotope values as indicators of trophic position and competitive overlap for Pacific salmon (Oncorhychus spp). Fish. Oceanogr. 2: 11-23. Woodruff, S.D., Slutz, R.J., Leane, R.L., and Steurer, P.M. 1987. A comprehensive • ocean-atmosphere dataset. Bull. Am. Meterol. Soc. 68: 1239-1250. Zar, J.H. 1984. Biostatistical Analysis. 2nd ed. Simon & Schuster Co., Englewood Cliffs, NJ. 25 Chapter 2 Effects of abundance and thermal habitat on marine growth of Fraser River sockeye salmon Chapter Abstract Large increases in the abundance of Pacific salmon (Oncorhynchus spp.) over the past two decades have coincided with sharp declines in growth rates of many sockeye salmon (Oncorhynchus nerka) stocks. I use catch and escapement data from Bristol Bay and Fraser River sockeye stocks to reconstruct, by ocean age, a minimum ocean abundance time series of sockeye salmon in the Gulf of Alaska, 1952-1992. The role of ocean habitat was assessed by dividing the abundance estimates by an index of thermal habitat available to sockeye salmon in the northeast Pacific. I demonstrate that age-, sex-, and stock-specific size at maturity of Fraser River sockeye is significantly reduced when abundance and density estimates of sockeye in the Gulf of Alaska are high. I also show that during a period of generally low oceanic productivity (1958-1975) marine growth of age 1.2 Fraser River sockeye was not related to population size. In contrast, during a period of high productivity (1978-1992) sockeye abundance in the Gulf of Alaska explained 33-81% of variation in growth of females and 33-79%o in males. My results suggest that under present climatalogical conditions and biological productivity, density dependent marine growth of Fraser River sockeye may occur if the abundance of age x.2+ sockeye exceeds approximately 100 million. 26 Introduction Since the mid-1970's, large changes have occurred to the physical characteristics, biological productivity, and salmon abundance in the North Pacific Ocean. For example, sea surface temperature rose approximately 1°C in coastal areas and 0.5°C in the open sea, presumably in response to global climate change (Hourston 1992). Also, the Aleutian Low Pressure system, which drives much of the surface current and nutrient upwelling in the Gulf of Alaska, was more intense during the 1980's compared to the period 1950-1970 (Namias et al. 1988; Beamish and Bouillon 1993). These and other changes in the physical characteristics of the north Pacific have coincided with large increases in biological productivity (Beamish and Bouillon 1993; Brodeur and Ware 1992; Polovina 1994). Between the 1960s and 1980s average summer biomass of zooplankton at Ocean Station P, located in the centre of the Gulf of Alaska, nearly doubled (Brodeur and Ware 1992). Substantial increases also occurred in the average biomass of other pelagic nekton such as neon flying squid, albacore, pomfret, salmon shark, and all species of Pacific salmon (Brodeur and Ware 1995). For Pacific salmon (Oncorhynchus spp.), larger increases in the abundance of the three species that migrate to the open sea (sockeye, pink, and chum) relative to species that are found in coastal areas (chinook and coho) suggests that changes in biological productivity were more prevalent in the open sea (Ware and McFarlane 1989; Brodeur and Ware. 1995). Coincident with the recent increase in salmon abundance has been a decrease in average size at maturity (Ishida et al 1993; Bigler et al 1996; Chapter 1; Cox and Hinch in press). This was particularly evident in most major Fraser River sockeye salmon stocks (O. nerka) 27 which have declined 3-6 cm in average size during the past twenty years (1976-1993) relative to the period 1952-1975 (Chapter 1; Cox and Hinch in press). Prior to the large changes in biological productivity that began in the mid 1970's, Rogers (1980) and Peterman (1984) examined interannual variation in growth of sockeye salmon from Alaska and British Columbia. Both showed that marine growth in the Gulf of Alaska of several sockeye stocks decreased linearly with increasing population size implying that growth was density dependent. Their results have been used by many authors ( e.g. Chapter 1; Helle and Hoffman 1995; McKinnell 1995; Cox and Hinch in press; Bigler et at 1996) as a basis for speculation that recent declines in size at maturity of all species of Pacific salmon are due to the large increases in salmon abundance that occurred over the past twenty years since Rogers' and Peterman's studies. Very few studies, however, have addressed this relationship directly (except see Ishida et al. 1993) and attempted to assess whether indeed, the recent declines in size of salmon are a density dependent phenomenon Present levels of sockeye salmon abundance in the Gulf of Alaska are at or near those that occurred prior to commercial exploitation (Welch and Parsons 1993). Thus, it is not surprising that many authors attribute recent declines in size to these increases by extrapolating the density-dependent relationships found by Rogers (1980) and Peterman (1984). However, increases in biological productivity in the North Pacific Ocean should have compensated for at least some of the increases in sockeye abundance resulting in a less severe loss in per capita ration size. This should, in turn, have resulted in less severe declines in size at maturity than those exhibited by many Fraser River sockeye stocks 28 (Chapter 1; Cox and Hinch in press). The rapid declines in size of Fraser River sockeye, which began in the relatively productive late-1970's and early-1980s, suggest that there is a need to examine density-dependent growth relationships from a more recent perspective. In particular, it is important to understand whether density dependent growth relationships still exist or have changed under different productivity regimes and levels of abundance. My first objective is to examine the evidence for density-dependent marine growth using data from 1958-1992 of ten Fraser River sockeye salmon stocks. I accomplish this by reconstructing, by ocean age, the minimum annual abundance of sockeye salmon in the Gulf of Alaska. This time period also provides contrast in both oceanic productivity and total Gulf of Alaska sockeye salmon abundance, thus enabling me to assess potential differences in density-dependent growth relationships between the periods 1958-1975 (low productivity, low abundance) and 1976-1992 (high productivity, high abundance). The decline in growth rates of sockeye during periods of increasing productivity could also be caused by physical factors such as increasing sea surface temperatures that limit the habitat available to salmon and thus exacerbate density-dependent growth (Welch et al 1995; Cox and Hinch 1997). The hypothesis that physical factors limit the distribution of salmon was first proposed by researchers from the International North Pacific Fisheries Commission (INPFC) during 1950's and 1960's. Much of this historical research on the high seas ecology of salmon centered on identifying migratory pathways and boundaries to the distribution of North American and Asian stocks of salmon (Hartt 1966; French 1976; Welch et al. 1995). The purpose of the research was to establish zones where North 29 American salmon would be protected from high seas interception by Japanese fishing fleets. In performing this work the INPFC studies provided volumes of valuable information on the oceanic distribution of Pacific salmon. It is now recognized that the distribution of North Amercian salmon within the region 128°W to 175°W is associated with certain physical oceanographic features such as thermal and saline fronts and current streams (Hartt 1966; French et al. 1976; Ignell and Murphy 1993). Of these physical oceanographic factors, temperature has been shown to be most important in delineating their southern limits; salmon seem to avoid certain regions where temperature is relatively high, but well below the lethal levels (Welch et al. 1995). My second objective in this paper is to assess the role of thermal limits and its potential effects on density-dependent growth. I accomplish this by developing an annual index of sockeye salmon density that is based on recontructed ocean abundance and annual thermal habitat area. Methods Gulf of Alaska Sockeye Abundance Most sockeye salmon that are found east of the North Pacific Convention (NPC) provisional line along 175°W are from either Western Alaska or British Columbia (Hartt 1966). Of these fish the Bristol Bay and Fraser River stock complexes are the most abundant (Peterman 1984). I use data on the escapement and commercial catch of Bristol 30 Bay and Fraser River sockeye salmon stocks to derive an estimate of minimum ocean abundance of sockeye in the Gulf of AJaska. Bristol Bay sockeye abundance data from 1954-1994 inclusive, were obtained from the Alaska Department of Fish and Game (Steve Fried, AK Dept of Fish and Game, Anchorage, AK, pers. comm.). The stocks included in this analysis are Kvichak, Branch, Naknek, Egegik, Ugashik, Wood, Igushik, and Togiak. Age classes 1.2, 1.3, 2.2, and 2.3 were used because they comprise