title: Sustaining ecological integrity with respect to climate change: a fuzzy adaptive management approach.
abstract: A fuzzy adaptive management framework is proposed for evaluating the vulnerability of an ecosystem to losing ecological integrity as a result of climate change in an historical period (ex post evaluation) and selecting the best compensatory management action for reducing potential adverse impacts of future climate change on ecological integrity in a future period (ex ante evaluation). The ex post evaluation uses fuzzy logic to test hypotheses about the extent of past ecosystem vulnerability to losing ecological integrity and the ex ante evaluation uses the fuzzy minimax regret criterion to determine the best compensatory management action for alleviating potential adverse impacts of climate change on ecosystem vulnerability to losing ecological integrity in a future period. The framework accounts for uncertainty regarding: (1) the relationship between ecosystem vulnerability to losing ecological integrity and ecosystem resilience; (2) the relationship between ecosystem resilience and the extent to which observed indicators of ecological integrity depart from their thresholds; (3) the extent of future climate change; and (4) the potential impacts of future climate change on ecological integrity and ecosystem resilience. The adaptive management element of the framework involves using the ex post and ex ante evaluations iteratively in consecutive time segments of the future time period to determine if and when it is beneficial to adjust compensatory management actions to climate change. A constructed example is used to demonstrate the framework.
authors.affiliation: Center for Applied Research and Environmental Systems, University of Missouri, 12310 Paradise Loop Road, Marion, MT 59925, USA. pratoa@missouri.edu
authors.forename: Tony
authors.initials: T
authors.lastname: Prato
mesh_terms: D057231:Climate Change; D003247:Conservation of Natural Resources / Q000379:methods*; D004463:Ecology; D017143:Fuzzy Logic