Landscape genetic connectivity in European wildcat ( Felis silvestris silvestris ): a matter of food, shelters and demographic status of populations

Conservation Genetics(2022)

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摘要
Understanding landscape impacts on gene flow is necessary to plan comprehensive management and conservation strategies of both the species of interest and its habitat. Nevertheless, only a few studies have focused on the landscape genetic connectivity of the European wildcat, an umbrella species whose conservation allows the preservation of numerous other species and habitat types. We applied population and landscape genetics approaches, using genotypes at 30 microsatellites from 232 genetically-identified wildcats to determine if, and how, landscape impacted gene flow throughout France. Analyses were performed independently within two population patches: the historical north-eastern patch and the central patch considered as the colonization front. Our results showed that gene flow occurred at large spatial scales but also revealed significant spatial genetic structures within population patches. In both population patches, arable areas, pastures and permanent grasslands and lowly fragmented forested areas were permeable to gene flow, suggesting that shelters and dietary resources are among the most important parameters for French wildcat landscape connectivity, while distance to forest had no detectable effect. Anthropized areas appeared highly resistant in the north-eastern patch but highly permeable in the central patch, suggesting that different behaviours can be observed according to the demographic context in which populations are found. In line with this hypothesis, spatial distribution of genetic variability seemed uneven in the north-eastern patch and more clinal in the central patch. Overall, our results highlighted that European wildcat might be a habitat generalist species and also the importance of performing spatial replication in landscape genetics studies.
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关键词
Felis s. silvestris,France,Landscape genetics,Linear mixed effects model,Maximum-likelihood population effect,Population genetics
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