over 97% of the total sockeye returns from these rivers (Peterman 1984). Data collection methods for estimating Bristol Bay sockeye salmon catch and escapement are described in Peterman and Wong (1984). Annual total return estimates (catch + escapement) of age 1.1, 1.2, and 1.3 sockeye from ten Fraser River sockeye stocks were obtained from Pacific Salmon Commission (PSC) and Department of Fisheries and Oceans (DFO) archives. Howard and Chapman (1948) provide a complete description of methods used to enumerate Fraser River sockeye escapements. Methods used to determine the stock and age composition of the commercial catch are described in Woodey (1987). The 1.2 (89.25%), 1.3 (6.9%>), 1.1 (2.2%o), and 2.2 (1.6%) age classes constitute the major portions of sockeye from the Fraser River (Killick and Clemens 1963). I estimated, by ocean age, the minimum ocean abundance of sockeye in the Gulf of Alaska by applying virtual population analysis to catch and escapement data from Bristol Bay and Fraser River stocks. I use ocean age (winters at sea) as an age classification because it 31 provides a better indication of the relative size of individual fish compared to total age (freshwater + winters at sea). Ocean age classes used in the reconstruction were x. 1 (1 winter at sea), x.2 (two winters at sea), x.2+, x.3 (three winters at sea), and x.3+. Ocean age four (x.4) was the maximum age considered for this analysis because of the extremely small numbers offish that spend greater than four winters at sea. A few Bristol Bay stocks have small numbers of these fish; however, their numbers were not large enough to justify separate age category. I used the method of Fry (1949) as described in Peterman and Wong (1984) to calculate a minimum estimate of age-specific ocean abundance (Eq 1). Nj,t = Ri,t + Ri+l,t+l + Ri+2,t+2 Rm,t+m-i (Eq. 1) where Nt,t = number of ocean age i fish in year t Rj,t = Returns (catch + escapement) of ocean age / fish in year t m = maximum ocean age Age-specific abundance (N i i t ) was then summed across Bristol Bay and Fraser River stocks for each year to arrive at the minimum ocean abundance for each ocean age. The analyses that follow are based on the assumption that Gulf of Alaska abundance indices for all ages are representative of the true abundance of those ages during those time periods. As in Peterman (1984), I did not apply an annual survival rate to the VP A estimates of abundance. The reason for this is that information on annual marine survival rates of sockeye are not available. Therefore, this assumption is probably not valid for juveniles (x. 0) because the VPA calculation does not account for variation in marine > 32 survival among-years and possibly among-stocks within-years. Variation in marine survival of Pacific salmon is log-normal and is assumed to occur mostly during early ocean life (Ricker 1962; Peterman 1981; Bradford 1995). Therefore, not adjusting abundance by a survival factor may have large effects on the interannual variation in x. 0 abundance and to a lesser extent x. J and older. It is for this reason that I do not include age x. 0 in the following analyses. Sockeye Density Index As described earlier, I use regions of optimal temperature as an index of total habitat available to sockeye salmon in the northeast Pacific Ocean. I refer to this area throughout this paper as thermal habitat area (THA). Thermal habitat area (THA) is defined here as that area (km2) of the north Pacific Ocean that is permanently bounded by the INPFC provisional line (175°W) to the west and the Aleutian Island chain to the north. A month-specific isotherm, which determined the southern limit to the distribution of sockeye (David Welch, Pacific Biological Station, Nanaimo, BC pers. comm.), was used as a dynamic boundary to the south and east. For each combination of month and year I calculated the area of the north Pacific Ocean that fell within these boundaries. SST data used to estimate the monthly position of sea surface isotherms were obtained from the Comprehensive Ocean-Atmospheric Dataset which is described in Woodruff et al. (1987). Monthly averages were then averaged within-years to arrive at an annual thermal habitat index for sockeye in the Gulf of Alaska. Estimates of age-specific ocean abundance for each year were then divided by the thermal habitat index to arrive at the annual estimates of age-specific sockeye salmon density. 33 Marine growth data Because over 98% of total somatic growth of sockeye salmon occurs in the ocean and because final size is not related to smolt size (Henderson and Cass 1991) I used spawning ground length (SL) as a measure of marine growth. Spawning ground lengths of age 1.1 and 1.2 sockeye from ten of the major Fraser River stocks were obtained from PSC and DFO archives. A full description of these data may be found in Chapter 1 and Cox and Hinch (in press). The Fraser River sockeye salmon stocks included in this study are Adams, Birkenhead, Chilko, Early Stuart, Gates, Horsefly, Late Nadina, Late Stuart, Raft, and Stellako. Because detailed data on size at maturity were not available, many of these stocks were not included in the original analyses of Peterman (1984). Statistical Analysis A correlation matrix was generated to examine the associations between abundance and density estimates and marine growth of Fraser River sockeye over the period 1961-1992, inclusive. Each stock-, age-, and sex-specific time series of SL was compared to five categories of abundance time series and five corresponding density time series. The abundance and density categories used were x. 1 ry.2 (dx. 1 ry.2), x. J ry-i (dx. 1 ry.i), x. 2 ^ . i (dx.2ry.i), x.2+ ry-i (dx.2+ ry.i), x.2+ ^ ^ . 2 + ry), and x.3 ry (dx.3 ry) where the subscript (ry) represents return year. Each category represents a hypothesis about the ocean age classes involved and timing of interactions that may lead to density-dependent ocean growth of sockeye salmon. For example, to test the hypothesis that abundance of x. 1 sockeye (or density, dx. 1) is associated with marine growth during the year of ocean entry, I examine correlations between SLry and x. 1 .^2 (dx.l .^2). Due to the large number of comparisons (10) for each stock-, age-, and sex-specific SL time series, Bonferroni adjustments were 34 used to control the comparis'onwise error rate. The abundance and density measures that were significantly correlated with stock-, age-, and sex-specific SL were recorded. Abundance-SL correlations were then compared to the corresponding density-SL correlations by Fisher's Z-test (Zar 1984, p.310) within each stock, sex, and age class in order to assess the utility of thermal habitat area information. Correlations were also compared among ocean age categories and lags in an attempt to identify key ocean age classes and time periods that may lead to density-dependent growth. After identifying the most critical age class interactions and timing, I proceeded to test the hypothesis that these relationships have changed since the coincident increases in ocean productivity and salmon abundance. To accomplish this, SL and ocean abundance data were grouped into two time periods. The first period (1958-1975) represented low ocean productivity and low salmon abundance and the second (1976-1992) represented high productivity and high salmon abundance. After stratifying the data by period, I detected a significant increasing linear trend in ocean abundance from 1976 to 1992.1 eliminated this trend by removing the low abundance years 1976 and 1977so that a fair comparison could be made between the two periods. I used analysis of covariance (ANCOVA) (PROC GLM; SAS Institute 1988) to test the hypothesis that the slopes of relationships between stock- and sex-specific SL of age 1.2 Fraser River sockeye and ocean abundance were the same for the two periods. 35 Results and Discussion From the 1950's to 1990's the abundance of sockeye salmon more than doubled in the Gulf of Alaska. Average annual minimum ocean abundance of x.2+ sockeye was 46.6 million over the period 1954-1974 and increased to an average 95.1 million from 1976-1992. The doubling of abundance is due largely to increases in Bristol Bay stocks, which have apparently benefited from both a reduction in high-seas interception and increased ocean productivity (Eggers et al. 1984). The abundance of Fraser River sockeye, on the other hand, increased more gradually between the 1960's and the late-1980's and approximately doubled in abundance (Figure 2.1). As a check on the data, I compared estimates of x.2+ abundance with similar estimates of ages 4 and 5 (total age) sockeye obtained (to the nearest million) from graphs found in Peterman and Wong (1984). Age classes 4 and 5 were selected because they most closely resemble my x.2+ age grouping. The two datasets were highly correlated; however, my data were biased high compared to Peterman and Wong (1984) (Figure 2.2). This was expected due to the addition of older ages in the x.2+ age group. The single outlier (1959) could not be explained without detailed knowledge of the ocean ages present in the data of Peterman and Wong (1984). Close examination of the influence of the 1959 data point showed that it had no affect on the final results.General agreement between the two datasets permits more meaningful comparisons between my results and those of Peterman (1984) and McKinnell (1995). Both of these studies used minimum ocean abundance data from Peterman and Wong (1984). 