Climate change is substantially impacting earth’s biodiversity, with a massive number of affected species that are difficult to study comprehensively. An “indicator species” approach that generalizes species-specific climate change impacts to broader groups (e.g., ensembles) could theoretically help overcome this challenge and streamline climate-smart conservation planning. We assessed the viability of this approach using four specialist amphibians (Ascaphus montanus, Dicamptodon copei, Plethodon idahoensis, and Plethodon vandykei), which we expected would have similar climate-related trajectories given their shared dependence on a narrow range of groundwater-driven habitats. Using boosted regression trees, we constructed species distribution models (SDMs) for each species and (if appropriate) major intraspecific lineage, then projected changes in environmental suitability under two climate change scenarios (SSP370 and SSP585) and timeframes (mid-century and late-century). Contrary to our expectation, future suitability projections varied widely among species, with small-to-moderate projected gains in suitability for A. montanus, relatively small changes with ambiguous directionality for D. copei, large gains in multiple regions for P. idahoensis, and major losses-in-place for P. vandykei. In addition, lineage-specific SDMs that assumed different niches for coastal and Cascades P. vandykei populations projected climate vulnerability for only the latter, highlighting a need for better genetic and ecological data. Given our collective findings, attempts to generalize climate change projections for purported “indicator species” to larger groups can be misleading, even within narrowly-defined and highly specialized ensembles. Moreover, we found a strong link between recent historical SDM outputs and species-tailored variables (e.g., seep-related variables), but many of these variables lacked future projections under climate change and were thus not directly usable to forecast climate change responses. Lastly, our findings also highlight research and conservation needs for our study species under climate change, such as identifying taxonomic scales of niche variation and protecting in-situ climatic refugia.

Climate change is substantially impacting earth’s biodiversity, with a massive number of affected species that are difficult to study comprehensively. An “indicator species” approach that generalizes species-specific climate change impacts to broader groups (e.g., ensembles) could theoretically help overcome this challenge and streamline climate-smart conservation planning. We assessed the viability of this approach using four specialist amphibians (Ascaphus montanus, Dicamptodon copei, Plethodon idahoensis, and Plethodon vandykei), which we expected would have similar climate-related trajectories given their shared dependence on a narrow range of groundwater-driven habitats. Using boosted regression trees, we constructed species distribution models (SDMs) for each species and (if appropriate) major intraspecific lineage, then projected changes in environmental suitability under two climate change scenarios (SSP370 and SSP585) and timeframes (mid-century and late-century). Contrary to our expectation, future suitability projections varied widely among species, with small-to-moderate projected gains in suitability for A. montanus, relatively small changes with ambiguous directionality for D. copei, large gains in multiple regions for P. idahoensis, and major losses-in-place for P. vandykei. In addition, lineage-specific SDMs that assumed different niches for coastal and Cascades P. vandykei populations projected climate vulnerability for only the latter, highlighting a need for better genetic and ecological data. Given our collective findings, attempts to generalize climate change projections for purported “indicator species” to larger groups can be misleading, even within narrowly-defined and highly specialized ensembles. Moreover, we found a strong link between recent historical SDM outputs and species-tailored variables (e.g., seep-related variables), but many of these variables lacked future projections under climate change and were thus not directly usable to forecast climate change responses. Lastly, our findings also highlight research and conservation needs for our study species under climate change, such as identifying taxonomic scales of niche variation and protecting in-situ climatic refugia.

