In:
European Journal of Wildlife Research, Springer Science and Business Media LLC, Vol. 66, No. 6 ( 2020-12)
Abstract:
Following severe population decline and local extinction due to massive habitat destruction and persecution, wildcats have recently reappeared in several parts of Germany’s low mountain region. It remains unknown how this reemergence occurred, specifically if local populations have been overlooked at low densities or if the species has successfully spread across the highly fragmented anthropogenic landscape. In the central German Rhön Mountains, for instance, wildcats were believed to be extinct during most of the twentieth century, however, the species was recently detected and subsequent genetic monitoring found the presence of a sizeable population. In this study, we used microsatellite and SNP genotypes from 146 wildcat individuals from 2008 to 2017 across a ~ 15,000 km 2 area in the central German low mountain region to understand the population re-establishment of wildcats in the region. Bayesian clustering and subsequent analyses revealed that animals in the Rhön Mountains appear to be a mix from the two adjacent populations in the North and South of the area, suggesting a recent range expansion from two different directions. Both populations meet in the Rhön Biosphere Reserve, leading to an admixture of the northern, autochthonous, and the southern reintroduced wildcat population. While we cannot completely exclude the possibility of undetected population persistence, the high genetic homogeneity in the central German wildcat population and the lack of any signatures of past population decline in the Rhön favor a scenario of natural expansion. Our findings thus suggest that wildcats are well capable of rapid range expansion across richly structured landscape mosaics consisting of open land, settlements, and forest patches and document the potential of massive non-invasive genetic sampling when aiming to reconstruct the complex population and range dynamics of wildlife.
Type of Medium:
Online Resource
ISSN:
1612-4642
,
1439-0574
DOI:
10.1007/s10344-020-01433-7
Language:
English
Publisher:
Springer Science and Business Media LLC
Publication Date:
2020
detail.hit.zdb_id:
2140087-8
SSG:
12
SSG:
23
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