36 Estimated thermal habitat area for sockeye in the northeast Pacific followed what appears to be a long-period fluctuation with little interannual variation (Figure 2.3) THA averaged 1.05 million km2 from the early 1960's to the mid-1970's, with a maximum (1.35 million km2) occurring during the mid-1970's. THA reached lows in the early 1960's (856,000 km2) and again in the early 1990's (90,000 km2). Figure 2.1. Minimum ocean abundance of age x. 1+ Bristol Bay (upper panel) and Fraser River sockeye (lower panel) in the Gulf of Alaska, 1954-1990. 0 I . 1 1 . 1 1950 1960 1970 1980 1990 37 Figure 2.2. Comparison of ocean abundance estimates of age x.2+ Bristol Bay and Fraser River sockeye (1958-1973) with estimates of age 4 and 5 (total age) Gulf of Alaska sockeye from Peterman and Wong (1984). The dashed line represents the 1:1 relationship between the two datasets. 100 _ 80 c o ! | 60 a) u co TJ C 3 .Q < + CN 40 f 20 20 40 60 80 P&WAge 4+5 Abundance (millions) 100 38 Figure 2.3. Estimated thermal habitat area for sockeye salmon in the northeast Pacific ocean, 1961-1992. 39 (2"J>I s.OOO) eeJV Gulf of Alaska abundance and density were both significantly correlated with age-, sex-, and stock-specific SL at maturity of Fraser River sockeye (Table 2.1). Although density-SL correlations (Table 2.2) were generally of greater magnitude, none were significantly different from their corresponding abundance-SL correlations (Fishers Z-test P > 0.05). An annual index of thermal habitat, therefore, does not appear to explain a significant amount of variation beyond that explained by Gulf of Alaska sockeye abundance. It is possible that my initial choice of an annual index does not reflect the true importance of thermal habitat in affecting sockeye salmon growth. If the majority of body growth occurs in short intervals (e.g., spring and summer) then my use of an annual index would be inappropriate. However, the limited amount of data that is available on seasonal growth patterns suggest that sockeye are able to find suitable conditions for growth throughout the year (Bilton and Ludwig 1966; French et al. 1976). More likely, the range of THA that I have observed is not representative of events that determine salmon density at the appropriate scale. Using THA to derive an index of density assumes that salmon are evenly distributed within the available habitat. In reality, salmon on the high seas are not distributed evenly and are often found in aggregations on spatial scales from 0-2000 km (Ignell and Murphy 1993; Welch et al. 1995; Hinch unpubl. data). Therefore, changes in THA on a large scale may not necessarily effect similar changes on small scale salmon density. THA may be important in describing the limits to the distribution of salmon, but its value for predicting actual salmon density within the distribution is probably limited, as was initially suggested by Welch et al (1995). Because of these limitations and the fact that abundance and density indices did not differ in their association with SL I will limit the following discussion to abundance-SL associations. 40 Female SL from ten stocks were significantly correlated with at least one category of ocean abundance. S L ^ were most highly correlated with the x.2+ ry-i category (7 stocks) followed by x.2+ ^ (2 stocks), and x.3 ry (1 stock). Although most maximum correlations occurred for the x.2+ ry-i category, the correlation coefficients (within stocks) between SLry and each of the three categories (x.2+ ry-i, x.2+ ^, and x.3 ry) were not significantly different from each other (Fisher's Z-test; P > 0.05). Male SL from eight stocks was significantly correlated with at least one category of ocean abundance. SL ^ were most highly correlated with the x.2+ ry.i category (5 stocks) followed by x.2+ ^ (2 stocks) and x.3+ ry(l stock). Again, differences in correlation coefficients among the three categories were not significant (Fisher's Z-test; P > 0.05). SL of age 1.1 male (jack) sockeye from only two stocks were significantly correlated with at least one category of ocean abundance. Birkenhead River and Gates Creek were the two stocks whose abundance-SL correlations (with x.2+ ^  and x.2+ ry.i, respectively) met the required adjusted significance level (p = 0.05/10 = 0.005). Five additional stocks were significantly correlated with at least one ocean abundance category at the 0.01 (3 stocks) and 0.05 (2 stocks) levels. As with age 1.2 males and females, differences in correlation coefficients among abundance categories were not significant (Fisher's Z-test; P > 0.05). 41 Table 2.1 Correlation coefficients between age-, sex-,and stock-specific spawning ground length and abundance indices for Bristol Bay and Fraser River sockeye. Correlations that meet the Bonferroni adjusted significance level (P = 0.05/10 = 0.005) are underlined. Age, sex, and stock n X. J ry.2 X. 1 ry-l X.2 ry-l X. 2 ry X. 2 + ry-l X» 3 ry 1.1 Males Adams 26 -0.245 -0.329 -0.245 -0.398 -0.431 -0.245 Birkenhead 31 -0.571 -0.553 -0.571 -0.713 -0.614 -0.572 Chilko 29 -0.333 -0.389 -0.333 -0.447 -0.300 -0.333 Early Stuart 19 0.117 -0.136 0.117 -0.057 -0.179 0.115 Gates 28 -0.398 -0.315 -0.398 -0.497 -0.539 -0.399 Horsefly 9 0.124 -0.154 0.124 -0.111 -0.424 0.124 Late Nadina 16 -0.280 0.073 -0.280 -0.192 -0.434 -0.280 Late Stuart 10 -0.414 -0.566 -0.414 -0.638 -0.751 -0.417 Raft 12 0.150 -0.161 0.150 -0.042 0.021 0.150 Stellako 19 -0.473 -0.213 -0.473 -0.427 -0.563 -0.474 1.2 Males Adams 28 -0.457 -0.178 -0.457 -0.455 -0.585 -0.458 Birkenhead 31 -0.323 0.146 -0.323 -0.134 -0.312 -0.323 Chilko 32 -0.523 -0.414 -0.523 -0.594 -0.521 -0.524 Early Stuart . 29 -0.476 -0.183 -0.476 -0.432 -0.515 -0.477 Gates 28 -0.280 -0.096 -0.280 -0.303 -0.462 -0.280 Horsefly 22 -0.604 -0.506 -0.604 -0.709 -0.468 -0.605 Late Nadina 29 -0.689 -0.456 -0.689 -0.721 -0.732 -0.689 Late Stuart 23 -0.595 -0.433 -0.595 -0.641 -0.490 -0.595 Raft 30 -0.550 -0.257 -0.550 -0.522 -0.508 -0.551 Stellako 32 -0.550 -0.230 -0.550 -0.525 -0.588 -0.551 1.2 Females Adams 30 -0.519 -0.288 -0.519 -0.518 -0.536 -0.519 Birkenhead 32 -0.621 -0.346 -0.621 -0.658 -0.762 -0.621 Chilko 32 -0.501 -0.566 -0.501 -0.676 -0.528 -0.501 Early Stuart 30 -0.479 -0.222 -0.479 -0.454 -0.524 -0.480 Gates 30 -0.580 -0.396 -0.580 -0.651 -0.706 -0.580 Horsefly 23 -0.514 -0.533 -0.514 ,0.675 -0.471 -0.514 Late Nadina 29 -0.581 -0.401 -0.581 -0.633 -0.595 -0.581 Late Stuart 23 -0.710 -0.372 -0.710 -0.701 -0.674 -0.711 Raft 30 -0.475 -0.287 -0.475 -0.521 -0.544 -0.475 Stellako 32 -0.474 -0.224 -0.474 -0.476 -0.545 -0.475 42 Table 2.2 Correlation coefficients between age-, sex-, and stock-specific spawning ground length and Gulf of Alaska sockeye density indices. Correlations that meet the Bonferroni adjusted significance level (P = 0.05/12 = 0.004) are underlined. Sample sizes for some comparisons may vary by n-1 or n+1. Age, sex, and stock n dx. lry-l dx.2 ry-j dx.2+ry - dx.2+ry.i 1.1 Males Adams 26 -0.218 -0.295 -0.233 -0.398 -0.426 -0.255 Birkenhead 30 -0.516 -0.545 -0.588 -0.710 -0.633 -0.595 Chilko 28 -0.243 -0.371 -0.337 -0.449 -0.373 -0.348 Early Stuart 18 0.129 -0.210 0.037 -0.108 -0.276 0.066 Gates 27 -0.432 -0.327 -0.444 -0.492 -0.562 -0.417 Horsefly 8 0.309 -0.086 0.225 -0.227 -0.421 0.040 Late Nadina 15 -0.298 0.115 -0.260 -0.224 -0.399 -0.286 Late Stuart 9 -0.498 -0.679 -0.511 -0.668 -0.805 -0.442 Raft 11 -0.072 -0.265 0.076 -0.128 0.021 0.083 Stellako 19 -0.517 -0.261 -0.537 -0.479 -0.615 -0.513 1.2 Males Adams 27 -0.482 -0.259 -0.539 -0.515 -0.630 -0.515 Birkenhead 30 -0.341 0.164 -0.338 -0.116 -0.297 -0.296 Chilko 31 -0.429 -0.412 -0.520 -0.659 -0.544 -0.583 Early Stuart 28 -0.435 -0.241 -0.515 -0.483 -0.563 -0.523 Gates 27 -0.345 -0.203 -0.381 -0.342 -0.530 -0.316 Horsefly 21 -0.498 -0.518 -0.601 -0.725 -0.505 -0.623 Late Nadina 28 -0.616 -0.421 -0.645 -0.744 -0.694 -0.722 Late Stuart 22 -0.493 -0.425 -0.597 -0.687 -0.524 -0.643 Raft 30 -0.513 -0.292 -0.595 -0.561 -0.561 -0.590 Stellako 31 -0.556 -0.287 -0.599 -0.588 -0.635 -0.603 1.2 Females Adams 29 -0.473 -0.299 -0.549 -0.557 -0.581 -0.555 Birkenhead 31 -0.549 -0.338 -0.624 -0.696 -0.761 . -0.669 Chilko 31 -0.402 -0.547 -0.497 -0.725 -0.565 -0.562 Early Stuart 29 -0.428 -0.269 -0.511 -0.468 -0.569 -0.496 Gates 29 -0.569 -0.412 -0.603 -0.660 -0.716 -0.607 Horsefly 22 -0.380 -0.539 -0.515 -0.709 -0.510 -0.547 Late Nadina 28 -0.508 -0.315 -0.524 -0.667 -0.571 -0.625 Late Stuart 22 -0.628 -0.395 -0.728 -0.735 -0.711 -0.752 Raft 30 -0.435 -0.314 -0.511 -0.543 -0.588 -0.500 Stellako 31 -0.451 -0.268 -0.506 -0.541 -0.590 -0.536 43 My results indicate that in all cases where SL is significantly correlated with sockeye abundance I cannot distinguish between effects that occur in the year preceding return (ry-l) from those effects that may occur during the return year (ry). In most cases, I also