Harnessing the Climate Commons: An Agent-based Modelling Approach to Reduce Carbon Emission from Deforestation and Degradation


"Humans have created a worldwide tragedy through free access to the global common atmosphere. Forest land use change contributes 18% of greenhouse gas emissions, which cause global warming. The 15th Conference of the Parties in Copenhagen increased political commitment to reduce emission from deforestation and degradation and to enhance carbon stocks (REDD+). However, government sectors, political actors, business groups, civil societies, tree growers and other interest groups at different levels may support or reject REDD+. This paper describes REDD+ dynamics through the following methods: identifying key actors that influence REDD+ policy; categorizing their objectives and interests, types of rationality and policy preferences; pointing out the strategies they used to fulfill their goals and simulating their actions and behaviors with an agent-based modelling approach. Through analysis of actors, arenas and institutions, various possible REDD+ options are explored. The model simulates: (1) how providers are likely to decrease or increase carbon stocks on their landscapes for their livelihoods under ‘business as usual’ institutions; (2) how they are likely to negotiate with potential buyers to implement REDD+, with regards to the involvement of brokers (governments or nongovernmental organizations); and (3) how they are likely to implement REDD+ after the agreement. The model has been/was developed as a spatially explicit model to consider the complexity of REDD+ target landscapes. The simulation results are examined against the 3E+ criteria, i.e. effectiveness in carbon emission reduction, cost efficiency and equity among involved stakeholders and co-benefit of other activities. This study took the Jambi landscape in Indonesia as a case/case study. The results explain why REDD+ works and does not work, who wins and loses, and develops scenarios for REDD+ institutional arrangements which would help to harness the global commons of climate change."



climate change, deforestation, agent-based computational economics, institutions