Decision errors in evaluating tipping points for ecosystem resilience |
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| Institution: | 1. School of Marine and Environmental Affairs, University of Washington, 3707 Brooklyn Avenue NE, Seattle, WA 98105 USA;2. Conservation Biology Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, 2725 Montlake Boulevard E, Seattle, WA 98112 USA;3. Southern California Coastal Water Research Project Authority, 3535 Harbor Blvd, Costa Mesa, CA 92626 USA;4. University of Washington, Joint Institute for the Study of the Atmosphere and Ocean (JISAO), 3737 Brooklyn Avenue NE, Box 355672, Seattle, WA 98195 USA;5. Pacific Marine Environmental Laboratory, National Oceanic and Atmospheric Administration, 7600 Sand Point Way NE, Seattle, WA 98115 USA;6. University of Washington, Applied Physics Lab, 1013 NE 40th Street, Box 355640, Seattle, WA 98105 USA;1. Department of Economics and Social Sciences, Università Politecnica delle Marche, Piazzale Martelli 8, Ancona, 60121, Italy;2. Department of Economics, Insubria University, Via Monte Generoso 71, Varese, 21100, Italy;3. National Institute of Statistics (ISTAT), Regional Office, Via Castelfidardo 4, Ancona, 60121, Italy;1. School of Natural Resources and Environment, University of Florida, Gainesville, FL 32611, United States;2. School of Forest Resources and Conservation, University of Florida, Gainesville, FL 32611, United States;1. Organic Plant Production and Agroecosystems Research in the Tropics and Subtropics, Universität Kassel, Steinstr. 19, D-37213 Witzenhausen, Germany;2. Soil Biology and Plant Nutrition, Universität Kassel, Nordbahnhofstr. 1a, D-37213 Witzenhausen, Germany |
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| Abstract: | When an ecosystem reaches tipping points for selected indicators, resilience to further changes in external drivers can decrease, regime shifts can occur that diminish the capacity of the ecosystem to provide ecosystem services, and the ecosystem is more vulnerable to collapse. Evaluating tipping points for resilience using crisp decision rules can result in decision errors about whether or not resilience has been compromised. The source and nature of those errors are described and a fuzzy decision rule is proposed for evaluating resilience. Decision errors are evaluated for four cases. Cases 1 through 3 (or case 4) derive conditions for evaluating decision errors when there is a single (or multiple) indicator(s). The primary sources of decision errors for the four cases are discrepancies between measured (or established) and true values of the indicators (or tipping points) and using a crisp decision rule to reach conclusions about whether or not resilience has been compromised. A fuzzy decision rule, based on fuzzy TOPSIS, is proposed that evaluates the extent to which an ecosystem is resilient. Although crisp decision rules provide unambiguous conclusions about resilience, those conclusions can be faulty, particularly when measured indicators and established tipping points deviate substantially from their true values. In contrast, the conclusions from the fuzzy decision rule are less susceptible to the decision errors and, hence, faulty decisions. |
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| Keywords: | Crisp decision rules Fuzzy decision rules Decision errors Tipping points Ecosystem resilience |
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