作者: Jean-Christophe Castella , Tran Ngoc Trung , Stanislas Boissau
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摘要: In Vietnam, the remarkable economic growth that resulted from doi moi (renovation) reforms was based largely on rural households had become new basic unit of agricultural production in early 1990s. The technical, economic, and social changes accompanied decollectivization process transformed production, resource management, land use, institutions defined access to resources their distribution. Combined with extreme biophysical, heterogeneity encountered northern mountains, these rapid led complexity agrarian dynamics today challenges traditional diagnostic approaches. Since 1999, a participatory simulation method has been developed disentangle cause-and-effect relationships between different driving forces use observed at scales. Several tools were combined understand interactions human natural systems, including narrative conceptual model, an agent-based spatial computational model (ABM), role-playing game, multiscale geographic information system (GIS). We synthesized into ABM named SAMBA-GIS knowledge generated above applied representative sample research sites. takes explicitly account dynamic among: (1) farmers' strategies, i.e., individual decision-making as function farm's profile; (2) define usage; (3) biophysical socioeconomic environment. next step consisted coupling GIS extrapolate application local management rules whole landscape. Simulations are initialized using layers GIS, e.g., 1990, accessibility, soil characteristics, etc., statistics available village level, population, ethnicity, livestock, etc. At each annual time step, landscape according decisions made by agent-farmers about how allocate such labor force, capital, productive activities, crops, gathering forest products, off-farm activities. simulations helped identify villages similar land-use change trajectories which same types technical and/or institutional innovations could be applied. Scenarios stakeholders assess potential impact base development. This adaptive approach gradually refined through researchers population.