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The resilience of ecologically significant landscapes is often hindered by traditional approaches to natural resource management, which treat ecologic, hydrologic, and social systems as distinct entities. Although acknowledging interdependencies is a great first step in managing complex systems, challenges exist in predicting effects of intervention due to key features such as non-linearity and uncertainty. In order to project the impact of urban populations on riparian corridors in a semi-arid desert, we integrated several modeling approaches to simulate how policy decision-making will effect riparian vegetation along the Upper San Pedro River. Policy decision-making was characterized with a Bayesian Belief Network, allowing uncertainty in the decision-making process to be incorporated. Policy decisions ultimately effected population growth and water use. Urban water demand, calculated by multiplying urban population size with per capita water consumption, was used in conjunction with response functions, developed from MODFLOW, to simulate changes in depth-to-groundwater by well pumping in a spatially-explicit agent-based model. Depth-to-groundwater was then used as an indicator of unique vegetation guilds within the riparian corridor. The model was used to test the effects of policy decision-making on the spatial distribution of riparian vegetation along the Upper San Pedro River. By using the model as a tool, decision-makers may have the ability to make better-informed decisions to ensure the resilience of the Upper San Pedro Watershed.
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- Effects of Policy Decision-Making on Riparian Corridors in a Semi-arid Desert: A Modeling Approach
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