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 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 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 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.