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Linking Climate Change and Fish Conservation Efforts Using Spatially Explicit Decision Support Tools

Fisheries professionals are increasingly tasked with incorporating climate change projections into their deci- sions. Here we demonstrate how a structured decision frame- work, coupled with analytical tools and spatial data sets, can help integrate climate and biological information to evaluate management alternatives. We present examples that link down- scaled 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 prioriti- zation 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 projec- tions. The barrier BN applied to three streams predicted that barrier removal decisions—previously made assuming a sta- tionary 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 uncertain- ties requiring further investigation.