Human–wildlife conflict patterns and hotspot prediction in the southern foothills of the Daba Mountains, China

Abstract

The Daba Mountain area is recognized as one of the global biodiversity hotspots. In recent years, human–wildlife conflicts (HWCs) in this region have intensified significantly. Understanding and mitigating the damage caused by wildlife is crucial for maintaining ecological balance and enhancing public welfare. We analyzed the current status of HWCs in the southern foothills of the Daba Mountains through semi-structured interviews and field surveys. Additionally, using the collected data on HWC occurrences, we predicted HWC hotspots using the maximum entropy (MaxEnt) model. The results: (1) A total of 449 cases of actual HWC incidents were investigated, primarily involving wild boars (Sus scrofa; 81.96%) and Asiatic black bears (Ursus thibetanus; 18.04%). The main types of HWC included crop destruction and attacks on beehives. (2) Incidents of damage caused by wild boars and Asiatic black bears were concentrated in the summer months, particularly from June to August. (3) In the study area, 21 out of 25 townships reported HWC cases. Notably, the townships of Fuxing, Gaoyan and Gaoguan were identified as the most affected, with Gaoyan and Fuxing experiencing the highest amounts of loss. (4) The variable of DTP (Distance to Protected Area) was found to have the greatest influence on the hotspot distributions of HWCs. The hotspot zone exhibited a strip-like distribution along the northwest–southeast axis in the central part of the study area. The total area of the HWC hotspots was 1352.56 km2. The largest hotspot areas were located in Xiuqi Town, Gaoyan Town, and Houping Township, accounting for 13.26%, 12.01%, and 7.83% of the total hotspot area, respectively. HWC hotspots require robust management measures to mitigate wildlife damage to local communities and enhance indigenous people’s engagement in wildlife conservation. Implementation of physical measures and compensation schemes may be necessary in these hotspots to alleviate the financial burden on indigenous populations. Our findings may provide valuable insights for the future formulation of biodiversity conservation policies and HWC mitigation strategies in the Daba Mountains.