Stock identification of Skeena River Steelhead. using Microsatellite DNA Loci

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1 1 Stock identification of Skeena River Steelhead using Microsatellite DNA Loci Terry D. Beacham Pacific Biological Station Department of Fisheries and Oceans Nanaimo, B. C. V9T 6N7 T. Beacham: Phone: Fax:

2 2 Table of Contents Abstract 4 Introduction..5 Materials and Methods..6 Results and Discussion..8 Acknowledgments 11 References Cited 12 List of Tables Table 1. Steelhead trout samples collected and analyzed from 10 populations in the Skeena River drainage.. 16 Table 2. Number of alleles observed, expected heterozygosity (H e ), observed heterozygosity (H o ), percent significant Hardy-Weinberg equilibrium tests, and F ST among steelhead trout populations for 13 microsatellite loci.. 17 Table 3. Estimated percentage classifications, including standard deviations (SD), of known mixtures of single populations (actual =100%) of Skeena River steelhead populations using a 9-population baseline Table 4. Estimated percentage composition of three simulated mixtures of steelhead trout using variation at 13 microsatellite loci and a 9-population baseline Table 5. Estimated percentage stock compositions for 1998 Skeena River Tyee test fishery, based upon a 9-population baseline Table 6. Estimated percentage stock compositions for 2003 Skeena River Tyee test fishery, based upon a 9-population baseline. 21 List of Figures Figure 1. Unrooted neighbor-joining tree based on chord distances outlining relationships of 9 steelhead trout populations in the Skeena River drainage.. 22

3 3 Figure 2. Percent stock composition at Tyee test fishery during 1998 for Babine River and Sustut River populations steelhead populations.. 23 Figure 3. Percent stock composition at Tyee test fishery during 1998 for Bulkley River drainage steelhead populations.. 24 Figure 4. Percent stock composition at Tyee test fishery during 1998 for Kispiox River, Kitwanga River, and Zymoetz River steelhead populations. 25 Figure 5. Percent stock composition at Tyee test fishery during 2003 for Babine River and Sustut River populations steelhead populations.. 26 Figure 6. Percent stock composition at Tyee test fishery during 2003 for Bulkley River drainage steelhead populations.. 27 Figure 7. Percent stock composition at Tyee test fishery during 1998 for Kispiox, Kitwanga, and Zymoetz steelhead populations. 28 Figure 8. Relative abundance of Babine River and Sustut River steelhead during the 1998 and 2003 test fishery at Tyee.. 29 Figure 9. Relative abundance of Bulkley River drainage steelhead during the 1998 and 2003 test fishery at Tyee.. 30 Figure 10. Relative abundance of Kispiox River, Kitwanga River, and Zymoetz River steelhead during the 1998 and 2003 test fishery at Tyee. 31

4 4 Abstract Variation at 13 microsatellite loci was surveyed in steelhead trout (Oncorhynchus mykiss ) from 9 populations in the Skeena River drainage. Analysis of simulated mixedstock samples suggested that variation at the microsatellite loci provided relatively accurate and precise estimates of stock composition for fishery management applications. Microsatellites provided an effective way to determine population structure, and provided reliable estimates of stock composition in mixed-stock fisheries.

5 5 Introduction Steelhead trout (Oncorhynchus mykiss), the anadromous form of rainbow trout, are found in all major coastal river systems in British Columbia. Steelhead trout abundance has become of increasing concern to fisheries managers, because the status of many populations in British Columbia may require increased emphasis on conservation (Slaney et al. 1996). The current management focus is to ensure the continued viability and productivity of existing populations, and after conservation requirements for specific populations have been obtained, to allow for limited exploitation of target populations. Steelhead trout are not abundant enough to support directed commercial fisheries, although some may be incidentally caught in salmon fisheries. Determination of population structure of exploited species is an essential component in successful management of fisheries. Specifically, this information can be used for applications ranging from the determination of appropriate conservation or management units to estimation of stock composition in mixed-stock fisheries. In British Columbia, surveys of genetic variation have been used to describe population structure in steelhead trout (Parkinson 1984, Taylor 1995, Beacham et al. 1999, Beacham et al. 2000, Heath et al. 2001, Hendry et al. 2002). All of these studies, except for Parkinson (1984), have been directed at local populations or regional groups of steelhead trout. Parkinson (1984) surveyed variation at five allozyme loci in primarily fry and parr from 73 presumed steelhead trout and rainbow trout populations in British Columbia. Development of highly polymorphic microsatellite loci has improved the resolution of detectable genetic variation among steelhead trout populations. Microsatellites are very useful genetic markers to survey genetic variation among salmonid populations. Non-lethal sampling and the abundance of loci make this method very effective for describing population structure in steelhead trout (Nielsen et al. 1994, 1997, Wenburg et al. 1996, Ostberg and Thorgaard 1999, Hendry et al. 2002).

