Previous studies generally report that hatchery‐origin Pacific Salmon (Oncorhynchus spp.) have lower relative reproductive success (RRS) than their natural‐origin counterparts. We estimated the RRS of Pink Salmon (O. gorbuscha) in Prince William Sound (PWS), Alaska using incomplete pedigrees. In contrast to other RRS studies, Pink Salmon have a short freshwater life history, freshwater habitats in PWS are largely unaltered by development, and sampling was conducted without the aid of dams or weirs resulting in incomplete sampling of spawning individuals. Pink Salmon released from large‐scale hatchery programs in PWS have interacted with wild populations for more than 15 generations. Hatchery populations were established from PWS populations but have subsequently been managed as separate broodstocks. Gene flow is primarily directional, from hatchery strays to wild populations. We used genetic‐based parentage analysis to estimate the RRS of a single generation of stray hatchery‐origin Pink Salmon in two streams, and across the odd‐ and even‐year lineages. Despite incomplete sampling, we assigned 1745 offspring to at least one parent. Reproductive success (RS), measured as sampled adult offspring that returned to their natal stream, was significantly lower for hatchery‐ vs. natural‐origin parents in both lineages, with RRS ranging from 0.03 to 0.47 for females and 0.05 to 0.86 for males. Generalized linear modeling for the even‐year lineage indicated that RRS was lower for hatchery‐origin fish, ranging from 0.42 to 0.60, after accounting for sample date (run timing), sample location within the stream, and fish length. Our results strongly suggest that hatchery‐origin strays have lower fitness in the wild. The consequences of reduced RRS on wild productivity depend on whether the mechanisms underlying reduced RRS are environmentally driven, and likely ephemeral, or genetically driven, and likely persistent across generations.

We investigate adaptive resource polymorphism in kokanee (Oncorhynchus nerka) from Jo-Jo Lake, Alaska, by determining whether previously observed niche expansion occurs at the population or individual level. Utilizing morphological, genetic, and stable isotope techniques, we found no evidence of discrete trophic morphotypes as previously described, but instead found evidence for an ontogenetic diet shift. Carbon and nitrogen isotope data indicate a 40% decrease in the proportion of benthic feeding and an increase of one trophic position over the size and age ranges of adult kokanee, corresponding to a diet shift from consumption of macroinvertebrates in smaller individuals to piscivory in larger individuals. This novel piscivory in kokanee may result from predatory and competitive freedom resulting from the lack of limnetic predators in Jo-Jo Lake. Piscivorous feeding despite a phenotype–environment mismatch has resulted in large, piscivorous kokanee having up to 70% of their gill rakers damaged. Observed reductions in gill raker number relative to the putative ancestral population are convergent with expectations for piscivorous fishes, despite a presumed lack of standing genetic variation for piscivory in the sockeye salmon – kokanee species complex. Jo-Jo Lake kokanee are a distinctive example of adaptation in salmonids in response to ecological release. This unusual population highlights the importance of phenotypic plasticity in response to competition in shaping the adaptive landscape and altering evolutionary trajectories.

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With advances in molecular genetics it is becoming increasingly feasible to conduct genetic stock identification (GSI) to inform management actions that occur within a fishing season. While applications of in-season GSI are becoming widespread, such programs seldom integrate data from previous years, underutilizing the full breadth of information available for real-time inference. In this study, we developed a Bayesian hierarchical model that integrates historical and in-season GSI data to estimate temporal changes in the composition of a mixed stock of sockeye salmon returning to Alaska’s Chignik watershed across the fishing season. Simulations showed that even after accounting for time constraints of transporting and analyzing genetic samples, a hierarchical approach can rapidly achieve accurate in-season stock allocation, outperforming alternative methods that rely solely on historical or in-season data by themselves. As the distribution and phenology of fish populations becomes more variable and difficult to predict under climate change, in-season management tools will likely be increasingly relied upon to protect biocomplexity while maximizing harvest opportunity in mixed stock fisheries.