LAUSR

Abstract Large scale spatial patterns of livestock predation risk from multiple co-predators are fundamental to applied conservation planning. Here, we examined important ecological, social, and landscape attributes explaining spatial patterns of human-carnivore interactions. We used a systematic grid-based framework, across an area of 14,200 km2 of sixteen Forest Divisions at the human-wildlife interface encompassing Protected Areas, Reserved Forest and Fringe Areas at the human-wildlife interface in the Eastern and Western Ghats, India. The data was collected on livestock depredation incidents from the tiger (Panthera tigris), leopard (Panthera pardus), and dhole (Cuon alpinus) for the past five years, through semi-structured interviews (n = 1460) of local communities. We examined socio-ecological (i.e. livestock abundance and forest dependency) and landscape attributes (i.e. forest cover, climates and topographic) influencing the depredation events from each carnivore species. We found that livestock predation risk by the tiger, leopard and dhole was driven by the size of livestock species, the dependency of local people on the forest, topography, proximity to water body and the forest boundary, precipitation, and forest cover. Risk of predation from leopard and dhole exhibited high spatial overlap, and predation by leopards was higher than dhole and tiger. Livestock predation by leopard and dhole was frequent in open areas of Reserved Forest and buffer zones, while that from tiger occurred in densely forested core regions of Protected Areas (PAs). Our predictive risk maps (ca. 22,525 km2) showed species-specific predation patterns, reflected ecological differences among large carnivores with regards to their habitat and spatial partitioning for domestic prey. Our predictive predation risk map and factors associated with livestock predations provides powerful visual guidance and tools for PA managers in developing multi-species conflict mitigation strategies. We recommend diversifying local economic livelihoods and benefit-sharing options for local communities to minimize their forest dependency.