6 6 Microsatellite loci can also be very useful in estimating stock composition in mixed-stock fisheries that intercept steelhead trout (Beacham et al. 1999, 2000). We surveyed microsatellite variation among steelhead trout populations in the Skeena River to resolve population structure and further refine associated stock identification applications. The objective of this study was to estimate stock composition of steelhead trout caught in test fisheries in the lower portion of the Skeena River drainage near Tyee and to assess the reliability of the estimates. Materials and Methods Collection of DNA samples and laboratory analysis Using a chelex resin protocol, DNA was extracted from scales, previously collected frozen samples stored at -20 C, or a punch of operculum or fin tissue preserved in 90% ethanol. We sampled adult fish from 9 steelhead trout populations in the Skeena River. The main method of sampling adults was by angling, although enumeration fences were used at some locations in some years. Fishery samples of returning adults in the Skeena River were collected with a gillnet test fishery (Jantz et al. 1990). Populations, year of sampling, and number of fish analyzed are outlined in Table 1. Further sampling details were outlined by Beacham et al. (1999, 2000). For the survey of baseline populations, PCR products at 13 microsatellite loci: Ogo4 (Olsen et al. 1998), Oke4 (Buchholz et al. 1999), Ots1, Ots2, Ots9 (Banks et al. 1999), Ots108 (Nelson and Beacham 1999), Oki10 (Smith et al. 1998), One101, One111, One114 (Olsen et al. 2000), and Omy325 (O Connell et al. 1997), Ssa197 (O Reilly et al. 1996), and Ssa408 (Cairney et al. 2000) were separated by size on denaturing polyacrylamide gels and allele sizes were determined with the ABI 377 automated DNA sequencer in conjunction with Genescan 3.1 and Genotyper 2.5 software (PE Biosystems, Foster City, CA). Allele frequencies for all samples surveyed

7 7 at all locations in this study are available at Data analysis F ST estimates for each locus were calculated with FSTAT (Goudet 1995), and the standard deviation of the estimate for an individual locus was determined by jackknifing over populations and for all loci combined by bootstrapping over loci. All annual samples available from a location were combined to estimate population allele frequencies, as was recommended by Waples (1990). The Cavalli-Sforza and Edwards (1967) chord distance was used to estimate genetic distance among populations. Estimation of stock composition Genotypic frequencies were determined at each locus in each population and the statistical package for the analysis of mixtures software program (SPAM version 3.7) (Debevec et al. 2000) was used to estimate stock composition of each mixture in the analysis of simulated fishery samples. Genotypic frequencies were determined at each locus in each population. Each locus was assumed to be in Hardy Weinberg equilibrium (HWE), and expected genotypic frequencies were determined from the observed allele frequencies and used as model inputs. Each baseline population was resampled with replacement in order to simulate random variation involved in the collection of the baseline samples before the estimation of stock composition of each test fishery or simulated mixture. Simulated mixtures composed of steelhead trout from different populations were examined in order to evaluate accuracy and precision of the estimated stock compositions. The Kitseguecla River population was not included in the baseline used as sample size was not considered to be representative. Simulated fishery samples of 150 fish were generated

