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Tradeoffs in marine reserve design: habitat condition, representation, and socioeconomic costs
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- Carissa J. Klein
- Australian Research Council Centre of Excellence for Environmental Decisions National Environmental Research Program funded Environmental Decisions Hub, School of Biological Sciences, University of Queensland St. Lucia Queensland Australia
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- Vivitskaia J. Tulloch
- Australian Research Council Centre of Excellence for Environmental Decisions National Environmental Research Program funded Environmental Decisions Hub, School of Biological Sciences, University of Queensland St. Lucia Queensland Australia
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- Benjamin S. Halpern
- National Center for Ecological Analysis and Synthesis Santa Barbara California USA
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- Kimberly A. Selkoe
- National Center for Ecological Analysis and Synthesis Santa Barbara California USA
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- Matthew E. Watts
- Australian Research Council Centre of Excellence for Environmental Decisions National Environmental Research Program funded Environmental Decisions Hub, School of Biological Sciences, University of Queensland St. Lucia Queensland Australia
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- Charles Steinback
- Ecotrust Portland Oregon USA
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- Astrid Scholz
- Ecotrust Portland Oregon USA
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- Hugh P. Possingham
- Australian Research Council Centre of Excellence for Environmental Decisions National Environmental Research Program funded Environmental Decisions Hub, School of Biological Sciences, University of Queensland St. Lucia Queensland Australia
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Description
<jats:title>Abstract</jats:title><jats:p>We present a novel method for designing marine reserves that trades off three important attributes of a conservation plan: habitat condition, habitat representation, and socioeconomic costs. We calculated habitat condition in four ways, using different human impacts as a proxy for condition: all impacts; impacts that cannot be managed with a reserve; land‐based impacts; and climate change impacts. We demonstrate our approach in California, where three important tradeoffs emerged. First, reserve systems that have a high chance of protecting good condition habitats cost fishers less than 3.1% of their income. Second, cost to fishers can be reduced by 1/2–2/3 by triaging less than 1/3 of habitats. Finally, increasing the probability of protecting good condition habitats from 50% to 99% costs fishers an additional 1.7% of their income, with roughly 0.3% added costs for each additional 10% confidence. Knowing exactly what the cost of these tradeoffs are informs discussion and potential compromise among stakeholders involved in protected area planning worldwide.</jats:p>
Journal
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- Conservation Letters
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Conservation Letters 6 (5), 324-332, 2013-01-16
Wiley
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Details 詳細情報について
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- CRID
- 1361137044870519168
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- ISSN
- 1755263X
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- Data Source
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- Crossref