cannot distinguish between the potential effects that different ocean age categories have on growth of Fraser River sockeye. Peterman (1984) defined the most critical ocean residence periods and age categories for density dependent effects on sockeye as those periods and ages that produced the greatest fraction of significant slopes of SL on Gulf of Alaska sockeye abundance. Although I have shown that this type of approach may suffer from an inability to distinguish among the various periods and age categories, the results may be suggestive. For example, 90% of the maximum age-, stock-, and sex-specific abundance-SL correlations occurred when x.2+ fish were used as an abundance index and 10% occurred with x.3. In addition, 65% of these maximum correlations occurred when abundance data from the year preceding return (ry-l) were used and 35% occurred using the return year data (ry). This is similar to the original findings of Peterman (1984) who suggested that the most critical period for Gulf of Alaska sockeye abundance to cause density-dependent growth effects on age 1.2 British Columbia sockeye was early in the penultimate year (ry-l). The results do not indicate a strong age class interaction with x. 1 as was found by Peterman (1984). However, McKinnell (1995) found no significant relationships between mean length at maturity of age 1.2 Skeena, Nass, and Rivers Inlet sockeye and Bristol Bay sockeye catch. Peterman (1984) suggested that competition among similar sized sockeye may lead to density-dependent reductions in growth. However, I believe that the large volume of food consumed by maturing x.2 and x.3 44 sockeye (McKinnell 1995) is a more plausible mechanism that would explain slower growth of fish of all sizes. The significant cases that I reported for age 1.1 sockeye support this hypothesis. Age 1.1 "jacks" are relatively small during their 13-15 month (1-winter) existence in the ocean compared to x.2 and x.3 fish, yet still they exhibit significant decreases in growth when Gulf of Alaska abundance of x.2 and x.3 fish are high. The results for age 1.1 fish also suggest that variation in marine growth may be more dependent upon state of maturity rather than size. Lander and Tanonaka (1964) examined marine growth of immature and maturing Western Alaskan sockeye that were captured by research vessels operating in the North Pacific Ocean during the period 1956 to 1960. Their results showed little variation in marine growth of immature sockeye taken from broadly separated geographical areas during the same ten day period each year. In contrast, average size of maturing fish differed significantly between areas of capture. Of course, the differences in growth rate shown for maturing fish may also be attributable to stock-specific differences that were not accounted for because the samples were not separated by area of origin. Changes in density-dependent growth relationships I chose to use x.2+ ry-i for the following regression analyses for a number of reasons. First, it was most highly correlated to SL of most stocks. Second, Fraser River sockeye spend the entire penultimate year (ry-1) in the open sea; this would increase the likelihood of interaction with other Gulf of Alaska sockeye stocks (Chapter 1; Cox and Hinch in press). Third, Fraser River sockeye that are destined to mature after two winters at sea are 45 maturing during the latter portion of this period. Finally, growth in length is greatest during the penultimate year (Lander and Tanonaka 1964). Female sockeye from nine stocks and males from five stocks showed significant negative SL-x.2+ry.i relationships during the 1978-1992 period. Differences between sexes in the number of significant relationships could be partly due to the lower power of detecting changes in size at maturity of males compared to females (Cox and Hinch in press; Chapter 1). Significant stock- and sex-specific regressions of SL on x.2+,y.i during this period explained 33-81% and 33-79% of variation in growth of females and males, respectively (Table 2.3; Figure 2.4). In contrast, stock- and sex-specific regression slopes were both positive and negative during the 1958-1975 period and all were non-significant. ANCOVA revealed that, in most cases, relationships between SL and x.2+ry.i were different during the periods 1958-1975 and 1978-1992 (Table 2.3). One could speculate that the large increases in zooplankton biomass during the 1978-1992 period would have offset the coincident increases in salmonid abundance resulting in no net change in growth rate. Instead, strong density-dependent growth during the productive 1980s suggests that sockeye abundance increased at a faster rate than the food supplies required to maintain growth rates. The fact that growth of age 1.2 sockeye was not density-dependent from 1958-1975 contradicts the results of Peterman (1984), although Peterman (1984) used ocean abundance of ages 2 and 3 (total age; corresponds to x.O and x. 1) as explanatory variables. On the other hand, my results support those of McKinnell (1995) who found no 46 relationship between mean length at maturity of age 1.2 Skeena sockeye and Gulf of Alaska abundance during this period. 47 Table 2.3. Comparison of standardized slopes (b'), probabilities that slopes are equal to zero (P b=o), coefficients of determination (r2) and number of years of data (n) for relationships between mean spawning ground length of age 1.2 female and male Fraser River sockeye and abundance of age x.2+ ry.1 Bristol Bay and Fraser River sockeye during the periods 1958-1975 and 1978-1992. The last column gives the probability from ANCOVA that slopes from the two periods are equal (P bi=b2)-1958-1975 1978-1992 Stock b,' P bl=0 r2 n b2' Pb2=0 r2 n Pbl=b2 Females Adams 0.154 0.54 0.02 18 -0.580 0.03 0.35 13 0.04 Birkenhead -0.003 0.99 0.00 18 -0.848 <0.01 0.76 15 <0.01 Chilko 0.342 0.16 0.12 18 -0.784 <0.01 0.41 15 <0.01 Early Stuart 0.217 0.48 0.05 13 -0.672 <0.01 0.43 15 0.02 Gates -0.136 0.63 0.02 15 -0.622 < 0.01 0.45 15 0.20 Horsefly 0.197 0.54 0.04 12 -0.885 <0.01 0.58 11 0.01 Late Nadina 0.420 0.12 0.18 13 -0.623 <0.01 0.44 14 <0.01 Late Stuart 0.220 0.57 0.05 9 -0.975 <0.01 0.81 12 <0.01 Raft 0.346 0.22 0.12 14 -0.793 0.03 0.33 14 0.01 Stellako 0.217 0.38 0.05 18 -1.042 <0.01 0.64 15 <0.01 Males Adams -0.066 0.800 0.00 17 -0.489 0.06 0.31 12 0.26 Birkenhead -0.299 0.240 . 0.09 17 -0.183 0.48 0.04 15 0.77 Chilko 0.208 0.400 0.04 18 -0.898 <0.01 0.55 15 <0.01 Early Stuart 0.247 0.440 0.06 12 -1.045 <0.01 0.79 15 < 0..01 Gates -0.030 0.920 0.00 13 -0.493 0.05 0.27 15 0.42 Horsefly 0.026 0.940 0.00 11 -0.758 0.02 0.47 11 0.14 Late Nadina -0.167 0.570 0.03 14 -0.608 0.01 0.42 15' 0.09 Late Stuart 0.549 0.100 0.30 10 -0.843 <0.01 0.75 11 <0.01 Raft 0.189 0.520 0.04 14 -0.704 0.03 0.33 14 0.04 Stellako 0.051 0.840 0.00 18 -1.117 <0.01 0.62 15 <0.01 48 Figure 2.4. Relationships between mean spawning ground body length of females (abscissa) and abundance of age sockeye (ordinate) in the Gulf of Alaska during 1958-1975 (solid line;closed circles) and 1978-1992 (dashed line; open circles). Regression relationships that were significantly different between periods are shown. See Table 2.3 for regression summary. 49 Figure 2.5. Relationships between mean spawning ground body length of males (abscissa) and abundance of age x.2+ry.i sockeye (ordinate) in the Gulf of Alaska during 1958-1975 (solid line;closed circles) and 1978-1992 (dashed line; open circles). Regression relationships that were significantly different between periods are shown. See Table 2.3 for regression summary. 50 x . 2 + r y - i Sockeye Abundance 50A Detailed mechanistic explanations for the density-dependent growth of sockeye on the high-seas are not possible at this time. However, explanations for sudden changes in density-dependent growth relationships, as I present, are simpler to conjure. In a brief analysis of spatial distribution of British Columbia sockeye salmon stocks, McKinnell (1995) concluded that differences in density-dependent growth relationships among British Columbia sockeye stocks could be attributed to their relative proximity to the centers of abundance of Western Alaska sockeye. Although this would account for differences in density dependent growth relationships among stocks, it does not explain the changes in relationships over time that I observed. The fluctuations in abundance of fish stocks are often associated with expansion and contraction of habitat area occupied by those stocks (MacCall 1990; McConnaughey 1995). If this relationship holds for Bristol Bay sockeye salmon, then the doubling of abundance during the late 1970s and early 1980s most likely caused an increase in their range in the northeast Pacific Ocean. Expansion of habitat occupied by Bristol Bay sockeye into regions commonly occupied by British Columbia fish would lead to an increase in competitive interactions between the two stocks. Increases in area occupied have been observed for Japanese chum (0. ketd) salmon as hatchery populations increased during the 1980s and 1990s (Nagasawa 1992). Therefore, a doubling of the abundance of Bristol Bay sockeye could