Surprise and Opportunity for Learning in Grand Canyon: the Glen Canyon Dam Adaptive Management Program

Ecology and Society: a journal of integrative science for resilience and sustainability

Melis, Theodore¹ 

关键词: adaptive management;    Colorado River;    ecosystem modeling;    Glen Canyon Dam;    Gr;    Canyon;    high-flow experiments;    humpback chub;    rainbow trout;    surprise learning;   

DOI  :  10.5751/ES-07621-200322

学科分类：生物科学（综合）

来源: Resilience Alliance Publications

【 摘 要 】

With a focus on resources of the Colorado River ecosystem below Glen Canyon Dam, the Glen Canyon Dam Adaptive Management Program has included a variety of experimental policy tests, ranging from manipulation of water releases from the dam to removal of non-native fish within Grand Canyon National Park. None of these field-scale experiments has yet produced unambiguous results in terms of management prescriptions. But there has been adaptive learning, mostly from unanticipated or surprising resource responses relative to predictions from ecosystem modeling. Surprise learning opportunities may often be viewed with dismay by some stakeholders who might not be clear about the purpose of science and modeling in adaptive management. However, the experimental results from the Glen Canyon Dam program actually represent scientific successes in terms of revealing new opportunities for developing better river management policies. A new long-term experimental management planning process for Glen Canyon Dam operations, started in 2011 by the U.S. Department of the Interior, provides an opportunity to refocus management objectives, identify and evaluate key uncertainties about the influence of dam releases, and refine monitoring for learning over the next several decades. Adaptive learning since 1995 is critical input to this long-term planning effort.Embracing uncertainty and surprise outcomes revealed by monitoring and ecosystem modeling will likely continue the advancement of resource objectives below the dam, and may also promote efficient learning in other complex programs.

【 授权许可】

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