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

Dealing With the Complexity of Effective Population Size in Conservation Practice

Effective population size (Ne) is one of the most important parameters in evolutionary biology, as it is linked to the long-term survival capability of species. Therefore, Ne greatly interests conservation geneticists, but it is also very relevant to policymakers, managers, and conservation practitioners. Molecular methods to estimate Ne rely on various assumptions, including no immigration, panmixia, random sampling, absence of spatial genetic structure, and/or mutation-drift equilibrium. Species are, however, often characterized by fragmented populations under changing environmental conditions and anthropogenic pressure. Therefore, the estimation methods' assumptions are seldom addressed and rarely met, possibly leading to biased and inaccurate Ne estimates. To address the challenges associated with estimating Ne for conservation purposes, the COST Action 18134, Genomic Biodiversity Knowledge for Resilient Ecosystems (G-BiKE), organized an international workshop that met in August 2022 in Brașov, Romania. The overarching goal was to operationalize the current knowledge of Ne estimation methods for conservation practitioners and decision-makers. We set out to identify datasets to evaluate the sensitivity of Ne estimation methods to violations of underlying assumptions and to develop data analysis strategies that addressed pressing issues in biodiversity monitoring and conservation. Referring to a comprehensive body of scientific work on Ne, this meeting report is not intended to be exhaustive but rather to present approaches, workshop findings, and a collection of papers that serve as fruits of those efforts. We aimed to provide insights and opportunities to help bridge the gap between scientific research and conservation practice.

Genomic predictions under different genetic architectures are impacted by mating designs

Mating in animal communities must be managed in a way that assures the performance increase in the progenies without increasing the rate of inbreeding. It has currently become possible to identify millions of single nucleotide polymorphisms (SNPs), and it is feasible to select animals based on genome-wide marker profiles. This study aimed to evaluate the impact of five mating designs among individuals (random, positive and negative assortative, minimized and maximized inbreeding) on genomic prediction accuracy. The choice of these five particular mating designs provides a thorough analysis of the way genetic diversity, relatedness, inbreeding, and biological conditions influence the accuracy of genomic predictions. Utilizing a stochastic simulation technique, various marker and quantitative trait loci (QTL) densities were taken into account. The heritabilities of a simulated trait were 0.05, 0.30, and 0.60. A validation population that only had genotypic records was taken into consideration, and a reference population that had both genotypic and phenotypic records was considered for every simulation scenario. By measuring the correlation between estimated and true breeding values, the prediction accuracy was calculated. Computing the regression of true genomic breeding value on estimated genomic breeding value allowed for the examination of prediction bias. The scenario with a positive assortative mating design had the highest accuracy of genomic prediction (0.733 ± 0.003 to 0.966 ± 0.001). In a case of negative assortative mating, the genomic evaluation's accuracy was lowest (0.680 ± 0.011 to 0.899 ± 0.003). Applying the positive assortative mating design resulted in the unbiased regression coefficients of true genomic breeding value on estimated genomic breeding value. Based on the current results, it is suggested to implement positive assortative mating in genomic evaluation programs to obtain unbiased genomic predictions with greater accuracy. This study implies that animal breeding programs can improve offspring performance without compromising genetic health by carefully managing mating strategies based on genetic diversity, relatedness, and inbreeding levels. To maximize breeding results and ensure long-term genetic improvement in animal populations, this study highlights the importance of considering different mating designs when evaluating genomic information. When incorporating positive assortative mating or other mating schemes into genomic evaluation programs, it is critical to consider the complex relationship between gene interactions, environmental influences, and genetic drift to ensure the stability and effectiveness of breeding efforts. Further research and comprehensive analyzes are needed to fully understand the impact of these factors and their possible complex interactions on the accuracy of genomic prediction and to develop strategies that optimize breeding outcomes in animal populations.

Salmon hatchery strays can demographically boost wild populations at the cost of diversity: quantitative genetic modelling of Alaska pink salmon

Hatcheries are vital to many salmon fisheries, with inherent risks and rewards. While hatcheries can increase the returns of adult fish, the demographic and evolutionary consequences for natural populations interacting with hatchery fish on spawning grounds remain unclear. This study examined the impacts of stray hatchery-origin pink salmon on natural population productivity and resilience. We explored temporal assortative mating dynamics using a quantitative genetic model that assumed the only difference between hatchery- and natural-origin adults was their return timing to natural spawning grounds. This model was parameterized with empirical data from an intensive multi-generational study of hatchery-wild interactions in the world's largest pink salmon fisheries enhancement program located in Prince William Sound, Alaska. Across scenarios of increasing hatchery fish presence on spawning grounds, our findings underscore a trade-off between demographic enhancement and preservation of natural population diversity. While enhancement bolstered natural population sizes towards local carrying capacities, hatchery introgression reduced variation in adult return timing by up to 20%. Results indicated that hatchery-origin alleles can rapidly assimilate into natural populations, despite the reduced fitness of hatchery fish attributable to phenotypic mismatches. These findings elucidate the potential for long-term demographic and evolutionary consequences arising from specific hatchery-wild interactions, emphasizing the need for management strategies that balance demographic enhancement with the conservation of natural diversity.

Color polymorphism and mating trends in a population of the alpine leaf beetle Oreina gloriosa

The bright colors of Alpine leaf beetles (Coleoptera, Chrysomelidae) are thought to act as aposematic signals against predation. Within the European Alps, at least six species display a basal color of either blue or green, likely configuring a classic case of müllerian mimicry. In this context, intra-population color polymorphism is paradoxical as the existence of numerous color morphs might hamper the establishment of a search image in visual predators. Assortative mating may be one of the main factors contributing to the maintenance of polymorphic populations. Due to the marked iridescence of these leaf beetles, the perceived color may change as the viewing or illumination angle changes. The present study, conducted over three years, involved intensive sampling of a population of Oreina gloriosa from the Italian Alps and applied colorimetry and a decision tree method to identify the color morphs in an objective manner. The tertiary sex ratio of the population was biased in favor of males, suggesting that viviparous females hide to give birth. Seven color morphs were identified, and their frequencies varied significantly over the course of the study. Three different analyses of mating (JMating, QInfomating, and Montecarlo simulations) recognized a general trend for random mating which coexists with some instances of positive and negative assortative mating. This could help explain the pre-eminence of one morph (which would be favored because of positive selection due to positive assortative mating) in parallel with the persistence of six other morphs (maintained due to negative assortative mating).

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.