Decoupling residents and dispersers from detection data improve habitat selection modelling: the case study of the wolf in a natural corridor

Resource selection analyses based on detection data are widely used to parametrize resistance surfaces identify ecological corridors. To successfully resistance, it is crucial decouple resident and disperser behaviours yet date connectivity studies using have not addressed this issue. Here, we decoupled of dispersing wolves by analysing collected within a natural corridor crossing human dominated plain in Italy. residents dispersers, ran Kernel Density analysis investigate whether clusters wolf points characterized sharply higher points’ density exist checked the areas outlined these (core areas) hold specific characteristics. Habitat was then performed compare intensity habitat carried out putative dispersers. We identified high-density cluster 30 outlining small core area stably located central part park. The dramatic differences R2 AUC models inside (R2 = 0.506; 0.952) outside 0.037; 0.643) corroborated hypothesis that effectively encloses belonging residents. Our results show through simple space use possible roughly discriminate between resident-behaving disperser-behaving individuals separately extremely different with strong effects parametrized from models.