explain the significant changes in density-dependent growth relationships between the two time periods that I observed 51 The change in density-dependent growth relationships between the two periods that I observed may not be simply due to sockeye salmon abundance alone. Although it appears from a closer examination of Figures 4 and 5 that the density-dependent growth response occurs mainly beyond 100 million age x.2+ sockeye, some of this effect is confounded with oceanographic events that prevailed during the period in which these abundance levels were attained: During the 1980s, when sockeye abundance first approached record levels, the main prey species for sockeye were being advected towards the perimeter of the Gulf of Alaska (Brodeur and Ware 1992; Hinch unpubl. data), presumably in response to intensification of the gyre upwelling system. This advection is believed to be partly responsible for the increases in juvenile salmon survival observed during that period (Beamish and Bouillon 1993). The redistribution of prey away from the center of the gyre may have caused lower effective prey densities in offshore areas where maturing sockeye are believed to exist. This effect, combined with higher sea surface temperatures, increases in pink and chum salmon abundance and an expanding range of the dominant sockeye stocks probably all contributed to the severe drop in size at maturity of Fraser River sockeye during the late 1980s and early 1990s. Conclusions My results indicate that sockeye salmon have become abundant enough in recent decades to cause strong density-dependent reductions in growth of Fraser River sockeye. The record small sizes of Fraser River sockeye that occurred during the early 1990s (Chapter 1; Cox and Hinch in press) could have resulted from a combination of high Gulf of Alaska sockeye abundance and a shift back to a period of low biological productivity (Polovina et 52 al 1994).This evidence suggests that marine growth may be even more drastically reduced if abundance is artificially maintained at high levels during periods of low productivity. References Beamish, R.J., and Bouillon, DR. 1993. Pacific salmon production trends in relation to climate. Can. J. Fish. Aquat. Sci. 50: 1002-1016. Bigler, B.S., Welch, D.W., and Helle, J.H. 1996. A review of size trends among north Pacific salmon (Oncorhynchus spp). Can. J. Fish. Aquat. Sci. 53:455-465. Bilton, H. T. and Ludwig, S. A. M . 1966. Times of annulus formation on scales of sockeye, pink, and chum salmon in the Gulf of Alaska. J. Fish. Res. Board Canada. 23: 1403-1410. Boer, G.J., McFarlane, N.A., and Lazare, M. 1992. Greenhouse gas-induced climate change simulated with the CCC second generation general circulation model. J. Clim. 5: 1045-1077. Bradford, M . J. 1995. Comparative review of Pacific salmon survival rates. Can. J. Fish. Aquat. Sci. 52: 1327-1338. Brodeur, R. D., and Ware, D. M. 1992. Long-term variability in zooplankton biomass in the subarctic Pacific Ocean. Fish. Oceanogr. 1(1): 32-38. 53 Brodeur, R. D., and Ware, D. M . 1995. Interdecadal variability in distribution and catch rates of epipelagic nekton in the Northeast Pacific Ocean. In: Climate change and northern fish populations. Edited by R.J. Beamish. Can. Spec. Publ. Fish. Aquat. Sci. 121. pp. 329-356. Cox, S. P., and Hinch, S. G. (in press). Changes in size at maturity of Fraser River sockeye salmon (1952-1993) and associations with temperature. Can. J. Fish. Aquat. Sci. Eggers, D. M. , Meacham, C. P., and Huttunen, D. C. 1984. Population dynamics of Bristol Bay sockeye salmon, 1956-1983, pp.200-225. In: The influence of ocean conditions on the production of salmonids in the North Pacific. Edited by W. G. Pearcy. Oregon State University., Corvallis, OR 97331, 3327 p. French, R., Bilton, H , Osako, M. , and Hartt, A. 1976. Distribution and origin of sockeye salmon in offshore waters of the North Pacific ocean. International North Pacific Fisheries Commission Bull. 34: 113 pp. Fry, F. E. J. 1949. Statistics of a lake trout fishery. Biometrics 5. 27-67. Hartt, A. C. 1966. Migrations of salmon in the North Pacific Ocean and Bering Sea as determined by seining and tagging, 1959-1960. International North Pacific Fisheries Commission Bull. 19: 141 pp. 54 Helle, J.H., and Hoffman, M.S. 1995. Size decline and older age at maturity of two chum salmon (Oncorhynchus keta) stocks in western North America. In. Climate change and northern fish populations. Edited by R.J. Beamish. Can. Spec. Publ. Fish. Aquat. Sci. 121. pp. 245-260. Henderson, M.A., and Cass, A.J. 1991. Effect of smolt size on smolt-adult survival for Chilko Lake sockeye salmon (Oncorhynchus nerka). Can. J. Fish. Aquat. Sci. 48: 988-994. Hourston, R A . 1992. Variability of North Pacific Ocean surface sensible and latent heat fluxes. M.Sc. Thesis, University of British Columbia, Vancouver, B.C. Howard, G. V. and Chapman, D. G. 1948. Problems in the enumeration of populations of spawning sockeye salmon. International Pacific Salmon Fisheries Commission Bull. II: 88 pp. Ignell, S. E. and Murphy, J. M . 1993. Salmonid spatial patterns near the North Pacific Subarctic Frontal Zone. International North Pacific Fisheries Commission Bull. 53(11): p. 253. Ishida, Y., Ito, S., McKinnell, S., and Nagasawa, K. 1993. Recent changes in age and size of chum salmon (Oncorhynchus keta) in the North Pacific Ocean and possible causes. Can. J. Fish. Aquat. Sci. 50: 290-295. 55 Killick, SR. and Clemens, W.A. 1963. The age, sex ratio and size of Fraser River sockeye salmon, 1915 to 1960. International Pacific Salmon Fisheries Commission Bull. XIV: 140p. Lander, R. H. and Tanonaka, G. K. 1966. Marine growth of Western Alaskan sockeye salmon (Oncorhynchus nerka Walbaum). International North Pacific Fisheries Commission. Bull., 14. pp. 1-31. MacCall, A D . 1990. Dynamic geography of marine fish populations. University of Washington Press. Seattle, WA. 153 pp. McConnaughey, R A . 1995. Changes in geographic dispersion of eastern Bering Sea flatfishes associated with changes in population size. Proceedings of the International Symposium on north Pacific Flatfish. Alaska Sea Grant College Program. AK-SG-95-04. McKinnell, S. 1995. Age-specific effects of sockeye abundance on adult body size of selected British Columbia sockeye stocks. Can. J. Fish. Aquat. Sci. 52: 1050-1063. Nagasawa, K. 1992. Future salmon research by the National Research Institute of Far Seas Fisheries. In: Proceedings of the International Workshop on Salmon Research in the North Pacific Ocean. Edited by Y. Ishida, K. Nagasawa, D.W. Welch, K. W. Myers, and A.P. Shershnev. National Research Institute of Far Seas Fisheries, Shimizu, Japan, pp. 63-66. 56 Namias, J., Yuan, X. , and Cayan, D.R. 1988. Persistence of North Pacific sea surface temperature and atmospheric flow patterns. J. Clim. 1: 682-703. Peterman, R. M.1981. Form of random variation in smolt-to-adult relations and its influence on production estimates. Can. J. Fish. Aquat. Sci. 38: 1113-1119. Peterman, R. M . 1984. Density-dependent growth in early ocean life of sockeye salmon (Oncorhynchus nerka). Can. J. Fish. Aquat. Sci. 41: 1825-1829. Peterman, R. M . and Wong, F. Y. C. 1984. Cross correlations between reconstructed ocean abundances of Bristol Bay and British Columbia sockeye salmon. Can. J. Fish. Aquat. Sci. 41: 1814-1824. Polovina, J. J., Mitchum, G. T., Graham, N. E., Craig, M . P., Demartini, E. E. and Flint, E. N . 1994. Physical and biological consequences of a climate event in the central North Pacific. Fish. Oceanogr. 3:15-21. Ricker, W. E. 1962. Comparison of ocean growth and mortality of sockeye salmon during their last two years. J. Fish. Res. Board Canada. 19: 531-577. Rogers, D. E. 1980. Density-dependent growth of Bristol Bay sockeye salmon, pp. 267-283. In: Salmonid ecosystems of the North Pacific. Edited by W. J. McNeil and D. C. Himsworth. Oregon State University Press, Corvallis, OR. 57 SAS Institute. 1988. SAS/STAT Users Guide, version 6.03. SAS Institute, Cary, North Carolina. Ware D. M. , and McFarlane, G. A. 1989. Fisheries production domains in the Northeast Pacific Ocean. In: Effects of ocean variability on recruitment and an evaluation of parameters used in stock assessment models. Edited by R.J. Beamish and G. A. McFarlane. Can. Spec. Publ. Fish. Aquat. Sci. 108: pp. 359. Welch, D.W., Chigirinsky, A.L, and Ishida, Y. 1995. Upper thermal limits on the oceanic distribution of Pacific salmon (Oncorhynchus spp.) in the spring. Can. J. Fish. Aquat. Sci. 52: 489-503. Woodey, J.C. 1987. In-season management of Fraser River sockeye salmon (Oncorhynchus nerka): meeting multiple objectives. In: Sockeye salmon (Oncorhynchus nerka) population biology and future management. Edited by H.D. Smith, L. Margolis, and C C . Wood. Can. Spec. Publ. Fish. Aquat. Sci. 96: pp. 367-374. Woodruff, S.D., Slutz, R.J., Leane, R.L., and Steurer, P.M. 1987. A comprehensive ocean-atmosphere dataset. Bull. Am. Meterol. Soc. 68: 1239-1250. Zar, J.H. 1984. Biostatistical Analysis. 