Human footprint differentially impacts genetic connectivity of four wide‐ranging mammals in a fragmented landscape

AIM: Maintaining connectivity is critical for long‐term persistence of wild carnivores in landscapes fragmented due to anthropogenic activity. We examined spatial genetic structure and the impact of landscape features on genetic structure in four widespread species—jungle cat (Felis chaus), leopard (Panthera pardus), sloth bear (Melursus ursinus) and tiger (Panthera tigris). LOCATION: Our study was carried out in the central Indian landscape, a stronghold in terms of distribution and abundance of large mammals. The landscape comprises fragmented forests embedded in a heterogeneous matrix of multiple land use types. METHODS: Microsatellite data from non‐invasively sampled individuals (90 jungle cats, 82 leopards, 104 sloth bears and 117 tigers) were used to investigate genetic differentiation. Impact of landscape features on genetic structure was inferred using a multimodel landscape resistance optimization approach. RESULTS: All four study species revealed significant isolation by distance (IBD). The correlation between genetic and geographic distance was significant only over a short distance for jungle cat, followed by longer distances for sloth bear, leopard and tiger. Overall, human footprint had a high negative impact on gene flow in tigers, followed by leopards, sloth bears and the least on jungle cats. Individual landscape variables—land use, human population density, density of linear features and roads—impacted the study species differently. Although land use was found to be an important variable explaining genetic structure for all four species, the amount of variation explained, and the optimum spatial resolution and the resistance values of different land use classes varied. MAIN CONCLUSIONS: As expected from theory, but rarely demonstrated using empirical data, the pattern of spatial autocorrelation of genetic variation scaled with dispersal ability and density of the study species. Landscape genetic analyses revealed species‐specific impact of landscape features and provided insights into interactions between species biology and landscape structure. Our results emphasize the need for incorporating functional connectivity data from multiple species for landscape‐level conservation planning.