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Decision analysis for greater insights into the development and evaluation of Chinook salmon restoration strategies in California's Central Valley.
- Source :
-
Restoration Ecology . Nov2020, Vol. 28 Issue 6, p1596-1609. 14p. - Publication Year :
- 2020
-
Abstract
- 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. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 10612971
- Volume :
- 28
- Issue :
- 6
- Database :
- Academic Search Index
- Journal :
- Restoration Ecology
- Publication Type :
- Academic Journal
- Accession number :
- 147223445
- Full Text :
- https://doi.org/10.1111/rec.13244