Robust mapping of human–wildlife conflict: controlling for livestock distribution in carnivore depredation models

Shifting human–wildlife conflict towards coexistence requires a robust understanding of where happens and why. Spatial models livestock depredation by wild predators commonly identify hotspots in areas are most abundant (e.g. nearer villages or pasture). This may reflect underlying distribution, rather than imply these inherently risky for livestock. limits the predictive power their usefulness mitigation carnivore conservation. Here, we build spatial both cattle (530 attacks mostly lions hyenas; 2009-2013), presence (14 GPS-collared herds; 2010-2012) near Hwange National Park, Zimbabwe. We use Bayes’ theorem to combine quantify risk as conditional probability given presence. Our raw predicted higher rates was more likely (near open habitats). By contrast, our model further from human activity dense vegetation (where were expected low presence). Risk has also increased sharply protected (core habitat). formulation captures high-risk those accessible (i.e. vulnerable) opposed simply they available (as much previous work). make recommendations protection conservation based on quantification risk, such avoid herding which prioritize protection. approach be profitably applied guide safer grazing other contexts movement data available. hope that concepts methods develop here will help advance future study generally.