8 8 by randomly resampling with replacement the baseline populations in each drainage. Estimated stock composition of a simulated mixture was then determined, and the whole process was repeated 100 times to estimate the mean and standard deviation of the individual stock composition estimates. For the test fishery samples, point estimates were made of the stock composition, and standard deviations of individual stock estimates derived from 100 bootstrap resamplings of both the baseline populations and the fishery sample. Results and Discussion Population structure Structure was observed among populations surveyed. The Lower Sustut River and Upper Sustut River populations clustered together, as did the Bulkley River and Morice River populations. Regional similarity was observed among the Bulkley River, Morice River, and Toboggan Creek populations. The Kitseguecla River population was the most distinct surveyed, but it likely that this distinctiveness is a result of sampling error, given that only 13 fish were surveyed in this population (Table 1). In order for a genetic-based method of stock identification to be applied successfully, there must be significant genetic differences among the populations that fishery mangers wish to separate. Significant genetic differentiation at the microsatellite loci was observed among steelhead populations surveyed from British Columbia. The average Fst value over all loci was 0.066, indicative of moderate differentiation among populations (Table 2). Simulated mixed-fishery samples Results of estimating simulated single population mixtures for Skeena River steelhead (150 steelhead from each population) using Rannala and Mountain correction

9 9 for small sample size are summarized in Table 3. In the analysis of single-population mixtures, where the expected result was 100% allocation to the target population, all estimates except for two populations were > 90%, the level generally considered acceptable for mixed-stock analysis. For those two populations (Bulkley River, Lower Sustut River), the number of fish surveyed was < 70 steelhead, and thus the lower values for these two populations likely reflect lower sample size, rather than any lack of population differentiation. Mixtures comprising only a single population illustrate the maximum bias expected in estimated stock compositions for that population. In actual applications, mixed-stock fishery samples will contain a range of populations, and estimated stock compositions from these mixtures may in fact be more reliable than those of singlepopulation mixtures. Three multi-population mixtures were evaluated to assess accuracy and precision of estimated stock compositions that one may expect to occur in actual applications. Classification results (percentages for Actual, Estimated, and standard deviations (SD)) by population for three simulated mixtures using Rannala and Mountain correction for small sample size are summarized in Table 4. Mean estimated stock compositions were usually within 2% of the specific population contribution. Simulations may at times provide an optimistic view of model performance when compared with applications to actual mixed fishery samples, particularly if fish from stocks not included in the baseline occur in the mixtures. However, if baseline coverage is improved, bias in the estimated stock compositions as a result of having fish in the mixtures from populations not in the baselines will be reduced. Accuracy and precision of estimated stock compositions of Skeena River steelhead had previously been investigated by Beacham et al. (2000) during a survey incorporating variation at 8 microsatellite loci analyzed on manual gels. With the new baseline of 13 microsatellite loci analyzed with an automated DNA sequencer, accuracy

10 10 and precision of the estimated stock compositions was increased relative to the previous analysis. In both studies, the same stock compositions were simulated for two mixtures. Mean error of estimation for the 13-locus baseline was 1.01%, whereas that of the 8- locus baseline was 1.13%. The mean standard deviation for the 13-locus baseline was 3.23%, and that for the 8-locus baseline was 3.39%. Thus, accuracy and precision were both increased with the new 13-locus baseline compared the previous 8-locus baseline. Estimated percentage stock compositions for the 1998 Tyee test fishery are outlined in Table 5 and Figs. 2-4 and those for the 2003 test fishery are outlined in Table 6 and Figs Under the assumption that the test fishery caught steelhead in proportion to run abundance throughout the season, and because all steelhead caught were analyzed, it is possible to estimate the seasonal relative abundance of steelhead. The dominant stock originated from the Bulkley River drainage, comprising 40% of the returns in both 1998 and In 1998, Babine River steelhead comprised 20% of the returns, but only an estimated 12% in Sustut River drainage populations comprised approximately 15% of the returns in both years. However, it may be that estimates for these populations include the contributions of other upper river unsampled populations. The Kispiox River population was estimated to comprise about 10% of the returns in both years. If the test fishery caught steelhead in proportion to population abundance in a constant manner throughout the season, and since all steelhead caught were analyzed, then the estimated stock composition times the weekly sample size should provide an estimate of relative abundance in each week for each population. This would allow determination of timing of specific populations through the lower Skeena River. Timing of different populations is outlined in Figs In 1998, peak abundance of steelhead occurred during the week of July 26, but in 2003, peak abundance was observed two

