, Volume 12, Issue 5, pp 1215-1227
Date: 12 May 2011

Empirical assessment of software efficiency and accuracy to detect introgression under variable stocking scenarios in brook charr (Salvelinus fontinalis)

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Abstract

Stocking wild populations with domesticated fish is a common practice that promotes variable levels of introgression depending on the stocking intensity. The detection of hybridization and introgression has recently benefited from the application of Bayesian techniques implemented in various software. However, few studies have assessed their efficiency under various scenarios of stocking in the wild. The objective of this study is to assess quantitatively the effects of using two of the most widely distributed software, Structure and NewHybrids, on the level of introgression detected in wild brook charr (Salvelinus fontinalis) subjected to variable stocking intensities. We first found differences in the efficiency of software assignments based on simulated individuals, with Structure performing better than NewHybrids. However, NewHybrids showed higher assignments accuracy than Structure for the same sets of individuals. Thus, our results suggest that these software should be used in combination to assess the effects of stocking. Indeed, Structure is particularly relevant to evaluate the presence of hybrids in wild populations, whereas NewHybrids might be preferred to accurately assess the number of hybrids present in a sample. When applied to wild populations, Structure assigned more individuals than NewHybrids to the wild category. Moreover, the proportions of assigned domestic and hybrid individuals were higher in more intensively stocked lakes, whereas the opposite trend was observed for wild individuals.