Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming Yunnan 650223, China; E-mail:
Kunming College of Life Sciences, University of Chinese Academy of Sciences, Kunming Yunnan 650223, China.
Zool Res. 2018 Nov 18;39(6):406-412. doi: 10.24272/j.issn.2095-8137.2018.056. Epub 2018 May 31.
Understanding the spatial patterns of human-wildlife conflict is essential to inform management decisions to encourage coexistence, but it is constrained by the lack of spatially-explicit data. We collected spatially-implicit data of human-wildlife conflicts from 2009-2015 around Daxueshan Nature Reserve, Yunnan, China, and investigated the patterns and drivers of these conflicts. A questionnaire was also designed to capture local resident attitudes toward insurance-based compensation for the losses caused by targeted wildlife. We found that the Asiatic black bear () was the most conflict-prone animal around the reserve, followed by the rhesus macaque () and Southeast Asian sambar (). Conflicts were unevenly distributed among seasons, villages, and communities, with several grids identified as conflict hotspots. Poisson models revealed that human-bear conflicts were negatively related to distance to the reserve and proportion of forest, but positively correlated to the proportion of cropland. Binomial models showed that communities affected by crop depredation were positively correlated with the proportion of cropland and negatively correlated with distance to the reserve, whereas communities affected by livestock depredation were negatively correlated with the proportion of cropland. The insurance-based scheme has compensated over 90% of losses, to the satisfaction of 90.6% of respondents. Our results suggest that human-bear conflict could be potentially reduced by eliminating food crops near the reserve boundary and livestock grazing at conflict hotspots. In addition, the insurance-based scheme could be replicated at a broader scale with improvement in loss assessment.
了解人兽冲突的空间格局对于为促进共存而提供管理决策至关重要，但这受到缺乏空间明确数据的限制。我们收集了 2009 年至 2015 年期间中国云南大雪山自然保护区周边的人兽冲突的空间隐含数据，并调查了这些冲突的模式和驱动因素。我们还设计了一份问卷，以了解当地居民对基于保险的赔偿的态度，赔偿对象是针对目标野生动物造成的损失。我们发现，在保护区周围，亚洲黑熊（）是最易发生冲突的动物，其次是猕猴（）和东南亚水鹿（）。冲突在季节、村庄和社区之间分布不均，有几个网格被确定为冲突热点。泊松模型显示，人与熊的冲突与距离保护区和森林比例呈负相关，但与耕地比例呈正相关。二项式模型表明，受作物破坏影响的社区与耕地比例呈正相关，与距离保护区呈负相关，而受牲畜破坏影响的社区与耕地比例呈负相关。基于保险的计划已经对超过 90%的损失进行了赔偿，令 90.6%的受访者满意。我们的结果表明，通过消除保护区边界附近的粮食作物和在冲突热点地区的牲畜放牧，可以减少人与熊的冲突。此外，在改进损失评估的情况下，基于保险的计划可以在更大范围内复制。