11 11 weeks later during the week of August 10. In 2003, timing of the mid and lower river populations was later than other populations, but this was not observed in Microsatellite loci provide practical markers for stock identification of steelhead trout only if there is adequate differentiation among populations in the baseline and the level of annual variation of allele frequencies within populations is minimal relative to population differentiation. Practical considerations with respect to baseline sampling and cost require that the differentiation among populations be greater than the variation within populations so that samples may be pooled over several years to obtain representative samples of populations contributing to fishery samples. Evidence to date indicates that the level of annual variation in allele frequencies within populations was 6 times less than differentiation among populations (Beacham et al. 2004), so pooling samples within populations over several years is a viable option. Acknowledgments This study could not have been accomplished without the support and assistance of many agencies and organizations. Financial support for the extension of the Tyee test fishery in 2003 was provided by the North Coast Steelhead Allliance and Babine River Foundation. Financial support for analysis of the mixed-fishery samples was provided by the Habitat Conservation Trust Fund and the British Columbia Ministry of Water, Land, and Air Protection (MWLAP). Test fishery sample collection was coordinated through the Department of Fisheries Oceans (DFO) in Prince Rupert, and baseline sample collection was conducted by MWLAP staff and the Gitanyow Fisheries Program. Laboratory analysis was conducted by DFO Nanaimo staff.

12 12 References cited Banks, M. A., M. S. Blouin, B. A. Baldwin, V. K. Rashbrook, H. A. Fitzgerald, S. M. Blankenship and D. Hedgecock Isolation and inheritance of novel microsatellites in chinook salmon (Oncorhynchus tshawytscha). J. Hered. 90: Beacham, T. D., S. Pollard, and K. D. Le Population structure and stock identification of steelhead trout in southern British Columbia, Washington, and the Columbia River based on microsatellite DNA variation. Trans. Am. Fish. Soc. 128: Beacham, T. D., S. Pollard and K. D. Le Microsatellite DNA population structure and stock identification of steelhead trout trout (Oncorhynchus mykiss) in the Nass and Skeena Rivers in northern British Columbia. Marine Biotechnology 2: Beacham, T. D., K. D. Le, and J. R. Candy Population structure and stock identification of steelhead trout (Oncorhynchus mykiss) in British Columbia and the Columbia River based on microsatellite variation. Env. Biol. Fish. In press. Buchholz, W., S.J. Miller, and W.J. Spearman Summary of PCR primers for salmonid genetic studies. US Fish. Wild. Serv. Alaska Fish. Prog. Rep Cairney, M., J. B. Taggart, and B. Hoyheim Characterization of microsatellite and minisatellite loci in Atlantic salmon (Salmo salar L.) and cross-species amplification in other salmonids. Mol. Ecol. 9: Cavalli-Sforza, L. L. and A. W. F. Edwards Phylogenetic analysis: models and estimation procedures. Amer. J. Hum. Genet. 19: Debevec, E.M., R. B. Gates, M. Masuda, J. Pella, J. Reynolds and L. W. Seeb SPAM (Version 3.2): Statistics program for analyzing mixtures. J. Hered. 91:

13 13 Goudet, J FSTAT A program for IBM PC compatibles to calculate Weir and Cockerham s (1984) estimators of F-statistics (version 1.2). J. Heredity 86: Heath, D. D., C. Busch, J. Kelly and D. Y. Atagi Temporal change in genetic structure and effective population size in steelhead trout (Oncorhynchus mykiss). Mol. Ecol. 11: Hendry, M.A., J. K. Wenburg, K. W. Myers and A. P. Hendry Genetic and phenotypic variation through the season provides evidence for multiple populations of wild steelhead trout in the Dean River, British Columbia. Trans. Am. Fish. Soc. 131: Jantz, L., R. Kadowaki, and B. Spilsted Skeena River salmon test fishery, Can. Data Rep. Fish. Aquat. Sci. 804: iv + 151p. Nelson, R. J. and T. D. Beacham Isolation and cross species amplification of microsatellite loci useful for study of Pacific salmon. Anim. Genet. 30: Nielsen, J. L., C. A. Gan, J. M. Wright, D. B. Morris and W. K. Thomas Biogeographic distributions of mitochondrial and nuclear markers for southern steelhead trout. Mol. Mar. Biol. Biotech. 3: Nielsen, J. L., C. Carpanzano, M. C. Fountain and C. A. Gan Mitochondrial DNA and nuclear microsatellite diversity in hatchery and wild Oncorhynchus mykiss from freshwater habitats in southern California. Trans. Amer. Fish. Soc. 126: Olsen, J. B., P. Bentzen and J. E. Seeb Characterization of seven microsatellite loci derived from pink salmon. Mol. Ecol. 7: Olsen, J. B., S. L. Wilson, E. J.Kretschmer, K. C. Jones and J. E. Seeb Characterization of 14 tetranucleotide microsatellite loci derived from sockeye salmon. Mol. Ecol. 9:

