Influence of sampling scheme on the inference of sex-biased gene flow in the American badger (Taxidea taxus)

Population genetics has fueled a substantial growth in studies of dispersal, a life-history trait that has important applications in ecology and evolution. Mammals typically exhibit male-biased gene flow, so this pattern often serves as a null hypothesis in empirical studies. Estimation of dispersal...

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Published inCanadian journal of zoology Vol. 90; no. 10; pp. 1231 - 1242
Main Authors Kierepka, E.M., Latch, E.K., Swanson, B.J.
Format Journal Article
LanguageEnglish
Published Ottawa NRC Research Press 01.10.2012
National Research Council of Canada
Canadian Science Publishing NRC Research Press
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ISSN1480-3283
0008-4301
1480-3283
0008-4301
DOI10.1139/z2012-094

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Summary:Population genetics has fueled a substantial growth in studies of dispersal, a life-history trait that has important applications in ecology and evolution. Mammals typically exhibit male-biased gene flow, so this pattern often serves as a null hypothesis in empirical studies. Estimation of dispersal using population genetics is not without biases, so we utilized a combination of population genetic methods and simulations to evaluate gene flow within the American badger (Taxidea taxus (Schreber, 1777)), a highly elusive and poorly understood mustelid. A total of 132 badgers captured between 2001 and 2002 were genotyped at nine microsatellite loci to investigate fine-scale genetic structure consistent with philopatry in females and dispersal in males. Resultant genetic patterns were largely consistent with a panmictic population with little evidence for sex-biased dispersal, and simulations confirmed that our sampling scheme did not substantially impact our statistics. An overall deficiency of heterozygotes was observed across the Lower Peninsula, which indicates either a Wahlund effect, mixing of separate populations, or inbreeding. Our study emphasizes the importance in deciphering between actual behavioral mechanisms and sampling effects when interpreting genetic data to understand other factors that influence dispersal like population density and territoriality.
Bibliography:http://dx.doi.org/10.1139/z2012-094
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ISSN:1480-3283
0008-4301
1480-3283
0008-4301
DOI:10.1139/z2012-094