Using Coupled Simulation Models to Link Pastoral Decision Making and Ecosystem Services
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Boone, R. B., K. A. Galvin, S. B. BurnSilver, P. K. Thornton, D. S. Ojima, and J. R. Jawson. 2011. Using coupled simulation models to link pastoral decision making and ecosystem services. Ecology and Society 16(2): 6
Permanent link to this item: http://hdl.handle.net/10568/3837
Internet URL: http://www.ecologyandsociety.org/vol16/iss2/art6/
Historically, pastoral people were able to more freely use the services their semi-arid and arid ecosystems provide, and they adapted to changes in ways that improved their well-being. More recently, their ability to adapt has been constrained due to changes from within and from outside their communities. To compare possible responses by pastoral communities, we modeled ecosystem services and tied those services to decisions that people make at the household level. We created an agent-based household model called DECUMA, joined that model with the ecosystem model SAVANNA, and applied the linked models to southeastern Kajiado District, Kenya. The structure of the new agent-based model and linkages between the models are described, and then we demonstrate the model results using a scenario that shows changes in Maasai well-being in response to drought. We then explore two additional but related scenarios, quantifying household well-being if access to a grazing reserve is lost and if access is lost but those most affected are compensated. In the second scenario, households in group ranches abutting the grazing reserve that lost access had large declines in livestock populations, less food energy from animal sources, increased livestock sales and grain purchases, and increased need for supplemental foods. Households in more distant areas showed no changes or had increases in livestock populations because their herds had fewer animals with which to compete for forage. When households neighboring the grazing reserve were compensated for the lease of the lands they had used, they prospered. We describe some benefits and limitations of the agent-based approach.