Prioritizing areas for wolf management in Austria by modelling potential habitat and depredation risk

The recovery of wolf populations across Europe has reignited human–wildlife conflicts, particularly in countries such as Austria, where wolves have been absent for more than a century. Livestock depredation remains one of the primary sources of tension, and effective management requires a solid spatial basis for planning. In this study, we laid the groundwork for evidence‐based management by prioritizing areas for wolf management through spatially explicit modelling of habitat suitability and livestock depredation. We developed a species distribution model (SDM) to predict potential wolf habitat and a depredation susceptibility model (DSM) to identify areas of potential livestock predation. Both models were built using the MaxEnt algorithm, based on extensively filtered wolf presence records (n = 124) and depredation cases (n = 109) together with a comprehensive set of 37 environmental, topographic, anthropogenic and livestock‐related variables. The SDM indicated that approximately 47% of Austria constitutes suitable wolf habitat, predominantly in forested areas. The DSM identified 23% of Austria as areas of significant depredation susceptibility, driven primarily by livestock presence and proximity to forests. Combining the SDM and DSM, we developed an asymmetrical prioritization index (sustainability‐adjusted risk index, SARI), to pinpoint areas of higher management focus. The SARI revealed ~ 8000 km ² (9.5% of Austria) of overlapping habitat suitability and depredation susceptibility, with the top 10th percentile indicating areas requiring urgent management intervention. These areas are concentrated at alpine pastures and open landscapes adjacent to or surrounded by forests, particularly in Tyrol and Carinthia. Our findings emphasize the need for spatial planning of targeted management strategies, including livestock protection measures and coexistence initiatives, to mitigate conflicts in hotspot areas and support sustainable wolf population recovery. By providing spatially explicit data, this research offers a valuable tool for resource allocation and evidence‐based decision‐making, paving the way for effective coexistence between humans and wolves.