Genetic Differentiation Of Wild Boar Populations In A Region Endangered By African Swine Fever

For areas at risk for African swine fever (ASF) introduction from neighboring regions, it is important for epidemic control to know how wild boar (Sus scrofa) dispersion dynamics could be used to combat the spread of ASF. In this regard, long-term information based on population genetic data makes an important contribution. We selected our study area as Rhineland-Palatinate, Germany, because it had a high density of wild boars and was threatened by ASF via infected wild boars from neighboring Belgium. On an area of around 20,000 km(2), we collected almost 1,200 blood samples from 22 wild boar hunting grounds. The study area included a network of potential barriers to movement, including roads and rivers. We assessed genetic differentiation based on microsatellite data. We used 2 spatial (Bayesian Analysis of Population Structure [BAPS] and TESS) and 1 non-spatial (STRUCTURE) Bayesian model-based approaches to analyze the data. Each of the algorithms detected 4 clusters with different cluster compositions in different areas and identified the highest degrees of differentiation between hunting grounds east and west of the Rhine River, between Pfalz and Eifel-Hunsruck, and to a lesser degree between Westerwald and Taunus and between Eifel and Hunsruck. Thus, genetic evidence suggests barriers of different strength that might be helpful in a setup of complex and expensive measures against the spread of animal diseases such as ASF. The described approach could also provide valuable information for other threatened regions to contain ASF. (c) 2021 The Authors. The Journal of Wildlife Management published by Wiley Periodicals LLC on behalf of The Wildlife Society.