2nd ed. Simon & Schuster Co., Englewood Cliffs, NJ. 58 Chapter 3 Density-dependent marine growth of Early Stuart sockeye salmon: evidence for a critical period Chapter Abstract Critical periods for density dependent marine growth have not been clearly identified for Fraser River sockeye salmon. Using annual marine scale growth and age-specific estimates of sockeye salmon abundance from 1954-1991,1 show that Early Stuart sockeye salmon marine growth is negatively correlated to abundance during the penultimate year at sea. However, the correlations are only significant during the past fifteen years (1978-1991) compared to the earlier period 1954-1975. This suggests that critical periods for density dependent growth occur during the time, when Early Stuart sockeye salmon are present in the Central Gulf of Alaska. 59 Introduction Improvements in wild stock management and beneficial ocean conditions have resulted in dramatic increases in the abundance of many sockeye salmon (Oncorhynchus spp.) populations in recent years (Eggers et al. 1984; Beamish and Bouillon 1993). These increases are believed to be the major factor responsible for the significant declines in size at maturity of most Fraser River sockeye salmon stocks (Chapter 1 and 2; Cox and Hinch in press). Although it seems clear that marine growth is related to population size in the ocean (Rogers 1980; Peterman 1984; McKinnell 1995; Chapter 2), the timing of competitive interactions, sometimes refered to as critical periods, between stocks and age classes of sockeye from British Columbia and Alaska remains uncertain (Chapter 2). The search for critical periods for marine growth of sockeye salmon has been of interest to biologists for many years (Killick and Clemens 1963). More recent studies of density dependent marine growth of Pacific salmon (Oncorhynchus spp.) continue to offer some speculation on the potential timing of competitve interactions (Rogers 1980; Peterman 1984; Ishida et al 1993; McKinnell 1995; Chapter 2). However, few studies relate salmon abundance to direct estimates of annual marine growth (Ogura 1991; Ishida et al 1993; McKinnell 1995). In most cases, size at maturity and abundance data are simply lined up to represent different hypotheses about the timing of competitive interactions (Rogers 1980; Peterman 1984; McKinnell 1995; Chapter 2). Lagging data in this way often results in low power of detecting differences among the various hypotheses due to the large number of comparisons that are required (see Chapter 2). 60 British Columbia sockeye salmon typically spend 24-27 months (age 1.2; two winters) or 36-39 months (age 1.3; three winters) foraging in the Gulf of Alaska. The total body size increment achieved by an individual salmon from the time it enters the ocean as a juvenile until the time it re-enters freshwater as an adult, and thus stops growing, is referred to as total marine growth. It may be subdivided into individual marine growth phases that are assumed to each vary in response to changing physical and biological oceanographic conditions. My objective in this chapter is to determine if specific marine growth phases tend to vary in response to changing levels of sockeye salmon abundance in the Gulf of Alaska. I base my analyses on an up to date time series of sockeye abundance in the Gulf of Alaska and annual marine scale growth increments from age 1.2 Early Stuart sockeye. Methods Marine Growth Data Information on the amount of growth attained in each marine growth phase is obtained from returning adult fish by measuring the distance between successive ocean annuli on the scales. Each ocean annulus begins to form sometime in November or December and is completed by January (Bilton and Ludwig 1966). For age 1.2 fish that enter the ocean in May-June this leaves seven to eight months (June-December) of scale growth in the first marine growth stage (Ml), approximately eleven months for the second phase (M2), and five to seven months for the final marine growth phase (M3) (Bilton and Ludwig 1966). 61 Average annual marine scale growth increments from the Early Stuart (1954-1991) stock were estimated to the nearest micron from figures found in Welch (1994). Scale measurements for each marine growth zone (Ml , M2, and M3) are assumed to be proportional to growth in either body length or body weight during that period. Sockeye Abundance Minimum age-specific ocean abundances of sockeye salmon for the period 1954-1991 inclusive, were calculated by applying virtual population analysis to catch and escapement data from Bristol Bay and Fraser River sockeye salmon stocks (Chapter 2). These two stock complexes make up a significant proportion (>50%) of sockeye salmon found in the Gulf of Alaska (Peterman 1984). Statistical Analysis I used correlation analyses to detect the presence of critical periods for density-dependent marine growth of age 1.2 Early Stuart sockeye. Each time series of marine scale growth was correlated with time series of minimum ocean abundance of age x. 1 and x.2+ sockeye in the Gulf of Alaska. The x. 1 and x.2+ age categories represent immature (x. 1) and maturing (x.2+) components of the sockeye population in the Gulf of Alaska. Because there were two comparisons for each time series of marine growth, Bonferroni adjustments were used to control the comparisonwise error rate. 62 Results and Discussion Scale growth during each marine growth phase of Early Stuart sockeye salmon flucuated without trend from 1954-1991 (Figure 3.1). Growth during the first marine year (Ml), which is spent largely within the continental shelf region, slowed for a period of five successive years from 1979-1983. This period follows the well documented climatological shift in the dominant weather system over the northeast Pacific Ocean (Namais et al 1988). The subsequent intensification of gyre upwelling and circulation is believed to have resulted in advection of standing crops of zooplankton toward the perimeter of the Gulf of Alaska (Brodeur and Ware 1992; Hinch unpubl. data) where juvenile sockeye may be found during their first year in the ocean (Hart and Dell 1986). The fact that growth was actually slower during this time suggests that either the zooplankton species preferred by juvenile sockeye were not advected onto the continental shelf region, or conditions were simply not optimal for taking advantage of increased food concentrations. 63 Figure 3.1. Marine growth of age 1.2 Early Stuart sockeye salmon over the years 1954-1991, inclusive for ocean entry year (Ml), penultimate year (M2), and return year (M3). Growth stages of a single cohort may be found by subtracting one from the return year for M2 and subtracting two for M l . For example, growth for the cohort returning in 1990 may be found under 1990 (M3), 1989 (M2), and 1988 (Ml). 64 Marine growth during the second year at sea (M2), which is spent in the offshore waters of the Gulf of Alaska, also showed no long-term trend. However, aside from the single high growth rate year in 1986, M2 growth decreased from 1976 to 1991. Slower growth during the period spent in the Central Gulf of Alaska coincides with a period of higher biological productivity in the northeast Pacific Ocean (Brodeur and Ware 1995; Chapter 2). This suggests that effective prey densities were not, in fact high, possibly due to either c. advection of zooplankton toward the coast, increased predator/prey ratios due to increases in sockeye salmon abundance, or a combination of the two (Chapter 2). Early Stuart marine scale growth was only correlated with sockeye abundance during the second ocean year (M2; Table 3.1), however the relationship is not statistically significant at the adjusted probability level (P > 0.025). If the relationships are examined by time periods 1954-1975 and 1978-1991 (e.g. Chapter 2), representing low ocean productivity-low salmon abundance and high ocean productivity-high salmon abundance, respectively, then Early Stuart M2 scale growth during the period 1978-1991 is significantly correlated to x.2+ sockeye abundance (r = -0.662, P < 0.025, n = 15) (Figure 3.2). In Chapter 2 I found that ocean abundance of sockeye during the second ocean year (M2) over the period 1978-1992 explained 79% and 43% of the variability in length at maturity of age 1.2 Early Stuart males and females, respectively. Previous attempts to identify critical periods for density dependent growth of sockeye salmon have been limited by our inability to relate annual marine growth to annual estimates of sockeye abundance in the Gulf of Alaska. Using annual growth information 65 obtained from scales, I have shown that the second ocean year (M2) is the most likely critical period for density-dependent growth of age 1.2 Early Stuart sockeye salmon. This supports the conclusions of Chapter 2, where I proceeded under the assumption that density dependent effects occurred during the penultimate year at sea. 66 Table 3.1. Age-specific correlations between marine growth estimated from scales (Mx) and age-specific ocean abundance of sockeye. Probabilities and number of data points are included below each r value. All probabilities are controlled for comparisonwise error rate (CER) by dividing a = 0.05 by the number of comparisons for each stock/age group. The CER = (.05/2) = 0.025 in all cases. Significant correlation coefficients appear in bold type. Data obtained from 1954 -1991, inclusive. X.1 x.2+ Early Stuart 1.2 M1 M2 M3 •0.195 •0.130 0.470 33 0.063 0.726 33 284 32 •0.033 0.858 32 •0.347 0.048 33 •0.083 0.645 33 67 Figure 3.2. Relationships between second year marine growth (M2) of Early Stuart sockeye (sexes combined) and minimum abundance of age x.2+ sockeye in the Gulf of Alaska during the period 1954-1975 (open circles;solid line) and 1978-1991 (closed circles; dashed line). 