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评估湿地管理策略的成本和效益，同时考虑到不确定的海平面上升和生态系统响应。

Evaluating the costs and benefits of marsh-management strategies while accounting for uncertain sea-level rise and ecosystem response.

机构信息

Warren Pinnacle Consulting, Inc., Waitsfield, Vermont, United States of America.

出版信息

PLoS One. 2018 Aug 15;13(8):e0200368. doi: 10.1371/journal.pone.0200368. eCollection 2018.

DOI:10.1371/journal.pone.0200368
PMID:30110331
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6093603/
Abstract

Prioritization of marsh-management strategies is a difficult task as it requires a manager to evaluate the relative benefits of each strategy given uncertainty in future sea-level rise and in dynamic marsh response. A modeling framework to evaluate the costs and benefits of management strategies while accounting for both of these uncertainties has been developed. The base data for the tool are high-resolution uncertainty-analysis results from the SLAMM (Sea-Level Affecting Marshes Model) under different adaptive-management strategies. These results are combined with an ecosystem-valuation assessment from stakeholders. The SLAMM results and stakeholder values are linked together using "utility functions" that characterize the relationship between stakeholder values and geometric metrics such as "marsh area," marsh edge," or "marsh width." The expected-value of each site's ecosystem benefits can then be calculated and compared using estimated costs for each strategy. Estimates of optimal marsh-management strategies may then be produced, maximizing the "ecosystem benefits per estimated costs" ratio.

摘要

由于需要管理者在未来海平面上升和动态沼泽响应的不确定性下评估每种策略的相对收益，因此优先考虑沼泽管理策略是一项艰巨的任务。已经开发了一种建模框架，用于评估管理策略的成本和收益，同时考虑到这两个不确定性。该工具的基础数据是在不同自适应管理策略下 SLAMM（海平面影响沼泽模型）的高分辨率不确定性分析结果。这些结果与利益相关者的生态系统评估相结合。使用“效用函数”将 SLAMM 结果和利益相关者价值联系起来，这些函数描述了利益相关者价值与几何度量（如“沼泽面积”、“沼泽边缘”或“沼泽宽度”）之间的关系。然后可以计算每个地点的生态系统收益的预期价值，并使用每种策略的估计成本进行比较。然后可以生成最佳沼泽管理策略的估计值，最大化“每估计成本的生态系统收益”比率。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ea5d/6093603/26f45fea64c6/pone.0200368.g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ea5d/6093603/689a73e69bdb/pone.0200368.g001.jpg
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