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Wild stocks of chum salmon, Oncorhynchus keta, have experienced recent declines in some areas of their range. Also, the release of hatchery chum salmon has escalated to nearly three billion fish annually. The decline of wild stocks and the unknown effects of hatchery fish combined with the uncertainty of future production caused by global climate change have renewed interest in the migratory patterns of chum salmon on the high seas. We studied the composition of high-seas mixtures of maturing and immature individuals using baseline data for 20 allozyme loci from 356 populations from throughout the Pacific Rim. Composition estimates were made from three time series. Two of these time series were from important coastal migratory corridors: the Shumagin Islands south of the Alaska Peninsula and the east coast of the Kamchatka Peninsula. The third was from chum salmon captured incidentally in the Bering Sea trawl fishery for walleye pollock. We also analyzed geographically dispersed collections of chum salmon captured in the month of July. The time series show dynamic changes in stock composition. The Shumagin Island corridor was used primarily by Northwest Alaskan and Asian populations in June; by the end of July stocks from the Alaska Peninsula and southern North America dominated the composition. The composition along the Kamchatka coast changed dramatically from primarily Russian stocks in May to primarily Japanese stocks in August; the previously undocumented presence of stocks from the Alaska Peninsula and Gulf of Alaska was also demonstrated. Immature chum salmon from throughout the Pacific Rim, including large proportions of southern North American stocks, contributed to the Bering Sea bycatch during the months of September and October. The migration routes of North American stocks is far more widespread than previously observed, and the Bering Sea is an important rearing area for maturing and immature chum salmon from throughout the species’ range.

We tested signals of historical reductions in effective population size within populations of sockeye salmon Oncorhynchus nerka returning to Bristol Bay, Alaska, to examine the roles that ecotype, migration obstacles, and drainage might play in the highly variable production of the Kvichak River drainage. We collected data for eight microsatellite loci from ∼100 fish at each of 16 locations within the Kvichak River drainage and five locations within the more productively stable Naknek River drainage. Pair-wise exact tests were used to group similar collections within ecotype, within drainage, and above and below migration obstacles. After grouping, collections represented independent populations for further analyses. We examined the number of alleles per locus, mean ratio of the number of alleles to the range in allele size, heterozygosity excess, and gametic disequilibrium as measures of reduction-in-population-size events. Number of alleles per locus revealed the largest number of significant differences. Tributary populations showed a stronger signal consistent with reduced effective population size than did beach populations within the Kvichak River drainage. Kvichak River drainage populations showed a stronger signal consistent with reduced effective population size than did the Naknek River drainage populations. Populations above migration obstacles showed signals consistent with reduction in historical population sizes in multiple measures indicating some of these reductions may be severe enough to qualify as demographic bottlenecks.

Mutation rate can vary widely among microsatellite loci. This variation may cause discordant single-locus and multi-locus estimates of FST, the commonly used measure of population divergence. We use 16 microsatellite and five allozyme loci from 14 sockeye salmon populations to address two questions about the affect of mutation rate on estimates of FST: (1) does mutation rate influence FST estimates from all microsatellites to a similar degree relative to allozymes?; (2) does the influence of mutation rate on FST estimates from microsatellites vary with geographic scale in spatially structured populations? For question one we find that discordant estimates of FST among microsatellites as well as between the two marker classes are correlated with mean within-population heterozygosity (HS ) and thus are likely due to differences in mutation rate. Highly polymorphic microsatellites (HS > 0.84) provide significantly lower estimates of FST than moderately polymorphic microsatellites and allozymes (HS < 0.60). Estimates of FST from binned allele frequency data and RST provide more accurate measures of population divergence for highly polymorphic but not for moderately polymorphic microsatellites. We conclude it is more important to pool loci of like HS rather than marker class when estimating FST. For question two we find the FST values for moderately and highly polymorphic loci, while significantly different, are positively correlated for geographically proximate but not geographically distant population pairs. These results are consistent with expectations from the equilibrium approximation of Wright’s infinite island model and confirm that the influence of mutation on estimates of FST can vary in spatially structured populations presumably because the rate of migration varies inversely with geographic scale.