Identifying wildlife corridors to restore population connectivity: An integration approach involving multiple data sources

Identification of wildlife corridors usually prioritizes ecological data while often overlooking the perspectives of local communities despite their relevance. This oversight may contribute to human-wildlife conflicts in surrounding areas. This study aims to demonstrate how multiple data sources and aspects can be integrated to identify wildlife corridors using the Dong Phayayen-Khao Yai Forest Complex as a case study. Suitable areas serving as additional wildlife corridors for the Asiatic black bear were identified, and appropriate management strategies to enhance the overall suitability of the wildlife corridor were determined. Firstly, road segments having the potential to serve as additional wildlife corridors were selected based on four criteria related to physical barriers. Then a Bayesian Belief Network was developed to assess the corridor suitability for each proposed road segment by including data from various sources and aspects (ecological data, the human dimension and landscape characteristics). Afterward, eight scenarios were tested to evaluate how they could impact the overall suitability. From seven potential road segments, only three segments showed high suitability to be additional wildlife corridors. Within the assessed 58 km² area, 13 km² (22 %) were identified as highly suitable for wildlife corridors under current situations. Improving human attitudes toward wildlife corridor construction emerged as the scenario that could increase the overall suitability the most (from 13 to 29 km²) while increasing human threats (hunting, wildlife pet trade, and vehicle collisions) was the scenario that reduced overall suitability the most (from 13 to 4 km²). Our framework in this study is practical, adaptable, and flexible for various decision-making processes. It can also be adapted to other areas and focal species by making relevant adjustments to align with specific landscapes and contexts.