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Decision analysis for greater insights into the development and evaluation of Chinook salmon restoration strategies in California's Central Valley
Restoration Ecology ( IF 2.8 ) Pub Date : 2020-07-11 , DOI: 10.1111/rec.13244
James T. Peterson 1 , Adam Duarte 2
Affiliation  

Considerable resources have been invested in ecological restoration projects across the globe to restore ecosystem integrity. Restoration strategies are often diverse and have been met with mixed success. In this article, we describe the Chinook salmon (Oncorhynchus tshawytscha) decision‐support models developed by the Central Valley Project Improvement Act Science Integration Team as part of a larger structured decision‐making effort aimed at maximizing natural adult production of Chinook salmon in California's Central Valley, the United States. We then describe the decision‐analytic tools the stakeholder group used to solve the models and explore model results, including stochastic dynamic programming, forward simulation, proportional scoring, relative loss, expected value of perfect information, response profile analyses, and indifference curves. Using these tools, the stakeholder group was able to develop and evaluate restoration strategies for multiple Chinook salmon runs simultaneously, a first for the restoration program. We found that actions targeted at one run were detrimental to others, which was unexpected. Furthermore, information uncovered during this process was used to direct efforts towards targeted research/monitoring to reduce critical uncertainties in salmon demographic rates and make better restoration decisions moving forward. The decision sciences have established a wide range of analytical tools and approaches to simplify complex problems into key components, and we believe the concepts described in this article are of great interest and can be applied by many restoration practitioners that undoubtedly face similar difficulties when implementing restoration strategies for complex systems.

中文翻译:

决策分析可为加利福尼亚中央谷地的奇努克鲑鱼恢复策略的发展和评估提供更深刻的见解

全球在生态修复项目上投入了大量资源,以恢复生态系统的完整性。恢复策略通常是多种多样的,并且取得了不同的成功。在本文中,我们描述了奇努克鲑鱼(Oncorhynchus tshawytscha)由中央谷地项目改进法案科学整合小组开发的决策支持模型,该决策支持模型是一项更大的结构化决策工作的一部分,旨在最大程度地提高美国加利福尼亚中央谷地的奇努克鲑的自然成年产量。然后,我们描述利益相关者小组用来解决模型和探索模型结果的决策分析工具,包括随机动态规划,正向模拟,比例计分,相对损失,理想信息的期望值,响应曲线分析和无差异曲线。使用这些工具,利益相关者小组能够同时开发和评估多个奇努克鲑鱼养殖场的恢复策略,这是恢复计划中的第一个。我们发现,针对一次运行的操作不利于其他运行,这是出乎意料的。此外,在此过程中发现的信息被用于指导努力进行有针对性的研究/监测,以减少鲑鱼人口统计数据的关键不确定性,并做出更好的恢复决策。决策科学已经建立了广泛的分析工具和方法,可以将复杂的问题简化为关键组成部分,我们相信本文中介绍的概念非常受关注,并且可以被许多修复实践者应用,这些修复实践无疑会在实施修复过程中面临类似的困难。复杂系统的策略。在此过程中发现的信息用于指导目标研究/监测,以减少鲑鱼人口统计数据的关键不确定性,并做出更好的恢复决策。决策科学已经建立了广泛的分析工具和方法,可以将复杂的问题简化为关键组成部分,并且我们相信本文中描述的概念非常受关注,并且可以被许多修复实践者应用,这些修复实践无疑会在实施修复过程中面临类似的困难复杂系统的策略。在此过程中发现的信息用于指导目标研究/监测,以减少鲑鱼人口统计数据的关键不确定性,并做出更好的恢复决策。决策科学已经建立了广泛的分析工具和方法,可以将复杂的问题简化为关键组成部分,并且我们相信本文中描述的概念非常受关注,并且可以被许多修复实践者应用,这些修复实践无疑会在实施修复过程中面临类似的困难复杂系统的策略。
更新日期:2020-07-11
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