14 14 O Connell, M., R. G. Danzmann, J. M. Cornuet, J.M. Wright and M. M. Ferguson Differentiation of rainbow trout populations in Lake Ontario and the evaluation of the stepwise mutation and infinite allele mutation models using microsatellite variability. Can. J. Fish. Aquat. Sci. 54: O Reilly, P. T., L. C. Hamilton, S. K. McConnell and J. M. Wright Rapid analysis of genetic variation in Atlantic salmon (Salmo salar) by PCR multiplexing of dinucleotide and tetranucleotide microsatellites. Can. J. Fish. Aquat. Sci. 53: Ostberg, C.O. and G. H. Thorgaard Geographic distribution of chromosome and microsatellite DNA polymorphisms in Oncorhynchus mykiss native to western Washington. Copeia 1999(2): Parkinson, E. A Genetic variation in populations of steelhead trout trout (Salmo gairdneri) in British Columbia. Can. J. Fish. Aquat. Sci. 41: Slaney, T. L., K. D. Hyatt, T. G. Northcote and R. J. Fielden Status of anadromous salmon and trout in British Columbia and Yukon. Fisheries 21: Smith, C. T., B. F. Koop and R. J. Nelson Isolation and characterization of coho salmon (Oncorhynchus kisutch) microsatellites and their use in other salmonids. Mol. Ecol. 7: Taylor, E.B Genetic variation at minisatellite DNA loci among North Pacific populations of steelhead trout and rainbow trout (Oncorhynchus mykiss). J. Hered. 86: Waples, R. S Temporal changes of allele frequency in Pacific salmon populations: implications for mixed-stock fishery analysis. Can. J. Fish. Aquat. Sci. 47: Wenburg, J. K., J. B. Olsen and P. Bentzen Multiplexed systems of microsatellites for genetic analysis in coastal cutthroat trout (Oncorhynchus clarki

15 15 clarki) and steelhead trout (Oncorhynchus mykiss). Mol. Mar. Biol. Biotech. 5:

16 16 Table 1. Steelhead trout samples collected and analyzed from 10 populations in the Skeena River drainage. Sample sizes (N) are for years sampled. Population Years sampled N Total N Lower Sustut River 1997, , Upper Sustut River 1994, 1996, 1997, , 50, 84, Babine River 1991, 1992, 1995, 1996, 1997, , 18, 22, 31, 28, Bulkley River 1995, 1996, , 36, Morice River 1991, 1992, 1995, , 30, 15, Toboggan Creek Kispiox River 1992, 1995, , 30, Kitwanga River Zymoetz River 1993, 1995, , 18, Kitseguecla River

17 17 Table 2. Number of alleles observed, expected heterozygosity (H e ), observed heterozygosity (H o ), percent significant Hardy-Weinberg equilibrium tests, and F ST among steelhead trout populations for 13 microsatellite loci. Standard deviations are in parentheses. Locus Alleles H e H o HWE F ST Ogo (0.009) Oke (0.019) Ots (0.014) Ots (0.006) Ots (0.006) Ots (0.013) Oki (0.021) One (0.015) One (0.008) One (0.004) Omy (0.006) Ssa (0.015) Ssa (0.008) All loci (0.007)

18 18 Table 3. Estimated percentage classifications, including standard deviations (SD), of known mixtures of single populations (actual =100%) of Skeena River steelhead populations using a 9-population baseline. Population Estimate Babine 95.3 (2.0) Bulkley 85.3 (3.1)*1 Morice 93.6 (2.6) Toboggan 90.0 (3.8) Upper Sustut 98.7 (1.1) Lower Sustut 84.7 (3.4)*2 Kispiox 90.1 (3.0) Kitwanga 93.8 (2.5) Zymoetz 93.0 (2.5)_ *Baseline sample sizes < 70 fish. 1 Sum of Bulkley/Morice = 90.8%. 2 Sum of Upper/Lower Sustut = 88.5%.