68 3.10 r o c 3.00 • </) 2.85 2.80 1 •- ' — ' • ' ^ ' 1 — ' : 1 0 20 40 . 60 80 100 120 140 160 x.2 + Sockeye Abundance (millions) 68a References Beamish, R.J., and Bouillon D.R. 1993. Pacific salmon production trends in relation to climate. Can. J. Fish. Aquat. Sci. 50: 1002-1016. Bilton, H. T. and Ludwig, S. A. M . 1966. Times of annulus formation on scales of sockeye, pink, and chum salmon in the Gulf of Alaska. J. Fish. Res. Board Canada. 23: 1403-1410. Brodeur, R. D., and Ware, D. M . 1992. Long-term variability in zooplankton biomass in the subarctic Pacific Ocean. Fish. Oceanogr. 1(1): 32-38. Brodeur, R. D., and Ware, D. M . 1995. Interdecadal variability in distribution and catch rates of epipelagic nekton in the Northeast Pacific Ocean. In: Climate change and northern fish populations. Edited by R.J. Beamish. Can. Spec. Publ. Fish. Aquat. Sci. 121. pp. 329-356. Cox, S. P., and Hinch, S. G. (in press). Changes in size at maturity of Fraser River sockeye salmon (1952-1993) and associations with temperature. Can. J. Fish. Aquat. Sci. Eggers, D. M. , Meacham, C. P., and Huttunen, D. C. 1984. Population dynamics of Bristol Bay sockeye salmon, 1956-1983, pp.200-225. In: The influence of ocean conditions on the production of salmqnids in the North Pacific. Edited by W. G. Pearcy. Oregon State University., Corvallis, OR 97331, 3327 p. 69 Hartt, A. C , and Dell, M . B. 1986. Early oceanic migrations and growth of juvenile Pacific salmon and steelhead trout. International North Pacific Fisheries Commission Bull. 46: 105 pp. Ishida, Y., Ito, S., McKinnell, S., and Nagasawa, K. 1993. Recent changes in age and size of chum salmon (Oncorhynchus keta) in the North Pacific Ocean and possible causes. Can. J. Fish. Aquat. Sci. 50: 290-295. Killick, S.R. and Clemens, W.A. 1963. The age, sex ratio and size of Fraser River sockeye salmon, 1915 to 1960. International Pacific Salmon Fisheries Commission Bull. XIV: 140p. McKinnell, S. 1995. Age-specific effects of sockeye abundance on adult body size of selected British Columbia sockeye stocks. Can. J. Fish. Aquat. Sci. 52: 1050-1063. Namias, J., Yuan, X., and Cayan, D.R. 1988. Persistence of North Pacific sea surface temperature and atmospheric flow patterns. J. Clim. 1: 682-703. Ogura, M. , Y. Ishida, and S. Ito. 1991. Growth variation of coho salmon Oncorhynchus kisutch in the Western North Pacific. Nippon Suisan Gakkaishi 57(6): 1089-1093 Peterman, R. M . 1984. Density-dependent growth in early ocean life of sockeye salmon (Oncorhynchus nerka). Can. J. Fish. Aquat. Sci. 41: 1825-1829. 70 Rogers, D. E. 1980. Density-dependent growth of Bristol Bay sockeye salmon, pp. 267-283. In: Salmonid ecosystems of the North Pacific. Edited by W. J. McNeil and D. C. liimsworth. Oregon State University Press, Corvallis, OR. Welch, D.W. 1994. Variation in marine growth rates of British Columbia pink and sockeye salmon stocks. (NPAFC Doc. 94) 30 p. Dept. of Fisheries and Oceans, Biological Sciences Branch, Pacific Biological Station, Nanaimo, B.C. Canada. V9R 5K6 71 CONCLUSIONS Using data from several sockeye salmon stocks I have demonstrated that size at maturity has declined substantially over the past twenty years apparently in response to changing biotic and abiotic oceanographic conditions. During this time, these two factors appear to affect marine growth on different temporal and spatial scales. In general, physical oceanographic factors, such as temperature are associated with changes in size at maturity across many stocks during both the 1960s-1970s and 1980s-1990s climatic regimes; suggesting both large spatial (e.g: gyre) and temporal scale effects. Biotic processes, such as competitive interactions among sockeye salmon are more strongly associated with interannual variation in size at maturity, however these associations are restricted to relatively fewer stocks and predominate during the 1980-1990 climatic regime; indicating smaller spatial and temporal scale effects. Therefore, both large and small spatial and temporal scale phenomena appear to affect the marine growth of Fraser River sockeye salmon. -Potential effects of climate change: sockeye salmon may be in hot water Current trends suggest that the northeast Pacific Ocean has been warming over the past decade; however, it remains uncertain whether the trend is due to global climate warming or a reversal of a regional cooling period which began in the late 1950s (Zebdi and Collie 1995). Realizing the appropriate scales of biotic and abiotic effects represents a positive step toward understanding the potential effects of global climate warming on the marine growth of sockeye salmon. For example, an increase in northeast Pacific Ocean sea surface 72 growth of most sockeye stocks if salmon abundance is low. If the same situation occurred, but salmon abundance remained at or near present levels, perhaps due to enhancement or increased survival, major declines in size at maturity are likely to result due to the combined effects of high temperature, high abundance, and possibly a reduction in the standing crop of prey (Hinch et al 1995). Large decreases in size at maturity may result in punctuated changes to the population dynamics of sockeye salmon. Decreases in body weight of mature fish will reduce egg production and the ability to migrate upstream and spawn (Healey 1986). To compensate, sockeye salmon may need to remain at sea for an additional year in order to aquire the size and energy reserves necessary to minimize pre-spawning mortality (Peterman 1985; Mangel 1994). However, this would reduce population productivity due to an increase in generation time (Forbes and Peterman 1994). Welch (1994) showed that an additional year at sea would result in a 20% decrease in productivity for populations that primarily mature at age 1.2. Increases in average age at maturity associated with increases in SST have been observed in other salmon species, but not sockeye (Ogura et al. 1991; Helle and Hoffman 1995). If salmon abundance were to decrease during extended periods of warming, then growth reductions may be less obvious because constraints imposed by density dependent growth processes could be alleviated. Even if abundance decreases, large changes in ocean temperature and circulation could result in a re-distribution of sockeye stocks in the northeast Pacific Ocean and, combined with a reduction in thermal habitat, may result in higher sockeye densities. Although it does not appear to be a critical factor in regulating competitive interactions at the present time, thermal habitat area could become very important if it is reduced to critical levels in the future. If the changes to climate are abrupt then sockeye salmon may not have the 73 capacity, nor the time, to compensate by altering their life history strategies and migrations. Existing along the southernmost portion of the species range, Fraser River sockeye may also be vulnerable to anthropogenic impacts of climate change such as an increased need for irrigation and hydropower, as well as a possible redistribution of the human population to more inland areas where the major Fraser River sockeye populations are found. Regardless of climate change, communities in the interior of British Columbia will continue to grow in response to tourism and natural resource opportunities, as well as human population growth. Therefore, it is not improbable that the present priority to preserve salmon stocks will dwindle in response to increasing natural resource exploitation and development in the future. References Boer, G.J., McFarlane, N.A., and Lazare, M. 1992. Greenhouse gas-induced climate change simulated with the CCC second generation general circulation model. J. Clim. 5: 1045-1077. Forbes, L.S., and Peterman, R.M. 1994. Simple size-structured models of recruitment and harvest in Pacific salmon (Oncorhynchus spp.). Can. J. Fish. Aquat. Sci. 51: 603-616. 74 Healey, M.C. 1986. Optimum Size and Age at Maturity in Pacific Salmon and Effects of Size-Selective Fisheries. In. Salmonid age at maturity. Edited by D.J. Meerburg. Can. Spec. Publ. Fish. Aquat. Sci. 89: pp. 39-52. Helle, J.H., and Hoffman, M.S. 1995. Size decline and older age at maturity of two chum salmon (Oncorhynchus keta) stocks in western North America. In: Climate change and northern fish populations. Edited by R.J. Beamish. Can. Spec. Publ. Fish. Aquat. Sci. 121. pp. 245-260. Hinch, S.G., Healey, M . C , Diewert, R.E., Thomson, K.A., Hourston, R., Henderson, M.A., and Juanes, F. 1995. Potential effects of climate change on marine growth and survival of Fraser River sockeye. Can. J. Fish. Aquat. Sci. 52: 2651-2659. Mangel, M . 