Simulating forest plantation co-management with a multi-agent system. (English) Zbl 1132.91587

Summary: 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 appearing to offer the most promising pathway to accelerating plantation development, local community poverty alleviation and forest landscape improvement.


91B76 Environmental economics (natural resource models, harvesting, pollution, etc.)
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[1] SAFODA, Sabah Forestry Development Authority, (n.d.), (accessed 25.02.03)
[2] CIRAD, Natural resources and multi-agent simulations. centre de coopération internationale en recherche agronomique pour le Développement, (2001), (accessed 25.02.02)
[3] Bousquet, F.; Barreteau, O.; Le Page, C.; Mullon, C., An environmental modeling approach: the use of multi-agent simulations, ()
[4] Bousquet, F.; Bakam, I.; Proton, H.; Le Page, C., CORMAS: common-pool resources and multi-agent systems, Lecture notes in artificial intelligence, 1416, 826-838, (1998)
[5] Barreteau, O.; Bousquet, F., SHADOC: A multi-agent model to tackle variability of irrigated systems, Annals of operations research, 94, 139-162, (2000) · Zbl 0960.90003
[6] Thebaud, O.; Locatelli, B., Modeling the emergence of resource sharing conventions: an agent-based approach, The journal of artificial societies and social simulation, 4, 2, (2001), (accessed 25.02.03)
[7] Rouchier, J.; Bousquet, F.; Barreteau, O.; Le Page, C.; Bonnefoy, J.L., Multi-agent modelling and renewable resources issues: the relevance of shared representations for interacting agents, (), 181-197
[8] Bousquet, F.; Le Page, C.; Bakam, I.; Takforyan, A., Multi-agent simulations of hunting wild meat in a village in eastern cameroon, Ecological modelling, 138, 331-346, (2001)
[9] Rouchier, J.; Bousquet, F.; Requier-Dejardins, M.; Antona, M., A multi-agent model for transhumance in north cameroon, Journal of economic dynamics and control, 527-559, (2001) · Zbl 0956.91060
[10] d’Aquino, P.; Le Page, C.; Bousquet, F.; Bah, A., A novel mediating participatory modelling: the self-design process to accompany collective decision making, International journal agricultural resources, governance and ecology, 12, 1, 59-74, (2002)
[11] Brown, D.; Schreckenberg, K.; Shepherd, G.; Wells, A., Forestry as an entry point for governance reform, ODI forestry briefing, 1, (2002)
[12] Kaimowitz, D., The political economy of environmental policy reform in Latin America, Development and change, 27, 3, 433-452, (1996)
[13] Plumptre, T.; Graham, J., Governance and good governance: international and aboriginal perspectives, (1999), Institute On Governance
[14] Borrini-Feyerabend, G.; Farvar, M.T.; Nguinguiri, J.C.; Ndangang, V.A., Co-management of natural resources: organising, negotiating and learning-by-doing, (2000), GTZ and IUCN Kasparek Verlag. Heidelberg, Germany
[15] J. Mayers, S. Bass, D. Macqueen, The Pyramid: A diagnostic and planning tool for good forest governance, IIED (2002)
[16] Colfer, C.J.P.; Brocklesby, M.A.; Diaw, C.; Etuge, P.; Günter, M.; Harwell, E.; McDougall, C.; Porro, N.M.; Prabhu, R.; Salim, A.; Sardjono, M.A.; Tchikangwa, B.; Tiani, A.M.; Wadley, R.; Woelfel, J.; Wollenberg, E., The BAG: basic assessment guide for human well-being, ()
[17] Bernard, H.R., Research methods in anthropology: qualitative and quantitative approaches, (1994), Sage Thousand Oaks, CA
[18] Grant, J.W.; Pedersen, E.K.; Marin, S.L., Ecology and natural resource management, ()
[19] Muller, J.P., MAS in the field of computer science, ()
[20] Sen, S.; Weiss, G., Learning in multiagent systems, ()
[21] Barreteau, O.; Bousquet, F.; Attonaty, J., Role-playing games for opening the black box of multi-agent systems: method and lessons of its application to senegal river valley irrigated systems, Journal of artificial societies and social simulation, 4, 2, (2001), (accessed 20.05.01)
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