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    Fisheries professionals are increasingly tasked with incorporating climate change projections into their decisions. Here we demonstrate how a structured decision framework, coupled with analytical tools and spatial data sets, can help integrate climate and biological information to evaluate management alternatives. We present examples that link downscaled climate change scenarios to fish populations for two common types of problems: (1) strategic spatial prioritization of limited conservation resources and (2) deciding whether removing migration barriers would benefit a native fish also threatened with invasion by a nonnative competitor. We used Bayesian networks (BNs) to translate each decision problem into a quantitative tool and implemented these models under historical and future climate projections. The spatial prioritization BN predicted a substantial loss of habitat for the target species by the 2080s and provided a means to map habitats and populations most likely to persist under future climate projections. The barrier BN applied to three streams predicted that barrier removal decisions-previously made assuming a stationary climate-were likely robust under the climate scenario considered. The examples demonstrate the benefit of structuring the decision-making process to clarify management objectives, formalize assumptions, synthesize current understanding about climate effects on fish populations, and identify key uncertainties requiring further investigation.

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    Peterson, Douglas P.; Wenger, Seth J.; Rieman, Bruce E.; Isaak, Daniel J. 2013. Linking climate change and fish conservation efforts using spatially explicit decision support tools. Fisheries. 38(3): 112-127 + 58 pages of appendices.


    climate change, fish conservation, structured decision framework, analytical tools, spatial data sets, Bayesian networks (BNs)

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