Ecological and temporal drivers of human-gaur conflict in Tamil Nadu, India
Abstract Human–wildlife conflict (HWC) is one of the most pressing conservation challenges, particularly in shared landscapes where both humans and wildlife are adversely affected. Despite various global mitigation efforts, the frequency of HWC continues to rise. Among the conflict-prone species, th...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Springer
2025-07-01
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| Series: | Discover Animals |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s44338-025-00100-y |
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| Summary: | Abstract Human–wildlife conflict (HWC) is one of the most pressing conservation challenges, particularly in shared landscapes where both humans and wildlife are adversely affected. Despite various global mitigation efforts, the frequency of HWC continues to rise. Among the conflict-prone species, the Gaur (Bos gaurus) has increasingly been involved in such interactions across southern India. To support the development of long-term mitigation strategies for Human–Gaur Conflict (HGC), we conducted a comprehensive study using compensation records related to crop damage, human injury, and death across 48 forest divisions in Tamil Nadu between 2016 and 2024. We analyzed spatial and temporal trends by categorizing data by forest division and date of occurrence and predicted conflict risk zones using an ensemble modeling approach via the sdm package. Environmental variables related to climate, vegetation, terrain, and anthropogenic disturbance were used to test determinants of conflict risk. Our findings reveal that conflict intensity was highest in the Nilgiri division, followed by Dharmapuri and Kodaikanal. Crop damage was the predominant type of conflict, followed by human injuries, with incident peaks occurring from December to March. Response curve analysis revealed that elevation, proximity to forests and water, and human modification were strong positive predictors of conflict risk. In contrast, greater distance from roads and built-up areas, as well as higher terrain ruggedness, were associated with reduced conflict. The model predicted that 18,335 km² (14.1% of Tamil Nadu’s area) falls under conflict risk zones. This study offers critical insights into the spatial ecology of HGC and demonstrates the utility of predictive modeling for identifying high-risk areas, informing proactive mitigation strategies for conservation managers. |
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| ISSN: | 3004-894X |