Wolf depredation hotspots in France: Clustering analyses adjusting for livestock availability

International audienceAreas exhibiting high levels of predations on livestock generate conflicts between humans and large carnivores. Managers generally seek to identify these hotspots, in order to diagnose the causes that lead to hotspot formations and to provide financial or technical support to the involved livestock owners. When locating depredation hotspots, previous studies have not adjusted for livestock availability, making it difficult for managers to discriminate hotspots resulting from underlying livestock clusters from those due to other factors such as environmental factors. We studied hotspots of wolf depredation on sheep in France from the beginning of the natural wolf recolonisation in 1994 up to 2018. For each year, we applied the Ripley's K-function and Ripley's K inhom to determine the general depredation spatial pattern and the Kulldorff statistic to locate depredation hotspots. We showed that omitting livestock availability in these analyses led to flawed inference about the depredation pattern, and resulted in a substantial number of unidentified hotspots, including pastoral surfaces with low sheep availability. Our methodology provides reliable information for managers to understand the depredation pattern over space and time and to allocate resources

Critères de repérage précoce des enfants à risque de développer un surpoids

info:eu-repo/semantics/publishe

How to survey classical swine fever in wild boar (Sus scrofa) after the completion of oral vaccination? Chasing away the ghost of infection at different spatial scales

Additional file 1. “Disease” mapping model. This document details the hierarchical spatial Bayesian model computation