林业经济问题2026，Vol.46Issue(1)：36-48,13.DOI:10.16832/j.cnki.1005－9709.20250453
地方政府与林农森林生态保护的演化博弈研究
The Evolutionary Game of Forest Ecological Protection between Local Governments and Forest Farmers
摘要
Abstract
⑴ Background——Forest resources possess ecological,economic and social values simultaneously and hold significant strategic importance for China in achieving the"dual carbon"goals and advancing rural revital-ization.Existing studies on the mechanism of subsidy ineffectiveness mostly remain at the level of phenomenologi-cal description,lacking quantitative analysis that integrates the cost-benefit of local governments and forest farm-ers.Meanwhile,research on punishment mechanisms mostly adopts static settings,failing to consider the adapta-bility between the dynamic changes in forest farmers'behaviors and the intensity of punishments. ⑵ Methods——Based on an analysis of the behavioral logic of local governments and forest farmers in the process of forest ecological protection,this paper constructed an evolutionary game model between local govern-ments and forest farmers in forest ecological protection,and introduced a dynamic reward and punishment mecha-nism to analyze the evolutionary paths and constraint conditions of the strategic choices of both parties.Through a sensitivity analysis of two types of policy tools—ecological compensation and environmental penalties,it explored the impact of different parameters combinations on the stability of system evolution. ⑶ Results——First,there are two regulatory strategies adopted by local governments:one is the"benefit-oriented"regulation implemented when the incentive mechanism designed by the higher-level government leads to a positive net income for them;the other is the"responsibility-driven"regulation implemented by local govern-ments when performing their ecological protection duties and maintaining regional ecological security.Second,the static rewards with dynamic punishments mechanism demonstrates the optimal system stability and convergence performance.Compared with the other three reward and punishment mechanisms,this mechanism can effectively shorten the time required for the system to reach a stable state and reduce the fluctuation range of strategy selec-tion.Third,the increase in reward intensity can effectively stimulate the forest farmers'willingness to participate in the short term.However,the setting of the reward levels needs to carefully consider the resource input capacity of local governments.An ideal reward mechanism should focus on stabilizing expectations rather than relying on intensity stimulation. ⑷ Conclusions and Discussions——Based on the above research conclusions,the following policy sug-gestions are put forward:First,establish an incentive mechanism for local governments in forest protection and supervision.For higher-level governments,it is necessary to build a targeted and differentiated fiscal transfer pay-ment system.For areas such as collective forest regions and suburban forests,a mixed incentive approach should be developed.Second,optimize the interest structure of forest farmers and promote the protective utilization of forests.Local governments should restructure the profit distribution system in light of local conditions to ensure that the benefits of forest farmers from protective utilization of forests exceed those from destructive utilization.Additionally,they should establish punishment standards that match the severity of ecological damage.Third,improve the incentive and restraint mechanisms for forest protection.Adopt an institutional framework of"stable incentives+flexible restraints",meanwhile,the punishment mechanism must possess flexibility and deterrence to achieve long-term governance of forest ecosystems.关键词
森林生态保护/演化博弈/动态奖惩机制/地方政府/林农Key words
forest ecological protection/evolutionary game/dynamic reward and punishment mechanism/local governments/forest farmers分类
管理科学引用本文复制引用
赖静娴,梁海燕..地方政府与林农森林生态保护的演化博弈研究[J].林业经济问题,2026,46(1):36-48,13.基金项目
国家社会科学基金高校思政课研究专项课题(23VSZ100)、福建省社会科学研究基地重大项目(FJ2023JDZ031)、福建省社会科学研究基地重大项目(FJ2024MJDZ038)、2024年福建省自然科学基金面上项目(联合)(2024J01990) （23VSZ100）
