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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]

Many frameworks have been used to identify environmental flows for sustaining river ecosystems or specific taxa in the face of widespread flow alteration. However, these frameworks largely focus on identifying suitable flows and often ignore the important links between management actions, resulting flows, and valued ecosystem or social responses. Structured decision making (SDM) could assist the comparison of environmental flows by providing a mature framework to link management actions to objectives via environmental flow science. We describe SDM and illustrate its application using a case study focused on comparing environmental flow scenarios for the mainstem Willamette River, Oregon. In a short timeframe, SDM was applied to identify objectives, develop empirical and expert opinion‐based models, and compare flow scenarios while accounting for interannual flow variability and partial controllability. No scenario was clearly preferred based on available knowledge, largely because river flows could only be partially controlled through dam operations. Participants agreed that SDM was useful for comparing alternative dam operations, but that refined predictive models and additional objectives were needed to better inform basinwide flow decisions. In our view, SDM can provide more realistic comparisons of environmental flows by accounting for partial controllability and uncertainty, which may result in greater implementation of available flow management actions. Research Impact Statement: Structured decision making can support environmental flow implementation decisions by linking management options to ecosystem values while accounting for uncertainty. [ABSTRACT FROM AUTHOR]