Association between attitudes toward wildlife and patterns of risk of human–wildlife conflict near Giant Panda National Park

Abstract

Human–wildlife conflict (HWC) is an escalating humanitarian issue and a conservation concern. In terms of protection and management, areas at high risk of HWC are not necessarily afforded the same resources as areas prioritized for protection. To improve allocation of limited protection resources and HWC mitigation efficiency, we determined management priorities based on HWC risk and people's attitudes toward wildlife around the Giant Panda National Park. We constructed an ensemble species distribution model with 1959 species’ distribution loci and 337 conflict event records. This model was used to simulate the spatial distribution patterns of HWC risk and to evaluate the influence of diverse environmental factors. A survey of people's attitudes toward wildlife was conducted in 155 villages around the Giant Panda National Park. Priority areas for HWC management were concentrated near protected areas, where wildlife habitats and populations were recovering and expanding. We obtained 947 questionnaires, which showed that some residents were highly aware of conservation and had a high tolerance for wildlife, even when they were living in areas at high risk of HWC. However, people who had encountered conflicts with wild boar were more likely to have negative attitudes toward other wildlife, even giant pandas ( Ailuropoda melanoleuca ). Thus, HWC may lead to the generalization of negative attitudes toward wildlife conservation. In our study area, environmental (e.g., building fences and changing crop types) and social measures (e.g., insurance and ecocompensation) have been implemented to mitigate HWC. Our results can provide an important basis for the allocation of compensation resources and improvement of HWC management in areas of high conservation priority. Future studies should further explore how to develop more personalized HWC management plans based on the characteristics of different regions.

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