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• W3166450778 abstract "Abstract Decision analysis is applied to habitat and community resilience planning in Maryland, USA. Sea level rise is causing wetland loss and increased flooding in coastal areas. A team at The Nature Conservancy analyzed a decision to identify high-value conservation planning units across Maryland’s Lower Eastern Shore. The team selected two fundamental objectives: minimize habitat loss and minimize community flood impacts. Sub-objectives included habitat function, habitat migration potential, critical infrastructure, and social vulnerability. Spatial attributes were selected based on ecological knowledge about habitat and socio-economic knowledge about sustaining populations in flood-prone areas. Seven planning units were developed across the Lower Eastern Shore. Single-attribute value functions determined the overall value of each unit per attribute, whereas multi-attribute value functions determined the overall value of each unit for all fundamental objectives. Sensitivity analysis incorporated data adjustments based on different flood scenarios and unit sizes, and variation in attribute weights associated with the multi-attribute value function. The Pareto efficiency principle revealed tradeoffs between units for habitat protection and management and community engagement and adaptation. Results indicate that four units are Pareto efficient under different sensitivity iterations and they trade off value in the fundamental objectives, whereas one unit provides the highest combined habitat and community value. This research guided thinking about equity in decision making and targeting conservation actions at local scales. The approach and methods can be used to inform conservation decisions in other similar contexts." @default.
• W3166450778 created "2021-06-22" @default.
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• W3166450778 date "2021-06-15" @default.
• W3166450778 modified "2023-09-27" @default.
• W3166450778 title "Using Decision Analysis to Integrate Habitat and Community Values for Coastal Resilience Planning" @default.
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• W3166450778 doi "https://doi.org/10.1007/s12237-021-00970-x" @default.
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