Governing forest plantation to reduce poverty and improve forest landscape: a multiagent simulation approach

Abstract

Good forest governance lets all relevant stakeholders participate in the decision-making processes. Illegal logging and forest degradation are currently increasing, and logging bans are ineffective in reducing forest degradation. At the same time interest in forest plantations and concern about poverty problems of people adjacent to forests continue to increase rapidly. Governments have identified the development of small forest plantations as an opportunity to provide wood supplies to forest industries and to reduce poverty. However, the development of small plantations is very slow due to an imbalance of power and suspicion between communities and large companies. Current regulations do not offer many links amongst various stakeholders. The paper proposes a framework to link up social, economic and biophysical dynamics using multiagent simulation to explore scenarios of collaboration for plantations. Multiagent simulation is a branch of artificial intelligence that offers a promising approach to deal with multi stakeholder management systems, such as the case involving common pool of resources. It provides a framework, which allows analysis of stakeholders’ (or agents’) decisions in interaction. Each stakeholder has explicit communication capacities, behaviors and rational from which emerge specific actions. The purpose of this modeling is to create a common dynamic representation to facilitate negotiations to grow trees. Collaborations involving multistakeholders, especially local communities and wood based industries, appeared to offer the most promising pathway to accelerate plantation development toward local communities’ poverty alleviation and forest landscape improvement.