19 19 Table 4. Estimated percentage composition of three simulated mixtures of steelhead trout using variation at 13 microsatellite loci and a 9-population baseline. Each mixture of 150 fish was generated 100 times with replacement, and stock compositions of the mixtures were estimated by resampling with replacement each baseline population. is the sum of populations indicated. Standard deviation is in parentheses. Population Sample 1 Sample 2 Sample 3 Actual Estimated Actual Estimated Actual Estimated Babine (4.1) (4.2) (4.5) Bulkley (2.7) (3.7) 0.6 (0.8) Morice (3.0) (4.0) (4.3) Σ Bulkley/Morice (3.0) (4.1) (4.3) Toboggan (2.4) 1.4 (1.3) 1.1 (1.3) Upper Sustut (2.9) (3.2) 0.6 (0.7) Lower Sustut (3.1) 0.8 (1.1) 0.8 (0.9) Σ Upper/Lower Sustut (3.2) (3.2) 1.4 (1.0) Kispiox (3.1) (3.5) (3.1) Kitwanga (2.0) 0.6 (0.9) 0.6 (0.9) Zymoetz (2.6) (1.8) 0.3 (0.4).

20 20 Table 5. Estimated percentage stock compositions for 1998 Skeena River Tyee test fishery, based upon a 9-population baseline. Standard deviations are in parentheses. Jul 5-18 Jul Jul 26-Aug 1 Aug 2-8 Aug 9-15 Aug Sample size Population Expected Std.Dev. Expected Std.Dev. Expected Std.Dev. Expected Std.Dev. Expected Std.Dev. Expected Std.Dev. Babine 11.3 (5.7) 19.5 (3.8) 19.8 (4.4) 26.8 (4.0) 8.5 (5.5) 10.3 (5.4) Bulkley 5.7 (3.4) 4.4 (2.4) 4.6 (2.3) 3.6 (1.7) 2.0 (2.1) 0.0 (2.2) Kispiox 9.5 (7.1) 19.0 (3.6) 19.5 (3.9) 8.5 (3.1) 16.2 (5.3) 21.1 (5.6) Kitwanga 7.2 (4.5) 0.0 (1.8) 0.0 (1.9) 12.5 (2.6) 16.8 (4.4) 11.7 (4.1) Lower_Sustut 6.6 (4.2) 10.9 (3.0) 11.0 (2.7) 9.4 (2.3) 10.3 (3.7) 10.3 (3.8) Morice 15.4 (7.2) 18.2 (4.7) 17.4 (4.1) 20.4 (4.0) 33.6 (6.1) 28.0 (6.1) Sustut 18.3 (4.4) 8.6 (3.0) 8.5 (3.2) 2.5 (2.0) 3.0 (3.4) 5.2 (2.6) Toboggan 10.4 (5.2) 14.5 (3.5) 14.3 (3.5) 10.7 (3.0) 0.7 (3.3) 12.1 (5.4) Zymoetz 15.7 (5.2) 4.8 (2.4) 5.0 (2.5) 5.7 (1.9) 9.0 (3.0) 1.4 (2.2) Bulkley drainage 31.5 (7.5) 37.1 (4.7) 36.3 (4.9) 34.7 (4.4) 36.3 (6.6) 40.1 (6.4) Sustut drainage 24.9 (5.6) 19.6 (3.8) 19.5 (3.7) 11.9 (2.6) 13.3 (4.4) 15.6 (4.0) Aug Aug 30 - Sep 5 Sep 6-12 Sep Seasonal Population Expected Std.Dev. Expected Std.Dev. Expected Std.Dev. Expected Std.Dev. Expected Std.Dev. Babine 30.1 (6.2) 19.5 (8.9) 16.9 (9.9) 12.9 (9.3) 20.4 (2.1) Bulkley 1.4 (2.8) 0.0 (3.2) 0.0 (3.5) 3.5 (6.3) 2.8 (1.0) Kispiox 17.8 (5.3) 7.8 (6.7) 6.4 (8.6) 24.0 (10.3) 11.7 (1.9) Kitwanga 8.7 (4.3) 1.2 (4.9) 6.9 (8.4) 6.9 (6.7) 7.6 (1.4) Lower_Sustut 8.8 (3.0) 4.8 (2.9) 11.7 (6.4) 0.0 (3.1) 8.4 (1.1) Morice 24.3 (6.2) 37.6 (10.2) 18.2 (10.1) 31.5 (12.6) 26.2 (2.4) Sustut 2.3 (2.8) 3.3 (4.2) 8.6 (7.2) 0.0 (4.1) 5.5 (1.1) Toboggan 1.9 (4.0) 18.6 (8.5) 27.0 (10.2) 13.7 (9.7) 10.7 (1.8) Zymoetz 4.7 (3.4) 7.3 (5.7) 4.3 (3.9) 7.6 (4.4) 6.7 (1.1) Bulkley drainage 27.7 (6.4) 56.2 (11.3) 45.1 (11.1) 48.7 (14.0) 39.7 (2.4) Sustut drainage 11.0 (3.8) 8.1 (4.6) 20.3 (7.9) 0.0 (5.2) 13.9 (1.5)

