Abstract
Human-wildlife conflict (HWC) poses a pervasive global challenge, affecting livelihoods and threatening biodiversity. To better anticipate and mitigate HWC risk, we developed a large-scale predictive model using a Bayesian Belief Network (BBN). We surveyed 1,011 park rangers across 135 terrestrial protected areas in three Andean countries, documenting recent HWC incidents involving wildlife persecution or killing, livestock depredation, crop damage, or threats to human safety and property. We identified key drivers of HWC risk, including governance, wildlife acceptance, participation, and habitat quality. A sensitivity analysis revealed that enhancing governance and improving wildlife acceptance could reduce HWC risk by > 85%. The BBN model demonstrated scalability, effectively identifying strategies to reduce HWC risk at multiple scales, from individual protected areas to national networks. Our findings highlight the importance of strengthening governance, increasing wildlife acceptance, and enhancing community participation in conservation efforts. BBNs provide a flexible, cost-effective, and data-driven tool to guide protected areas and wildlife managers in monitoring, anticipating, and making informed decisions to mitigate conflict and promote coexistence.
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Acknowledgements
We sincerely thank Paul Aulestia, Carlos Nieto, and Angela Parra for their valuable contributions to this study. We also extend our gratitude to the technical staff of the protected area systems in Colombia, Ecuador, and Peru for their support. Special thanks to the Directorate of Protected Areas and Biodiversity of the Ministry of Water and Ecological Transition of Ecuador; the National Service of Natural Protected Areas (SERNANP) under the Ministry of Environment of Peru; and the National Natural Parks of Colombia under the Ministry of Environment and Sustainable Development for facilitating this research. This work was supported by the United States Geological Survey (USGS) Cooperative Fish and Wildlife Research Unit at Cornell University and SENESCYT. Data collection was made possible with the assistance of Marcela Torres, David Veintimilla, Erick Villalobos, Deyvis Huaman, Roberto Gutierrez, and Robert Marquez. Finally, we thank the reviewers for their insightful comments, which greatly improved this manuscript. Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government.
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García-Lloré, S., Stedman, R.C. & Fuller, A.K. Bayesian belief network model to predict human-wildlife conflict in protected areas.
Sci Rep (2026). https://doi.org/10.1038/s41598-026-56081-9
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DOI: https://doi.org/10.1038/s41598-026-56081-9
Keywords
- Human-wildlife conflict
- Bayesian belief network
- Protected areas
- Governance
- Wildlife acceptance
- Habitat quality
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