人类世时代基于异质性生态服务付费的森林碳减排激励模式优化研究

The carbon emissions caused by deforestation and degradation have become one of main causes of global warming in the Anthropocene, thus it is necessary to promote the implementation of .Reducing Emissions from Deforestation and Degradation (REDD+) programs. Due to the diversities of investors/landowners, supervision modes of implementation process and asymmetric information, the incentive modes show a variety of heterogeneities in REDD+ mechanism. However, the existing researches fail to consider the heterogeneity issue systematically, which makes the designed REDD+ mechanism too idealistic. Therefore, this project will first identify and analyze three heterogeneities in the REDD+ incentive modes within the framework of ecosystem services in the telecoupled Anthropocene. Secondly, a Stackelberg dynamic game model of payments for ecosystem services will be established to address the heterogeneity of investors/landowners. Thirdly, a tripartite evolutionary game model will be established to address the heterogeneity of supervision modes. Finally, a multi-task principal-agent model and a signaling model will be established to address the heterogeneity of asymmetric information. The results of the project could be helpful for the optimization policy formulation of REDD+ incentive modes in the Anthropocene from the perspective heterogeneous payments for ecosystem services, and promote the construction of ecological civilization. Meanwhile, the results could also help to deepen the understanding of REDD+ incentive modes, and promote the integration development of management science and ecosystem services.

人类世时代毁林和退化所致排放已成为全球变暖的主因之一，因此有必要推动减少毁林和退化所致排放(REDD+)机制的实施。由于REDD+机制中投资者和土地所有者多元，监管方式各异，不对称信息多样，REDD+激励模式表现出多种异质性。然而现有研究未能系统考虑异质性问题，致使所设计的REDD+机制过于理想化。因此，本项目首先在生态服务人类世远程耦合框架内识别和分析REDD+激励模式中的三种异质性；其次，通过构建生态服务付费斯塔克伯格动态博弈模型解决投资者/土地所有者异质性；再次，通过构建三方演化博弈模型解决实施过程中的监管方式异质性；最后，通过构建多任务-委托代理模型和信号传递模型解决不对称信息异质性。项目成果不仅可从异质性生态服务付费角度，为人类世时代REDD+机制激励模式的优化政策制定提供依据，推进生态文明建设；而且有助于加深对REDD+机制激励模式的理解，推动管理科学与生态系统服务的融合发展。

通过奖励人们为人类社会提供有价值的生态系统服务而付出的努力，生态系统服务付费(PES)的概念已引起全球关注的用于改善环境管理的一种成本有效的手段。由于PES机制中利益相关者多元，监管方式各异，不对称信息多样，PES激励模式表现出多种异质性。然而现有研究未能系统考虑异质性问题，致使所设计的PES机制过于理想化。因此本项目首先在生态服务人类世远程耦合框架内识别并分析PES激励模式中的异质性，并通过构建生态服务付费斯塔克伯格动态博弈模型解决利益相关者异质性；其次，通过构建三方演化博弈模型解决实施过程中的监管方式异质性；再次，通过构建多任务-委托代理模型和信号传递模型解决不对称信息异质性；最后，通过构建激励协调博弈模型来优化流域生态系统服务付费中的激励机制。研究结果表明：首先，减少毁林和退化所致排放(REDD+)中的激励协调契约既可以激励行动者的减排行为又能够保证行动者的公平参与，因此是一种公平有效的机制；其次，REDD+激励话语凭借政府权力形成的外部权力结构会影响利益相关者的减排行为；再次，在估算和预测REDD+中减排量时，必须同时考虑参考碳储量和实际碳储量导致的不确定性；最后，中国流域生态系统服务付费将市场机制与政府干预相结合，使其成为中国生态治理市场化的表现之一，但在长期可能是不可持续的。项目研究成果不仅可从异质性角度，为人类世时代PES机制激励模式的优化政策制定提供依据，推进生态文明建设；而且有助于加深对PES机制激励模式的理解，推动管理科学与生态学的融合发展。

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