School of Public Administration, Guangzhou University, Guangzhou 510006, China; Institute of Rural Revitalization, Guangzhou University, Guangzhou 510006, China.
School of Management and Economics, Beijing Institute of Technology, Beijing 100081, China; Yangtze Delta Region Academy (Jiaxing), Beijing Institute of Technology, Jiaxing 314001, China.
J Environ Manage. 2024 Jun;360:120958. doi: 10.1016/j.jenvman.2024.120958. Epub 2024 May 13.
To safeguard aquatic ecosystems and fishery resources while facilitating cooperative engagement between local governments and fishermen, an evolutionary game model featuring both stakeholders has been constructed in this study. The model examines the degree of compliance with ecological restoration policies linked to fishing bans, as well as the adaptive strategies of different types of fishermen with varied incentives while simulating the ecological restoration policy under diverse scenarios. The findings suggest that: (1) Compliance with the fishing ban policy among fishermen is determined by their economic interests, environmental preferences, and government regulations, while its enforcement by local authorities is influenced by regulatory costs, political performance, and reputation. (2) Variations in the ecological restoration policy of fishing bans result from several factors, including punitive measures and compensation. The higher the penalty, the greater the chance of compliance among fishermen, and the higher the restoration degree of the watershed ecosystem. Conversely, the higher the compensation, the more satisfied the fishermen are with the fishing ban policy, and the smoother the transformation of their livelihoods. (3) To enhance the effectiveness and sustainability of fishing bans, it is essential to consider the interests of multiple stakeholders and adopt a coordination mechanism that facilitates the design of a reasonable and effective incentive-compatible system, thereby increasing the fairness and acceptability of the policy. This study provides a new theoretical framework and methodology applicable to ecological restoration policies for fishery closures on a global scale, accompanied by robust data support and theoretical guidance for developing and implementing fishery closure policies.
为了保护水生态系统和渔业资源，同时促进地方政府和渔民之间的合作，本研究构建了一个包含两个利益相关者的演化博弈模型。该模型考察了渔民遵守与禁渔相关的生态恢复政策的程度，以及不同激励机制下不同类型渔民的适应策略，同时模拟了不同情景下的生态恢复政策。研究结果表明：（1）渔民遵守禁渔政策的程度取决于他们的经济利益、环境偏好和政府规定，而地方当局的执行情况则受到监管成本、政治绩效和声誉的影响。（2）禁渔生态恢复政策的变化是由多种因素引起的，包括惩罚措施和补偿。惩罚力度越大，渔民遵守政策的可能性就越大，流域生态系统的恢复程度就越高。相反，补偿越高，渔民对禁渔政策的满意度就越高，生计转型就越顺利。（3）为了提高禁渔政策的有效性和可持续性，必须考虑多个利益相关者的利益，并采用协调机制，设计合理有效的激励相容制度，从而提高政策的公平性和可接受性。本研究为全球范围内的渔业禁捕生态恢复政策提供了新的理论框架和方法，为制定和实施渔业禁捕政策提供了强有力的数据支持和理论指导。
