The extent to which stray, hatchery-reared salmon affect wild populations is much debated. Although experiments show that artificial breeding and culture influence the genetics of hatchery salmon, little is known about the interaction between hatchery and wild salmon in a natural setting. Here, we estimated historical and contemporary genetic population structures of chum salmon (Oncorhynchus keta) in Prince William Sound (PWS), Alaska, with 135 single nucleotide polymorphism (SNP) markers. Historical population structure was inferred from the analysis of DNA from fish scales, which had been archived since the late 1960’s for several populations in PWS. Parallel analyses with microsatellites and a test based on Hardy-Weinberg proportions showed that about 50% of the fish-scale DNA was cross-contaminated with DNA from other fish. These samples were removed from the analysis. We used a novel application of the classical source-sink model to compare SNP allele frequencies in these archived fish-scales (1964–1982) with frequencies in contemporary samples (2008–2010) and found a temporal shift toward hatchery allele frequencies in some wild populations. Other populations showed markedly less introgression, despite moderate amounts of hatchery straying. The extent of introgression may reflect similarities in spawning time and life-history traits between hatchery and wild fish, or the degree that hybrids return to a natal spawning area. The source-sink model is a powerful means of detecting low levels of introgression over several generations.
We examined genetic diversity patterns among 55 collections of Chum Salmon from the northeastern Pacific Ocean using 89 single nucleotide polymorphisms (SNPs). The distribution of Chum Salmon samples extended from the Nass River along the coast of British Columbia and along the coast of Washington as far south as the Columbia River. Chum Salmon represented three previously defined run-groups: fall (primarily), summer, and winter. Genetic variation at SNP loci, as measured by F ST , ranged from 0.002 to 0.279 over all collections and averaged 0.062 over all loci. Similar to the genetic patterns detected with microsatellites and allozymes, genetic variation followed a regional structure along geographic distance, with genetic diversity being highest in the north and decreasing southward, then increasing in and near the Columbia River. Within Puget Sound, Washington, genetic variation was structured further according to run timing (fall, summer, and winter) and shared ancestry. Simulations indicated that this suite of SNPs is powerful for identifying regional components in a Chum Salmon mixed fishery. Because of the transferability of SNP data, the growing SNP baseline for Chum Salmon will be useful for multiple agencies managing Chum Salmon around the Pacific Rim.
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