1932

Abstract

Traditional top-down methods for resource management ask first what future conditions will be, then identify the best action(s) to take in response to that prediction. Even when acknowledging uncertainty about the future, standard approaches () characterize uncertainties probabilistically, then optimize objectives in expectation, and/or () develop a small number of representative scenarios to explore variation in outcomes under different policy responses. This leaves planners vulnerable to surprise if future conditions diverge from predictions. In this review, we describe contemporary approaches to decision support that address deep uncertainty about future external forcings, system responses, and stakeholder preferences for different outcomes. Many of these methods are motivated by climate change adaptation, infra-structure planning, or natural resources management, and they provide dramatic improvements in the robustness of management strategies. We outline various methods conceptually and describe how they have been applied in a range of landmark real-world planning studies.

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2019-10-05
2024-06-25
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