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.

Single nucleotide polymorphisms (SNPs) are appealing genetic markers due to several beneficial attributes, but uncertainty remains about how many of these bi-allelic markers are necessary to have sufficient power to differentiate populations, a task now generally accomplished with highly polymorphic microsatellite markers. In this study, we tested the utility of 37 SNPs and 13 microsatellites for differentiating 29 broadly distributed populations of Chinook salmon (n = 2783). Information content of all loci was determined by In and , and the top 12 markers ranked by In were microsatellites, but the 6 highest, and 7 of the top 10 ranked markers, were SNPs. The mean ratio of random SNPs to random microsatellites ranged from 3.9 to 4.1, but this ratio was consistently reduced when only the most informative loci were included. Individual assignment test accuracy was higher for microsatellites (73.1%) than SNPs (66.6%), and pooling all 50 markers provided the highest accuracy (83.2%). When marker types were combined, as few as 15 of the top ranked loci provided higher assignment accuracy than either microsatellites or SNPs alone. Neighbour-joining dendrograms revealed similar clustering patterns and pairwise tests of population differentiation had nearly identical results with each suite of markers. Statistical tests and simulations indicated that closely related populations were better differentiated by microsatellites than SNPs. Our results indicate that both types of markers are likely to be useful in population genetics studies and that, in some cases, a combination of SNPs and microsatellites may be the most effective suite of loci. Fig. 2 Chord distance (D CSE ) neighbour-joining dendrograms and self-assignment matrices of populations of Chinook salmon from North America as determined with (a) 13 microsatellites, (b) 37 SNPs, and (c) all 50 markers combined. The diagonal represents the percentage of self-assigned individuals from a population and shaded blocks above and below the diagonal indicate percentage of mis-assignments to populations corresponding with the dendrogram. Grey grid lines correspond to regional clusters in the neighbour-joining dendrogram. Shading scale at the right of each figure depicts percentage assignment in 10% increments. 3472 S . R . N A R U M E T A L .

Parentage-based tagging (PBT) is a promising alternative to traditional coded-wire tag (CWT) methodologies for monitoring and evaluating hatchery stocks. This approach involves the genotyping of hatchery broodstock and uses parentage assignments to identify the origin and brood year of their progeny. In this study we empirically confirmed that fewer than 100 single nucleotide polymorphisms (SNPs) were needed to accurately conduct PBT, we demonstrated that our selected panel of SNPs was comparable in accuracy to a panel of microsatellites, and we verified that stock assignments made with this panel matched those made using CWTs. We also demonstrated that when sampling of spawners was incomplete, an estimated PBT rate for the offspring could also be predicted with fewer than 100 SNPs. This study in the Snake River basin is one of the first large-scale implementations of PBT in salmonids and lays the foundation for adopting this technology more broadly in the region, thereby allowing the unprecedented ability to mark millions of smolts and an opportunity to address a variety of parentage-based research and management questions.

Parentage‐based tagging (PBT), an innovative and large‐scale application of genetic parentage assignments, is transforming how fisheries managers determine the age and origin of sampled fish. PBT is an efficient alternative for mass tagging and has been widely implemented in the Pacific Northwest. While still an emerging technology, PBT is being used to provide information to managers in state, federal, and tribal agencies on the harvest, research, and conservation of Chinook Salmon Oncorhynchus tshawytscha and steelhead O. mykiss in this region. We review the development of PBT in the Pacific Northwest focusing on the technical and logistical challenges for implementing a regional PBT program. We also showcase recent results and review management efforts that made use of PBT‐derived data.

Mounting evidence of climatic effects on riverine environments and adaptive responses of fishes have elicited growing conservation concerns. Measures to rectify population declines include assessment of local extinction risk, population ecology, viability, and genetic differentiation. While conservation planning has been largely informed by neutral genetic structure, there has been a dearth of critical information regarding the role of non-neutral or functional genetic variation. We evaluated genetic variation among steelhead trout of the Columbia River Basin, which supports diverse populations distributed among dynamic landscapes. We categorized 188 SNP loci as either putatively neutral or candidates for divergent selection (non-neutral) using a multitest association approach. Neutral variation distinguished lineages and defined broad-scale population structure consistent with previous studies, but fine-scale resolution was also detected at levels not previously observed. Within distinct coastal and inland lineages, we identified nine and 22 candidate loci commonly associated with precipitation or temperature variables and putatively under divergent selection. Observed patterns of non-neutral variation suggest overall climate is likely to shape local adaptation (e.g., potential rapid evolution) of steelhead trout in the Columbia River region. Broad geographic patterns of neutral and non-neutral variation demonstrated here can be used to accommodate priorities for regional management and inform long-term conservation of this species.