Iterative scenarios for social-ecological systems
Dustin L. Herrmann, Department of Botany and Plant Sciences, University of California, Riverside
Kirsten Schwarz, Departments of Urban Planning and Environmental Health Sciences, University of California-Los Angeles
Craig R. Allen, Center for Resilience in Agricultural Working Landscapes, School of Natural Resources, University of Nebraska-Lincoln
David G Angeler, Swedish University of Agriculture Sciences, Department of Aquatic Sciences and Assessment
Tarsha Eason, U.S. Environmental Protection Agency, Office of Research and Development, Center for Environmental Measurement and Modeling
Ahjond Garmestani, U.S. Environmental Protection Agency; Utrecht University
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Managing social-ecological systems toward desirable regimes requires learning about the system being managed while preparing for many possible futures. Adaptive management (AM) and scenario planning (SP) are two systems management approaches that separately use learning to reduce uncertainties and employ planning to manage irreducible uncertainties, respectively. However, each of these approaches have limitations that confound management of social-ecological systems. Here, we introduce iterative scenarios (IS), a systems management approach that is a hybrid of the scopes and relationships to uncertainty and controllability of AM and SP that combines the "iterativeness" of AM and futures planning of SP. Iterative scenarios is appropriate for situations with high uncertainty about whether a management action will lead to intended outcomes, the desired benefits are numerous and cross-scale, and it is difficult to account for the social implications around the natural resource management options. The value of iterative scenarios is demonstrated by applying the approach to green infrastructure futures for a neighborhood in the city of Cleveland, Ohio, U.S., that had experienced long-term, systemic disinvestment. The Cleveland green infrastructure project was particularly well suited to the IS approach given that learning about environmental factors was necessary and achievable, but what would be socially desirable and possible was unknown. However, iterative scenarios is appropriate for many social-ecological systems where uncertainty is high as IS accommodates real-world complexity faced by management.
adaptive management; futures; green infrastructure; iterative scenarios; scenario planning; social-ecological systems; structured learning
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