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Adaptive management of large‐scale ecosystem restoration: increasing certainty of habitat outcomes in the Columbia River Estuary, U.S.A.
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2022
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Source: Restoration Ecology, 30(8)
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Journal Title:Restoration Ecology
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Description:Ecological restoration programs in dynamic coastal environments can benefit from adaptive management, including an iterative process for identifying and addressing critical uncertainties. We highlight key developments under the three pillars that have increased the rate of restoration by the Columbia Estuary Ecosystem Restoration Program (CEERP) over 20 years: science, coordination, and management. We show how such programs can be institutionalized to ensure that estuary ecosystems are better understood, conserved, and restored. The principal conservation effort under CEERP is to reconnect historical floodplain wetlands to the mainstem. The program also supports other restoration actions that demonstrate a high potential to benefit ecosystem function and endangered salmon populations; however, there is greater uncertainty regarding these less‐utilized techniques. Through adaptive management, we address technical uncertainty regarding benefits to the environmental resource and programmatic uncertainty pertaining to decision‐making. Here, we examine three periods of CEERP growth to establish how complementary research and restoration actions have improved program outcomes over time. We highlight the tools and processes that were developed and integrated into the program to refine program strategy, improve project design, and maximize ecological benefits. CEERP supported 77 restoration projects and reconnected over 7,000 acres of floodplain habitat to the lower Columbia River between 2004 and 2021. Building on these successes, we outline current plans to better engage landowners and local communities, solicit new project types, and maintain enough flexibility within the program to adapt to new priorities.
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Source:Restoration Ecology, 30(8)
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ISSN:1061-2971;1526-100X;
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Rights Information:CC BY-NC
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Compliance:Library
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