Understanding the causal factors associated with human/livestock-large carnivore conflict and distribution of conflict risk is key to designing effective preventative and mitigation strategies.Spatial modelling of human-carnivore conflict has recently gained traction, and predictive maps have become a great tool to understand the distribution of present and future conflict risk.However, very few such studies consider scale and FEM-ADAPT use appropriate spatial modelling tools.We aimed to understand the ecological correlates of human-tiger (Panthera tigris) conflict, predict livestock predation risk by reintroduced tigers in Panna Tiger Reserve, Central India and understand the prey-predator dynamics behind the conflict.
We modelled livestock kill as a function of various tiger relevant ecological variables at multiple scales employing spatially explicit statistical tools.As a first step, we used geostatistical modelling to create raster layers of covariates (prey, cover, human activities), following which we did univariate scaling.We then modelled livestock loss by tiger using a geoadditive Fender Flares model.Employing this model, we predicted and mapped conflict risk probabilities within our study site.
It was found that prey and shrub cover both selected at a fine scale, were key ecological determinants of human-tiger conflict.Prey showed an inverse relationship while shrub showed non-linear relationship with livestock predation.Which lead us to conclude that in habitats where optimum ambush cover is available but prey presence is low at fine-scale, carnivores are more likely to depredate domestic livestock since livestock have lost most of their anti-predator behaviours.Livestock kill by tiger is thus a culmination of predator choice and foraging tactics, and prey vulnerability and defence mechanism.
The spatially explicit predation risk map produced in this study can guide adequate human-tiger conflict prevention measures.