21 21 Table 6. Estimated percentage stock compositions for 2003 Skeena River Tyee test fishery, based upon a 9-population baseline. Standard deviations are in parentheses. Jul 6-19 Jul Jul 31- Aug 6 Aug 7-13 Aug Aug Sample size Babine 5.0 (11.9) 7.9 (6.4) 8.8 (7.0) 17.3 (6.2) 11.4 (4.9) 23.0 (7.5) Bulkley 0.0 (0.0) 0.0 (2.2) 4.9 (3.8) 2.3 (3.0) 2.7 (3.3) 2.1 (3.8) Kispiox 16.1 (15.1) 0.0 (2.2) 11.6 (7.5) 9.9 (6.3) 7.4 (6.4) 21.1 (8.9) Kitwanga 0.0 (2.7) 9.9 (6.1) 3.8 (5.2) 2.6 (4.6) 13.9 (5.5) 8.8 (4.9) Lower_Sustut 6.3 (9.7) 12.0 (7.1) 13.0 (5.4) 1.5 (3.6) 6.9 (2.8) 1.4 (2.8) Morice 42.2 (18.3) 36.3 (9.1) 38.0 (8.6) 40.3 (8.6) 35.1 (7.0) 28.3 (9.6) Sustut 21.9 (13.3) 28.3 (7.6) 10.6 (5.6) 11.5 (5.8) 5.6 (3.8) 13.1 (5.1) Toboggan 0.0 (0.0) 0.0 (4.2) 0.0 (4.7) 13.5 (6.5) 3.5 (4.3) 2.3 (5.1) Zymoetz 8.4 (8.5) 5.5 (4.1) 9.4 (5.4) 1.2 (2.3) 13.4 (4.3) 0.0 (3.3) Bulkley/Morice 42.2 (18.3) 36.3 (9.2) 42.8 (8.3) 56.1 (7.9) 41.3 (7.2) 32.6 (10.5) Sustut 28.2 (15.4) 40.4 (7.8) 23.6 (5.8) 12.9 (6.9) 12.5 (4.1) 14.5 (5.8) Aug 28- Sept 3 Sept 4-10 Sept Sept Seasonal Sample size Babine 0.0 (6.0) 13.9 (8.4) 2.9 (10.4) 0.0 (10.0) 11.1 (2.7) Bulkley 5.2 (5.3) 0.0 (1.7) 0.0 (5.0) 0.0 (2.0) 1.9 (1.2) Kispiox 30.7 (10.3) 29.3 (10.1) 29.2 (12.8) 85.5 (23.9) 15.8 (3.0) Kitwanga 23.1 (9.7) 13.6 (8.9) 9.2 (9.0) 0.0 (8.0) 9.5 (2.4) Lower_Sustut 0.0 (3.7) 1.1 (6.0) 13.7 (9.4) 0.0 (4.5) 6.7 (1.9) Morice 22.3 (10.8) 31.3 (10.6) 31.3 (12.9) 0.0 (12.0) 33.1 (4.4) Sustut 0.0 (1.9) 3.8 (7.0) 0.7 (6.0) 0.0 (13.5) 10.4 (2.1) Toboggan 2.5 (6.8) 2.5 (6.2) 8.5 (9.4) 14.5 (17.0) 4.2 (2.5) Zymoetz 16.2 (8.4) 4.5 (4.7) 4.5 (6.0) 0.0 (3.8) 7.3 (1.8) Bulkley/Morice 30.0 (10.8) 33.8 (11.8) 39.8 (13.9) 14.5 (18.5) 39.2 (4.6) Sustut 0.0 (4.2) 4.9 (8.1) 14.4 (11.5) 0.0 (13.8) 17.1 (2.5)

