Dynamic physical and economic modelling of riparian restoration options
A dynamic simulation framework is used to compare benefit-cost ratios of riparian restoration investment strategies to pursue ecosystem service benefits. The model is meant to be adaptable to generic restoration planning applications, with the Middle Rio Grande riparian corridor in Albuquerque, New Mexico, U.S.A. presented here as the illustrating case. Model inputs include ecosystem service values from an original choice experiment, values from regional benefit transfer studies, and information from land managers. The model includes three control variable modules: forest management, river restoration, and recreation infrastructure. Investment influences these modules, which in turn affect ecosystem service flows for the region. The model is exercised to compare a No-Action alternative with Optimal Benefit-Cost Ratio restoration funding. An extended sensitivity analysis explores a range of both physical and economic assumptions. The analysis has two major outcomes. The first is that directed restoration funding yields significant gains as compared with No-Action for all scenarios tested. The second major finding is that although optimized benefit-cost ratios are above unity for all states of the world tested, the ratio itself and funding patterns varied widely. These sensitivities underscore the need for a transparent adaptive management decision process supported by tools aimed not at deterministic prediction, but rather at structuring dialogue and inquiry into issues that defy simple intuition.
dynamic simulation ecosystem service rio grande choice experiment river restoration adaptive management benefit-cost analysis