An international multi‐laboratory project was conducted to develop a standardized DNA database for Chinook salmon (Oncorhynchus tshawytscha). This project was in response to the needs of the Chinook Technical Committee of the Pacific Salmon Commission to identify stock composition of Chinook salmon caught in fisheries during their oceanic migrations. Nine genetics laboratories identified 13 microsatellite loci that could be reproducibly assayed in each of the laboratories. To test that the loci were reproducible among laboratories, blind tests were conducted to verify scoring consistency for the nearly 500 total alleles. Once standardized, a dataset of over 16,000 Chinook salmon representing 110 putative populations was constructed ranging throughout the area of interest of the Pacific Salmon Commission from Southeast Alaska to the Sacramento River in California. The dataset differentiates the major known genetic lineages of Chinook salmon and provides a tool for genetic stock identification of samples collected from mixed fisheries. A diverse group of scientists representing the disciplines of fishery management, genetics, fishery administration, population dynamics, and sampling theory are now developing recommendations for the integration of these genetic data into ocean salmon management.

Recent advances in population genomics have made it possible to detect previously unidentified structure, obtain more accurate estimates of demographic parameters, and explore adaptive divergence, potentially revolutionizing the way genetic data are used to manage wild populations. Here, we identified 10 944 single-nucleotide polymorphisms using restriction-site-associated DNA (RAD) sequencing to explore population structure, demography, and adaptive divergence in five populations of Chinook salmon (Oncorhynchus tshawytscha) from western Alaska. Patterns of population structure were similar to those of past studies, but our ability to assign individuals back to their region of origin was greatly improved (>90% accuracy for all populations). We also calculated effective size with and without removing physically linked loci identified from a linkage map, a novel method for nonmodel organisms. Estimates of effective size were generally above 1000 and were biased downward when physically linked loci were not removed. Outlier tests based on genetic differentiation identified 733 loci and three genomic regions under putative selection. These markers and genomic regions are excellent candidates for future research and can be used to create high-resolution panels for genetic monitoring and population assignment. This work demonstrates the utility of genomic data to inform conservation in highly exploited species with shallow population structure.

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Studies of the oceanic and near-shore distributions of Pacific salmon, whose migrations typically span thousands of kilometres, have become increasingly valuable in the presence of climate change, increasing hatchery production and potentially high rates of bycatch in offshore fisheries. Genetics data offer considerable insights into both the migratory routes as well as the evolutionary histories of the species. However, these types of studies require extensive data sets from spawning populations originating from across the species' range. Single nucleotide polymorphisms (SNPs) have been particularly amenable for multinational applications because they are easily shared, require little interlaboratory standardization and can be assayed through increasingly efficient technologies. Here, we discuss the development of a data set for 114 populations of chum salmon through a collaboration among North American and Asian researchers, termed PacSNP. PacSNP is focused on developing the database and applying it to problems of international interest. A data set spanning the entire range of species provides a unique opportunity to examine patterns of variability, and we review issues associated with SNP development. We found evidence of ascertainment bias within the data set, variable linkage relationships between SNPs associated with ancestral groupings and outlier loci with alleles associated with latitude.

We examined the assumption that landscape heterogeneity similarly influences the spatial distribution of genetic diversity in closely related and geographically overlapping species. Accordingly, we evaluated the influence of watershed affiliation and nine habitat variables from four categories (spatial isolation, habitat size, climate, and ecology) on population divergence in three species of Pacific salmon (Oncorhynchus tshawytscha, O. kisutch, and O. keta) from three contiguous watersheds in subarctic North America. By incorporating spatial data we found that the three watersheds did not form the first level of hierarchical population structure as predicted. Instead, each species exhibited a broadly similar spatial pattern: a single coastal group with populations from all watersheds and one or more inland groups primarily in the largest watershed. These results imply that the spatial scale of conservation should extend across watersheds rather than at the watershed level which is the scale for fishery management. Three independent methods of multivariate analysis identified two variables as having influence on population divergence across all watersheds: precipitation in all species and subbasin area (SBA) in Chinook. Although we found general broad-scale congruence in the spatial patterns of population divergence and evidence that precipitation may influence population divergence in each species, we also found differences in the level of population divergence (coho [ Chinook and chum) and evidence that SBA may influence population divergence only in Chinook. These differences among species support a species-specific approach to evaluating and planning for the influence of broad-scale impacts such as climate change.