Participatory Simulation of Land-Use Changes in the Northern Mountains of Vietnam: the Combined Use of an Agent-Based Model, a Role-Playing Game, and a Geographic Information System

By Jean-Christophe Castella, Tran Ngoc Trung, Stanislas Boissau. 2005

398 citations recorded by the source corpus.

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

Subfields: Global and Planetary Change, Management, Monitoring, Policy and Law

View Paper: https://www.semanticscholar.org/paper/cb4c543bf127910a18fd803a77f0feb2cee39df9

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Citations in the corpus

The sustainable development oxymoron: quantifying and modelling the incompatibility of sustainable development goals (2016, neutral): “Other more explorative approaches such as agent-based simulations (Castella et al. 2005), participatory observations and focus groups (Cuthill 2002) or case studies (Crépin 2003; Dearing et al.”
Modeling human decisions in coupled human and natural systems: Review of agent-based models (2012, background): “…of using this approach has been reported from several 411 study regions such as Northeast Thailand (Naivitit et al., 2010), the Colombian Amazonian region (Pak 412 and Brieva, 2010), Senegal (D'Aquino et al., 2003), and Vietnam (Castella et al., 2005b; see D'Aquino et 413 al., 2002 for review).”
Describing human decisions in agent-based models - ODD + D, an extension of the ODD protocol (2013, background): “Examples for coincidence in models can be the random initialisation of the values of agents’ state variables (e.g. Balmann, 1997; Matthews, 2006), location of households on a map (e.g. Castella et al., 2005) or market-prices that influence agent decisions (e.g. Janssen et al., 2000).”
Companion Modeling, Conflict Resolution, and Institution Building: Sharing Irrigation Water in the Lingmuteychu Watershed, Bhutan (2006, methodology): “Several applications have been already developed (d’Aquino et al. 2003, Barnaud et al. 2006, Barreteau and Bousquet 2000, Castella et al. 2005, Étienne 2003, Étienne et al. 2003, Lynam et al. 2002).”
Modelling with stakeholders (2010, background): “These questions are relevant to any process where different organisational or hierarchical levels are involved (Castella et al., 2005; Kok et al., 2007).”
Linking Land Change with Driving Forces and Actors: Four Conceptual Models (2010, methodology): “The other models tend to rely more on social science methods, including participatory methods (Castella et al. 2005, Özkaynak 2008), interviews (Overmars et al. 2007a), or economic theory (Balmann 1997, Parker et al. 2003, Ligtenberg et al. 2004).”