Fuzzy Adaptive Management of Coupled Natural and Human Systems

Abstract A fuzzy logic-based, adaptive management (FLAM) model is developed that allows managers of coupled natural and human systems to determine preferred management actions over time when they are uncertain about the extent of future climate change and system responses to climate change and management actions. The FLAM model uses (1) data from adaptive management experiments and expert judgment, surveys, and/or simulation models to estimate multiple attributes of system responses to climate change and management actions, (2) fuzzy TOPSIS to determine the preferred management action for each climate change scenario within time periods, and (3) the minimax regret criterion to determine the preferred management actions across climate change scenarios within time periods. Application of the model is demonstrated for a hypothetical national park whose managers want to determine the best adaptive management strategy for increasing the number of backcountry campsites over time.