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Accounting for Potential Effects on Fish Production from Barrier Removals to Inform Management Decisions: An Application of Structured Decision Making
Michael L. Jones1, Todd B. Steeves2, Shawn Nowicki3, Kelly F. Robinson1, Lisa Peterson1 and Alexander J. Jensen1
1 Quantitative Fisheries Center, Department of Fisheries and Wildlife, 480 Wilson Road, Room 13, Michigan State University, East Lansing, MI 48824
2 Fisheries and Oceans Canada, 1219 Queen St. East, Sault Ste Marie, ON P6A2E5
3 U.S. Fish & Wildlife Service, 3090 Wright Street, Marquette, MI 49855
There is considerable uncertainty about the effects of dam removals in rivers, especially as they relate to fish. Structured decision making (SDM) accounts for expected outcomes of different possible management decisions, and has been applied to prior barrier removals. Researchers at Michigan State University’s Quantitative Fisheries Center held back-to-back two day workshops in Romulus, MI, and Mississauga, ON, from November 14-17, 2016, to introduce Great Lakes fishery managers to SDM and report on the state of scientific knowledge relevant to predicting fish production from habitat above barriers. The Romulus and Mississauga workshops were attended by 17 and 23 individuals, respectively, representing management, academic, and non-governmental organizations. Each workshop featured descriptions of the five steps of SDM (Problem Definition, Objectives, Alternative Actions, Consequences, and Tradeoffs), large group discussions, and research presentations on predicting fish production above barriers. Based on post-workshop surveys, the workshops were well received and encouraged further interest in learning more about the application of SDM to fishery management.
· Structured Decision Making (SDM) is a useful tool to help managers, stakeholders, and researchers discuss and make effective decisions on complex fishery issues, including barrier removals in the Great Lakes.
· Modeling and field studies lend insight into the expected effects of dam removals on fish populations and communities, but many critical uncertainties remain that are important to consider in the SDM process.