Combining incentives for pollination with collective action to provide a bundle of ecosystem services in farmland
A polycentric approach to ecosystem service (ES) governance that combines individual incentives for interdependent ES providers with collective action is a promising lever to overcome the decline in ES and generate win-win solutions in agricultural landscapes. In this study, we explored the effectiveness of such an approach by focusing on incentives for managed pollination targeting either beekeepers or farmers who were either in communication with each other or not. We used a stylized bioeconomic model to simulate (i) the mutual interdependency through pollination in intensive agricultural landscapes and (ii) the economic and ecological impacts of introducing two beekeeping subsidies and one pesticide tax. The findings showed that incentives generated a spillover effect, affecting not only targeted stakeholders but non-targeted stakeholders as well as the landscape, and that this effect was amplified by communication. However, none of the simulated types of polycentric ES governance proved sustainable overall: subsidies showed excellent economic but low environmental performance, while the tax led to economic losses but was beneficial for the landscape. Based on these results, we identified three conditions for sustainable ES governance based on communication between stakeholders and incentives: (i) strong mutual interdependency (i.e. few alternatives exist for stakeholders), (ii) the benefits of communication outweigh the costs, and (iii) the incentivized ES drivers are not detrimental to other ES. Further research is needed to systematize which combination of individual payments and collaboration are sustainable in which conditions.
Code (0)
등록된 구현이 없습니다.
Methods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
Causal Foundations of Collective Agency
A key challenge for the safety of advanced AI systems is the possibility that multiple simpler agents might inadvertently form a collective agent with capabilities and goals distinct from those of any individual. More ge…
Learning Incentive Structures for Cooperative Resilience in Multi-Agent Systems under Social Dilemmas
Multi-agent social dilemmas, such as the tragedy of the commons, capture settings where individual incentives conflict with collective well-being, making these systems highly vulnerable to collapse under disruptions. In …
Multi-agent Reinforcement LearningSimulation-based Modelling of Growth and Pollination of Greenhouse Strawberry
The cultivated strawberry Fragaria ananassa Duch. is widely planted in greenhouses in China. Its production heavily depends on pollination services. Compared with artificial pollination, bee pollination can significantly…
VNE Strategy based on Chaotic Hybrid Flower Pollination Algorithm Considering Multi-criteria Decision Making
With the development of science and technology and the need for Multi-Criteria Decision-Making (MCDM), the optimization problem to be solved becomes extremely complex. The theoretically accurate and optimal solutions are…
Decision MakingNetwork EmbeddingModelling Cooperation in Network Games with Spatio-Temporal Complexity
The real world is awash with multi-agent problems that require collective action by self-interested agents, from the routing of packets across a computer network to the management of irrigation systems. Such systems have…
Deep Reinforcement LearningManagementreinforcement-learningReinforcement Learning+1