Reliability of trans-generational genetic mark-recapture (tGMR) for enumerating Pacific salmon.

As Pacific salmon (Oncorhynchus spp.) decline across much of their range, it is imperative to further develop minimally invasive tools to quantify population abundance. One such advancement, trans-generational genetic mark-recapture (tGMR), uses parentage analysis to estimate the size of wild populations. Our study examined the precision and accuracy of tGMR through a comparison to a traditional mark-recapture estimate for Chilkat River Chinook salmon (O. tshawytscha) in Southeast Alaska. We examined how adult sampling location and timing impact tGMR by comparing estimates derived using samples collected in the lower river mainstem to those using samples obtained in upriver spawning tributaries. Results indicated that tGMR estimates using a representative sample of mainstem adults were most concordant with, and 3% more precise than, the traditional mark-recapture estimate for this stock. Importantly, the timing and location of adult sampling were found to impact abundance estimates, depending on what proportion of the population dies or moves to unsampled areas between downriver and upriver sampling events. Additionally, we identified potential sources of bias in tGMR arising from violations of key assumptions using a novel individual-based modeling framework, parameterized with empirical values from the Chilkat River. Simulations demonstrated that increased reproductive success and sampling selectivity of older, larger individuals, introduced negative bias into tGMR estimates. Our individual-based model offers a customizable and accessible method to identify and quantify these biases in tGMR applications (https://github.com/swrosenbaum/tGMR_simulations). We underscore the critical role of system-specific sampling design considerations in ensuring the precision and accuracy of tGMR projects. This study validates tGMR as a potentially useful tool for improved population enumeration in semelparous species.

Tidal gradients, fine-scale homing and a potential cryptic ecotype of wild spawning pink salmon (Oncorhynchus gorbuscha).

The homing behaviour of salmon is a remarkable natural phenomenon, critical for shaping the ecology and evolution of populations yet the spatial scale at which it occurs is poorly understood. This study investigated the spatial scale and mechanisms driving homing as depicted by spawning site-choice behaviour in pink salmon (Oncorhynchus gorbuscha) in Prince William Sound, Alaska. Molecular pedigree analyses of over 30,000 adult spawners in four streams revealed that pink salmon exhibit fine-scale site fidelity within a stream, returning to within <100 m of their parents. Homing behaviours were driven in part by a salinity gradient between intertidal and freshwater environments, with individuals incubated in freshwater environments more than twice as likely to spawn upstream of tidal influence than those incubated in the intertidal. Our findings challenge the traditional view that pink salmon populations are genetically and phenotypically homogenous due to their short freshwater residency as juveniles and high rates of dispersal as returning adults (i.e. straying). This study has important implications for rates of inbreeding, local adaptation and gene flow within populations, and is particularly relevant to the management of salmon hatcheries, given the high incidence of hatchery-origin pink salmon, reared in freshwater hatchery environments, that stray into wild populations of Prince William Sound.

Assortative mating for reproductive timing affects population recruitment and resilience in a quantitative genetic model.

Quantitative models that simulate the inheritance and evolution of fitness-linked traits offer a method for predicting how environmental or anthropogenic perturbations can affect the dynamics of wild populations. Random mating between individuals within populations is a key assumption of many such models used in conservation and management to predict the impacts of proposed management or conservation actions. However, recent evidence suggests that non-random mating may be underestimated in wild populations and play an important role in diversity-stability relationships. Here we introduce a novel individual-based quantitative genetic model that incorporates assortative mating for reproductive timing, a defining attribute of many aggregate breeding species. We demonstrate the utility of this framework by simulating a generalized salmonid lifecycle, varying input parameters, and comparing model outputs to theoretical expectations for several eco-evolutionary, population dynamic scenarios. Simulations with assortative mating systems resulted in more resilient and productive populations than those that were randomly mating. In accordance with established ecological and evolutionary theory, we also found that decreasing the magnitude of trait correlations, environmental variability, and strength of selection each had a positive effect on population growth. Our model is constructed in a modular framework so that future components can be easily added to address pressing issues such as the effects of supportive breeding, variable age structure, differential selection by sex or age, and fishery interactions on population growth and resilience. With code published in a public Github repository, model outputs may easily be tailored to specific study systems by parameterizing with empirically generated values from long-term ecological monitoring programs.

Power of a dual-use SNP panel for pedigree reconstruction and population assignment.

The use of high-throughput, low-density sequencing approaches has dramatically increased in recent years in studies of eco-evolutionary processes in wild populations and domestication in commercial aquaculture. Most of these studies focus on identifying panels of SNP loci for a single downstream application, whereas there have been few studies examining the trade-offs for selecting panels of markers for use in multiple applications. Here, we detail the use of a bioinformatic workflow for the development of a dual-purpose SNP panel for parentage and population assignment, which included identifying putative SNP loci, filtering for the most informative loci for the two tasks, designing effective multiplex PCR primers, optimizing the SNP panel for performance, and performing quality control steps for downstream applications. We applied this workflow to two adjacent Alaskan Sockeye Salmon populations and identified a GTseq panel of 142 SNP loci for parentage and 35 SNP loci for population assignment. Only 50-75 panel loci were necessary for >95% accurate parentage, whereas population assignment success, with all 172 panel loci, ranged from 93.9% to 96.2%. Finally, we discuss the trade-offs and complexities of the decision-making process that drives SNP panel development, optimization, and testing.