Reducing uncertainty in climate change responses of inland fishes: A decision-path approach
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Abstract
Climate change will continue to be an important consideration for conservation practitioners. However, uncertainty in identifying appropriate management strategies, particularly for understudied species and regions, constrains the implementation of science-based solutions and adaptation strategies. Here, we share a decision-path approach to reduce uncertainty in climate change responses of inland fishes to inform conservation and adaptation planning. With the Fish and Climate Change database (FiCli), a comprehensive, online, public database of peer-reviewed literature on documented and projected climate impacts to inland fishes, users can identify relevant studies and associated management recommendations via geographic regions, response types (i.e., fish assemblage dynamics, demographic, distributional, evolutionary, phenological), fish taxa, and traits (e.g., thermal guilds, feeding type, parental care, habitat type) and use a suite of summary tools to make more informed decisions. For both data-rich and data-poor scenarios, we demonstrate that this approach can reduce uncertainty in understanding climate change responses. Using thermal sensitivity as an example, we also establish the utility of FiCli database to address other user-defined, management-relevant questions via supplementary analyses. This decision-path approach can be applied to rapid assessments, management decisions, and policy development and may serve as a model for other conservation decision-making processes.
| Publication type | Article |
|---|---|
| Publication Subtype | Journal Article |
| Title | Reducing uncertainty in climate change responses of inland fishes: A decision-path approach |
| Series title | Conservation Science and Practice |
| DOI | 10.1111/csp2.12724 |
| Volume | 4 |
| Issue | 7 |
| Year Published | 2022 |
| Language | English |
| Publisher | Wiley |
| Contributing office(s) | National Climate Adaptation Science Center |
| Description | e12724, 15 p. |
| Google Analytic Metrics | Metrics page |