Understanding admixture patterns in supplemented populations: a case study combining molecular analyses and temporally explicit simulations in A tlantic salmon

Genetic admixture between wild and introduced populations is a rising concern for the management of endangered species. Here, we use a dual approach based on molecular analyses of samples collected before and after hatchery fish introduction in combination with a simulation study to obtain insight i...

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Veröffentlicht in:Evolutionary applications 2013-02, Vol.6 (2), p.218-230
Hauptverfasser: Perrier, Charles, Baglinière, Jean‐Luc, Evanno, Guillaume
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Sprache:eng
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Zusammenfassung:Genetic admixture between wild and introduced populations is a rising concern for the management of endangered species. Here, we use a dual approach based on molecular analyses of samples collected before and after hatchery fish introduction in combination with a simulation study to obtain insight into the mechanisms of admixture in wild populations. Using 17 microsatellites, we genotyped pre‐ and post‐stocking samples from four Atlantic salmon populations supplemented with non‐native fish to estimate genetic admixture. We also used individual‐based temporally explicit simulations based on realistic demographic and stocking data to predict the extent of admixture. We found a low admixture by hatchery stocks within prestocking samples but moderate to high values in post‐stocking samples (from 12% to 60%). The simulation scenarios best fitting the real data suggested a 10–25 times lower survival of stocked fish relative to wild individuals. Simulations also suggested relatively high dispersal rates of stocked and wild fish, which may explain some high levels of admixture in weakly stocked populations and the persistence of indigenous genotypes in heavily stocked populations. This study overall demonstrates that combining genetic analyses with simulations can significantly improve the understanding of admixture mechanisms in wild populations.
ISSN:1752-4571
1752-4571
DOI:10.1111/j.1752-4571.2012.00280.x