Main roads and land cover shaped the genetic structure of a Mediterranean island wild boar population

Abstract

Abstract Patterns of genetic differentiation within and among animal populations might vary due to the simple effect of distance or landscape features hindering gene flow. An assessment of how landscape connectivity affects gene flow can help guide management, especially in fragmented landscapes. Our objective was to analyze population genetic structure and landscape genetics of the native wild boar (Sus scrofa meridionalis) population inhabiting the island of Sardinia (Italy), and test for the existence of Isolation‐by‐Distance (IBD), Isolation‐by‐Barrier (IBB), and Isolation‐by‐Resistance (IBR). A total of 393 Sardinian wild boar samples were analyzed using a set of 16 microsatellite loci. Signals of genetic introgression from introduced non‐native wild boars or from domestic pigs were revealed by a Bayesian cluster analysis including 250 reference individuals belonging to European wild populations and domestic breeds. After removal of introgressed individuals, genetic structure in the population was investigated by different statistical approaches, supporting a partition into five discrete subpopulations, corresponding to five geographic areas on the island: north‐west (NW), central west (CW), south‐west (SW), north‐central east (NCE), and south‐east (SE). To test the IBD, IBB, and IBR hypotheses, we optimized resistance surfaces using genetic algorithms and linear mixed‐effects models with a maximum likelihood population effects parameterization. Landscape genetics analyses revealed that genetic discontinuities between subpopulations can be explained by landscape elements, suggesting that main roads, urban settings, and intensively cultivated areas are hampering gene flow (and thus individual movements) within the Sardinian wild boar population. Our results reveal how human‐transformed landscapes can affect genetic connectivity even in a large‐sized and highly mobile mammal such as the wild boar, and provide crucial information to manage the spread of pathogens, including the African Swine Fever virus, endemic in Sardinia.

Keywords

• gene flow
• landscape genetics
• microsatellites
• population structure
• Sardinia
• Sus scrofa meridionalis