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A quantitative analysis of public preferences for the wild boar management in urban and rural China
- Source :
- Global Ecology and Conservation, Vol 41, Iss , Pp e02353- (2023)
- Publication Year :
- 2023
- Publisher :
- Elsevier, 2023.
-
Abstract
- Human-wildlife conflict is rapidly evolving in response to significant ecological, social, and economic changes affecting society globally. Developing objective and acceptable resolution strategies is challenging because of divergence in perceptions and understandings of human-wildlife conflict between urban and rural populations, and this disparity is increasing with rapid urbanization. In this study, we explore preferences for wild boar conflict management in China using a mixed methods approach of a survey, choice experiments, and interviews. We found that significant differences in the preferences of wild boar management exist between rural and urban residents. The majority of rural residents preferred hunting whereas most urban residents in cities remote from the conflict preferred non-hunting measures. However, we found that economic cost played an important role in influencing public preferences for management measures. The urban population had positive preferences for hunting if they were required to pay an environmental tax to compensate farmers for crop damage when asked to consider their preferred management strategy package. We consider that the current management of hunting wild boar in China requires improvement, and we argue that China should adjust the current hunting management policy to take into account the benefits of wild boar population control and the economic development of the surrounding rural areas.
Details
- Language :
- English
- ISSN :
- 23519894
- Volume :
- 41
- Issue :
- e02353-
- Database :
- Directory of Open Access Journals
- Journal :
- Global Ecology and Conservation
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.6367bc0de0194348a4db135afda04573
- Document Type :
- article
- Full Text :
- https://doi.org/10.1016/j.gecco.2022.e02353