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Climate Change Vulnerability Assessment for Amphibians in the North Central United States

December 27, 2024

Climate change is a primary threat to biodiversity, but for most species, we still lack information required to assess their potential vulnerability to changes. Climate change vulnerability assessment (CCVA) is a widely-used technique to rank relative vulnerability to climate change based on species distributions, habitat associations, environmental tolerances, and life-history traits. For species that we expect are vulnerable to climate change yet are data deficient, like many amphibians, we often lack information required to construct traditional CCVAs. We extended the CCVA framework by constructing models based on life history theory, using empirical evidence of traits and distributions that reflected sensitivity of data-deficient species to environmental perturbation. These csv data files were assembled to perform climate change vulnerability assessments of the 31 amphibian species, both across the north central region and within individual US states. We incorporated information from species' life history traits and other characteristics along with climate projections of evapotranspiration deficit change, to score relative vulnerability of the 31 amphibians. Associated R code is for scoring relative vulnerability, where overall score is a product of exposure to climate change times sensitivity to that change, minus adaptive capacity of each species. All species are listed as Species of Greatest Conservation Need in at least one of 7 states in the North Central United States: Montana, Wyoming, Colorado, North Dakota, South Dakota, Nebraska, and Kansas.

Publication Year 2024
Title Climate Change Vulnerability Assessment for Amphibians in the North Central United States
DOI 10.5066/P1UMVKOB
Authors Ross K Hinderer, Lisa Eby
Product Type Data Release
Record Source USGS Asset Identifier Service (AIS)
USGS Organization National Climate Adaptation Science Center
Rights This work is marked with CC0 1.0 Universal
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