1994. Climate change and salmonid life history variation. Deep-Sea Res. II 41(1): 75-106. Ogura, M. , Ishida, Y., and Ito, S. 1991. Growth variation of coho salmon Oncorhynchus kisutch in the Western North Pacific. Nippon Suisan Gakkaishi 57: 1089-1093. Peterman, R.M. 1985. Patterns of interannual variation in age at maturity of sockeye salmon (Oncorhynchus nerka) in Alaska and British Columbia. Can. J. Fish. Aquat. Sci. 42: 1595-1607. 75 Welch, D.W. 1994. Variation in marine growth rates of British Columbia pink and sockeye salmon stocks. (NPAFC Doc. 94) 30 p. Dept. of Fisheries and Oceans, Biological Sciences Branch, Pacific Biological Station, Nanaimo, B.C. Canada. V9R 5K6 Zebdi, A., and Collie, J.S. 1995. Effect of climate on herring (Clupeapallasi) population dynamics in the Northeast Pacific Ocean. In. Climate change and northern fish populations. Edited by R.J. Beamish.Can. Spec. Publ. Fish. Aquat. Sci. 121. pp. 277-290. 76 Appendix 1. Reconstructed ocean abundance of Fraser River, British Columbia sockeye salmon totaled over ten major stocks (Chapter 2; Methods; Sockeye Abundance Data). Y e a r x.1 x.2 x.3 x .2+ x .3+ T o t a l 1 9 5 4 2 3 5 8 4 9 4 2 1 4 6 0 2 0 1 0 8 6 0 0 7 0 1 3 0 0 6 0 9 0 1 5 3 6 4 5 8 4 1 9 5 5 3 7 5 8 7 4 4 2 3 5 8 4 9 4 2 1 0 3 6 0 1 4 4 6 2 0 9 5 8 2 2 0 8 3 9 1 9 5 6 1 8 1 2 1 2 7 5 3 7 5 8 7 4 4 2 3 2 3 2 3 4 6 0 8 1 9 7 8 2 4 2 0 3 2 5 3 1 9 5 7 3 3 7 3 5 1 5 1 8 1 2 1 2 7 5 3 7 4 0 6 9 4 2 1 8 6 1 9 6 9 2 5 2 3 5 4 8 4 1 9 5 8 3 1 3 7 4 1 4 3 3 7 3 5 1 5 1 7 3 7 8 7 1 8 2 0 7 5 2 2 3 3 2 3 8 8 9 6 4 7 1 9 5 9 3 9 8 6 7 4 3 3 1 3 7 4 1 4 3 2 9 4 7 9 8 6 4 3 2 2 1 2 1 0 4 1 8 9 5 5 1 9 6 0 3 0 5 8 7 1 2 3 9 8 6 7 4 3 3 1 0 1 7 9 2 7 0 8 8 5 3 5 1 0 1 4 7 2 4 7 1 9 6 1 3 3 7 3 0 9 8 3 0 5 8 7 1 2 3 9 7 2 6 5 2 7 0 3 1 3 6 4 1 0 4 0 4 4 6 2 1 9 6 2 1 4 8 3 4 8 5 3 3 7 3 0 9 8 2 9 1 2 3 5 0 6 2 8 5 4 4 8 7 7 6 8 9 3 3 1 9 6 3 2 7 1 3 9 9 7 1 4 8 3 4 8 5 3 3 1 4 3 4 8 4 7 9 7 8 3 3 7 5 1 1 8 3 0 1 9 6 4 4 6 3 3 9 6 3 2 7 1 3 9 9 7 1 4 4 7 8 9 6 4 1 6 1 8 9 3 8 7 9 5 8 5 6 1 9 6 5 5 6 0 1 7 2 8 4 6 3 3 9 6 3 2 6 4 5 2 9 4 7 2 7 9 2 5 7 1 2 8 8 0 9 8 5 1 9 6 6 2 6 3 6 6 7 7 5 6 0 1 7 2 8 4 5 1 1 8 6 3 1 0 1 1 3 5 9 1 1 2 7 5 0 2 6 8 1 9 6 7 3 8 3 9 5 6 6 2 6 3 6 6 7 7 5 3 8 7 6 3 9 8 0 2 4 3 1 6 1 1 8 6 3 8 8 2 1 9 6 8 5 5 9 0 0 5 1 3 8 3 9 5 6 6 2 5 8 1 6 3 1 6 4 2 1 1 9 7 1 2 0 1 1 2 4 8 1 9 6 9 6 6 4 7 4 8 3 5 5 9 0 0 5 1 3 7 9 0 8 4 2 9 3 8 0 8 9 3 1 6 0 2 8 3 7 6 1 9 7 0 3 1 0 4 7 0 4 6 6 4 7 4 8 3 5 4 0 8 3 4 7 1 2 0 5 5 8 3 0 1 5 1 6 0 5 3 4 1 9 7 1 6 0 3 4 6 0 8 3 1 0 4 7 0 4 6 4 9 6 4 6 9 9 6 0 1 1 7 3 1 5 6 3 5 7 8 1 1 9 7 2 6 9 9 4 9 4 2 6 0 3 4 6 0 8 3 0 3 2 1 1 5 9 0 6 6 7 2 3 1 6 0 6 1 6 6 5 1 9 7 3 2 7 1 2 8 6 8 6 9 9 4 9 4 2 5 9 4 3 3 9 1 1 2 9 3 8 3 3 3 1 5 6 5 1 2 0 1 1 9 7 4 3 4 7 5 1 0 2 2 7 1 2 8 6 8 6 7 0 0 7 6 0 9 4 1 3 6 2 8 1 2 8 8 8 7 3 0 1 9 7 5 4 6 8 8 8 0 2 3 4 7 5 1 0 2 2 5 9 8 4 2 7 6 0 7 3 5 2 9 1 0 7 6 2 3 3 1 1 9 7 6 8 3 3 4 5 5 9 4 6 8 8 8 0 2 3 3 8 6 7 3 8 8 0 7 5 5 4 0 1 6 4 1 0 0 9 9 1 9 7 7 5 0 4 0 1 4 9 8 3 3 4 5 5 9 4 6 2 3 4 5 8 1 2 9 5 8 0 1 7 1 7 9 9 8 1 6 6 1 9 7 8 2 6 0 4 7 2 6 5 0 4 0 1 4 9 8 1 2 9 1 0 9 1 3 1 6 9 2 5 8 1 1 5 7 7 3 9 8 4 1 9 7 9 6 7 4 3 7 9 6 2 6 0 4 7 2 6 5 0 0 7 2 0 7 7 6 1 1 9 3 3 1 4 3 5 5 7 2 9 1 9 8 0 1 0 5 6 7 1 2 2 6 7 4 3 7 9 6 2 5 5 1 8 2 8 9 2 9 5 6 2 4 1 9 8 6 2 7 4 6 1 9 8 1 4 2 7 6 1 8 5 1 0 5 6 7 1 2 2 6 7 1 5 0 5 2 1 7 2 8 2 1 7 4 2 1 5 5 8 3 5 9 1 9 8 2 5 1 5 9 3 3 0 4 2 7 6 1 8 5 1 0 4 0 5 1 3 0 1 4 6 8 1 3 1 5 1 9 8 4 0 6 4 5 1 9 8 3 1 1 5 3 6 8 3 8 5 1 5 9 3 3 0 4 2 4 6 9 5 9 9 4 0 6 2 8 9 2 0 9 4 3 1 2 7 1 9 8 4 1 0 8 9 3 5 8 8 1 1 5 3 6 8 3 8 5 1 3 6 1 2 0 1 6 6 7 2 9 5 8 2 7 5 6 6 5 4 6 1 9 8 5 5 8 0 8 9 1 9 1 0 8 9 3 5 8 8 1 1 5 1 0 9 4 0 2 2 4 0 4 5 2 8 2 8 2 1 3 4 4 7 1 9 8 6 1 9 9 6 7 6 9 5 8 0 8 9 1 9 1 0 7 2 5 4 8 0 1 6 5 3 4 3 9 9 1 8 5 3 1 1 6 8 1 9 8 7 1 6 6 0 8 4 5 8 1 9 9 6 7 6 9 5 7 2 8 5 5 6 7 7 2 5 3 2 5 2 4 3 3 3 7 8 3 1 9 8 8 1 6 4 8 2 5 0 3 1 6 6 0 8 4 5 8 1 9 8 4 0 6 1 1 8 5 9 2 5 1 9 3 5 0 7 5 0 2 2 1 9 8 9 9 6 9 2 2 3 3 1 6 4 8 2 5 0 3 1 6 5 5 3 1 8 0 3 3 0 3 5 6 8 3 4 2 7 2 7 9 1 6 1 9 9 0 4 6 7 9 2 0 0 9 6 9 2 2 3 3 1 6 3 9 1 6 3 7 2 6 0 8 3 8 7 0 3 0 7 6 3 0 7 0 1 9 9 1 7 0 3 9 9 4 6 7 9 2 0 0 9 6 5 9 7 0 4 1 4 3 3 8 9 0 4 1 4 4 0 9 3 0 3 77 Appendix 2. Reconstructed ocean abundance of Bristol Bay, Alaska sockeye salmon totaled over eight major stocks (Chapter 2; Methods; Sockeye AbundanceData). J Year x.1 x.2 x.3 x.2+ x.3+ Total 1954 12885449 74239 74239 12959688 1955 5576760 12885449 74239 12959688 74239 18536448 1956 3074815 5576760 12885449 18536448 12959688 21611263 1957 11348124 3074815 5576760 21283689 18208874 32631813 1958 50861056 11348124 3074815 16164706 4816582 67025762 1959 11624800 50861056 11348124 63551782 12690726 75176582 1960 11036399 11624800 50861056 67084882 55460082 78121281 1961 6574750 11036399 11624800 38613010 27576611 45187760 1962 13693680 6574750 11036399 21137058 14562308 34830738 1963 69784161 13693680 6574750 23334849 9641169 93119010 1964 8516429 69784161 13693680 85761347 15977186 94277776 1965 10562044 8516429 69784161 83394548 74878119 93956592 1966 9348154 10562044 8516429 33746542 23184498 43094696 1967 21431007 9348154 10562044 23590148 14241994 45021155 1968 50703621 21431007 9348154 33801824 12370817 84505445 1969 10731216 50703621 21431007 75624061 24920440 86355277 1970 5786658 10731216 50703621 65382861 54651645 71169519 1971 2782444 5786658 10731216 27218783 21432125 30001227 1972 14052785 2782444 5786658 12313070 9530626 26365855 1973 22863876 14052785 2782444 19318913 5266128 42182789 1974 12216522 22863876 14052785 39140056 16276180 51356578 1975 11148168 12216522 22863876 40200634 27984112 51348802 1976 19461300 11148168 12216522 27035451 15887283 46496751 1977 44058693 19461300 11148168 35466326 16005026 79525019 1978 65284516 44058693 19461300 69965779 25907086 135250295 1979 32265551 65284516 44058693 116612192 51327676 148877743 1980 12872166 32265551 65284516 109339337 77073786 122211503 1981 50097683 12872166 32265551 61712762 48840596 111810445 1982 45063156 50097683 12872166 78694752 28597069 123757908 1983 33886331 45063156 50097683 102190719 57127563 136077050 1984 19538582 33886331 45063156 90350966 56464635 109889548 1985 29130175 19538582 33886331 68957036 49418454 98087211 1986 21290496 29130175 19538582 60579470 31449295 81869966 1987 52734737 21290496 29130175 59955929 38665433 112690666 1988 51507473 52734737 21290496 86207787 33473050 137715260 1989 39772529 51507473 52734737 115182222 63674749 154954751 1990 48133836 39772529 51507473 110752357 70979828 158886193 1991 41671245 48133836 39772529 112344431 64210595 154015676 1992 33098800 41671245 48133836 112515097 70843852 145613897 78 Appendix 3. Minimum ocean abundance of sockeye salmon totaled over Fraser River and Bristol Bay stocks. Year x.1 x.2 x.3 x.2+ x.3+ Total 1954 15243943 2220259 10860070 13080329 28324272 1955 9335504 15243943 2177840 17421783 74239 26757287 1956 21196090 9335504 15208683 24618426 12959688 45814516 1957 14721639 21196090 9317454 43145658 18208874 57867297 1958 53998470 14721639 20453533 36916939 4816582 90915409 1959 15611543 53998470 14642922 69983994 12690726 85595537 1960 14095111 15611543 53962848 74173417 55460082 88268528 1961 9947848 14095111 15597452 45644374 27576611 55592222 1962 15177165 9947848 13948749 27422506 14562308 42599671 1963 72498158 15177165 9889098 28132682 9641169 100630840 1964 13150392 72498158 15141576 89923240 15977186 103073632 1965 16163772 13150392 72429455 90673805 74878119 106837577 1966 11984831 16163772 13028292 43860133 23184498 55844964 1967 25270573 11984831 15949683 31614464 14241994 56885037 1968 56293672 25270573 11929785 40223021 12370817 96516693 1969 17378699 56293672 25221849 85004954 24920440 102383653 1970 8891362 17378699 56111968 77438691 54651645 86330053 1971 8817052 8891362 17227685 36819956 21432125 45637008 1972 21047727 8817052 8818773 21379793 9530626 42427520 1973 25576744 21047727 8725835 32257246 5266128 57833990 1974 15691624 25576744 20753545 48553684 16276180 64245308 1975 15836970 15691624 25462303 46274163 27984112 62111133 1976 27795859 15836970 15603260 35110991 15887283 62906850 1977 49098842 27795859 15771626 48424343 16005026 97523185 1978 67889242 49098842 27590409 83135037 25907086 151024279 1979 39009347 67889242 49065900 124224125 51327676 163233472 1980 23439288 39009347 67836344 118634961 77073786 142074249 1981 54373868 23439288 38980603 78994936 48840596 133368804 1982 50222486 54373868 23277296 93376067 28597069 143598553 1983 45423169 50222486 54344642 111597008 57127563 157020177 1984 30432170 45423169 50199276 107023924 56464635 137456094 1985 34939094 30432170 45397271 91361564 49418454 126300658 1986 23287265 34939094 30264062 77113869 31449295 100401134 1987 69343195 23287265 34858731 67681254 38665433 137024449 1988 67989976 69343195 23274557 104800306 33473050 172790282 1989 49464762 67989976 69287917 148217905 63674749 197682667 1990 52813036 49464762 67899110 136836227 70979828 189649263 1991 41741644 52813036 49432233 126683335 64210595 168424979 1992 33098800 41671245 48133836 112515097 70843852 145613897 79 

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