The importance of fine-scale predictors of wild boar habitat use in an isolated population

Predicting the likelihood of wildlife presence at potential wildlife-livestock interfaces is challenging. These interfaces are usually relatively small geographical areas where landscapes show large variation over small distances. Models of wildlife distribution based on coarse data over wide geographical ranges may not be representative of these interfaces. High-resolution data can help identify fine scale predictors of wildlife habitat use at a local scale and provide more accurate predictions of species habitat use. These data may be used to inform knowledge of interface risks, such as disease transmission between wildlife and livestock, or human-wildlife conflict. This study uses fine-scale habitat use data from wild boar (Sus scrofa) based on activity signs and direct field observations in and around the Forest of Dean in Gloucestershire, England. Spatial logistic regression models fitted using a variant of penalized quasi‐likelihood were used to identify habitat-based and anthropo...