Simulating forest plantation co-management with a multi-agent system

Simulating forest plantation co-management with a multi-agent system

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Article ID: iaor2007778
Country: Netherlands
Volume: 44
Issue: 5/6
Start Page Number: 535
End Page Number: 552
Publication Date: Sep 2006
Journal: Mathematical and Computer Modelling
Authors: ,
Keywords: simulation: applications
Abstract:

Co-management of forest resources is a process of governance that enables all relevant stakeholders to 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 neighboring people whose livelihoods depend on forest services and products 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. This paper proposes a framework for linking social, economic and biophysical dynamics to create multi-agent simulations and explore scenarios of collaboration for plantations. Multi-agent simulation is a branch of artificial intelligence that offers a promising approach to dealing with multi-stakeholder management systems, such as common pool resources. It provides a framework which allows analysis of stakeholders' (or agents') interactions and decision making. Each stakeholder has explicit communication capacities, behaviors and rationales from which emerge specific actions. The purpose of this modeling is to create a common dynamic representation to facilitate negotiations for growing trees. A system of governance involving multi-stakeholders, especially local communities and wood based industries, appears to offer the most promising pathway to accelerating plantation development, local community poverty alleviation and forest landscape improvement.

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