22 22 Figure 1. Unrooted neighbor-joining tree based on chord distances outlining relationships of 9 steelhead trout populations in the Skeena River drainage.

23 Babine/Sustut Percent Babine Lower_Sustut Upper_Sustut Sustut drainage Jul 5-18 Jul Jul 26- Aug 1 Aug 2-8 Aug 9-15 Aug Aug Aug 30 - Sep 5 Sep 6-12 Sep Figure 2. Percent stock composition at Tyee test fishery during 1998 for Babine River and Sustut River populations steelhead populations.

24 Bulkley drainage Percent Bulkley Morice Toboggan Bulkley drainage Jul 5-18 Jul Jul 26- Aug 1 Aug 2-8 Aug 9-15 Aug Aug Aug 30 - Sep 5 Sep 6-12 Sep Figure 3. Percent stock composition at Tyee test fishery during 1998 for Bulkley River drainage steelhead populations.

25 mid/lower Percent Kispiox Kitwanga Zymoetz Jul 5-18 Jul Jul 26- Aug 1 Aug 2-8 Aug 9-15 Aug Aug Aug 30 - Sep 5 Sep 6-12 Sep Figure 4. Percent stock composition at Tyee test fishery during 1998 for Kispiox River, Kitwanga River, and Zymoetz River steelhead populations.

26 Babine Lower Sustut Upper Sustut Sustut Drainage 30 Percent Jul 6-19 Aug Aug 7-13 Jul 31- Aug 6 Jul Sep Sep 4-10 Aug 28- Sept 3 Aug Sep Figure 5. Percent stock composition at Tyee test fishery during 2003 for Babine River and Sustut River populations steelhead populations.

27 Bulkley Morice Toboggan Bulkley Drainage 40 Percent Sep Sep Sep 4-10 Aug 28- Sept 3 Aug Aug Aug 7-13 Jul 31- Aug 6 Jul Jul 6-19 Figure 6. Percent stock composition at Tyee test fishery during 2003 for Bulkley River drainage steelhead populations.

28 Kispiox Kitwanga Zymoetz 60 Percent Aug 28- Sept 3 Aug Aug Aug 7-13 Jul 31- Aug 6 Jul Jul 6-19 Sep Sep Sep 4-10 Figure 7. Percent stock composition at Tyee test fishery during 2003 for Kispiox, Kitwanga, and Zymoetz steelhead populations.

29 Babine Lower Sustut Upper Sustut Sustut Drainage Number of Fish Jul 6-19 Jul Jul 31- Aug 6 Aug 7-13 Aug 28- Sept 3 Aug Aug Sep 4-10 Sep Sep Figure 8. Relative abundance of Babine River and Sustut River steelhead during the 1998 and 2003 test fishery at Tyee.

30 Bulkley Morice Toboggan Bulkley Drainage Number of Fish Jul 6-19 Aug 7-13 Jul 31- Aug 6 Jul Aug 28- Sept 3 Aug Aug Sep Sep Sep 4-10 Figure 9. Relative abundance of Bulkley River drainage steelhead during the 1998 and 2003 test fishery at Tyee.

31 Kispiox Kitwanga Zymoetz Number of Fish Jul 6-19 Jul Jul 31- Aug 6 Aug 7-13 Aug 28- Sept 3 Aug Aug Sep 4-10 Sep Sep Figure 10. Relative abundance of Kispiox River, Kitwanga River, and Zymoetz River steelhead during the 1998 and 2003 test fishery at Tyee.

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