Climate change is substantially impacting earth’s biodiversity, with a massive number of affected species that are difficult to study comprehensively. An “indicator species” approach that generalizes species-specific climate change impacts to broader groups (e.g., ensembles) could theoretically help overcome this challenge and streamline climate-smart conservation planning. We assessed the viability of this approach using four specialist amphibians (Ascaphus montanus, Dicamptodon copei, Plethodon idahoensis, and Plethodon vandykei), which we expected would have similar climate-related trajectories given their shared dependence on a narrow range of groundwater-driven habitats. Using boosted regression trees, we constructed species distribution models (SDMs) for each species and (if appropriate) major intraspecific lineage, then projected changes in environmental suitability under two climate change scenarios (SSP370 and SSP585) and timeframes (mid-century and late-century). Contrary to our expectation, future suitability projections varied widely among species, with small-to-moderate projected gains in suitability for A. montanus, relatively small changes with ambiguous directionality for D. copei, large gains in multiple regions for P. idahoensis, and major losses-in-place for P. vandykei. In addition, lineage-specific SDMs that assumed different niches for coastal and Cascades P. vandykei populations projected climate vulnerability for only the latter, highlighting a need for better genetic and ecological data. Given our collective findings, attempts to generalize climate change projections for purported “indicator species” to larger groups can be misleading, even within narrowly-defined and highly specialized ensembles. Moreover, we found a strong link between recent historical SDM outputs and species-tailored variables (e.g., seep-related variables), but many of these variables lacked future projections under climate change and were thus not directly usable to forecast climate change responses. Lastly, our findings also highlight research and conservation needs for our study species under climate change, such as identifying taxonomic scales of niche variation and protecting in-situ climatic refugia.

Climate change is substantially impacting earth’s biodiversity, with a massive number of affected species that are difficult to study comprehensively. An “indicator species” approach that generalizes species-specific climate change impacts to broader groups (e.g., ensembles) could theoretically help overcome this challenge and streamline climate-smart conservation planning. We assessed the viability of this approach using four specialist amphibians (Ascaphus montanus, Dicamptodon copei, Plethodon idahoensis, and Plethodon vandykei), which we expected would have similar climate-related trajectories given their shared dependence on a narrow range of groundwater-driven habitats. Using boosted regression trees, we constructed species distribution models (SDMs) for each species and (if appropriate) major intraspecific lineage, then projected changes in environmental suitability under two climate change scenarios (SSP370 and SSP585) and timeframes (mid-century and late-century). Contrary to our expectation, future suitability projections varied widely among species, with small-to-moderate projected gains in suitability for A. montanus, relatively small changes with ambiguous directionality for D. copei, large gains in multiple regions for P. idahoensis, and major losses-in-place for P. vandykei. In addition, lineage-specific SDMs that assumed different niches for coastal and Cascades P. vandykei populations projected climate vulnerability for only the latter, highlighting a need for better genetic and ecological data. Given our collective findings, attempts to generalize climate change projections for purported “indicator species” to larger groups can be misleading, even within narrowly-defined and highly specialized ensembles. Moreover, we found a strong link between recent historical SDM outputs and species-tailored variables (e.g., seep-related variables), but many of these variables lacked future projections under climate change and were thus not directly usable to forecast climate change responses. Lastly, our findings also highlight research and conservation needs for our study species under climate change, such as identifying taxonomic scales of niche variation and protecting in-situ climatic refugia.

Climate change is substantially impacting earth’s biodiversity, with a massive number of affected species that are difficult to study comprehensively. An “indicator species” approach that generalizes species-specific climate change impacts to broader groups (e.g., ensembles) could theoretically help overcome this challenge and streamline climate-smart conservation planning. We assessed the viability of this approach using four specialist amphibians (Ascaphus montanus, Dicamptodon copei, Plethodon idahoensis, and Plethodon vandykei), which we expected would have similar climate-related trajectories given their shared dependence on a narrow range of groundwater-driven habitats. Using boosted regression trees, we constructed species distribution models (SDMs) for each species and (if appropriate) major intraspecific lineage, then projected changes in environmental suitability under two climate change scenarios (SSP370 and SSP585) and timeframes (mid-century and late-century). Contrary to our expectation, future suitability projections varied widely among species, with small-to-moderate projected gains in suitability for A. montanus, relatively small changes with ambiguous directionality for D. copei, large gains in multiple regions for P. idahoensis, and major losses-in-place for P. vandykei. In addition, lineage-specific SDMs that assumed different niches for coastal and Cascades P. vandykei populations projected climate vulnerability for only the latter, highlighting a need for better genetic and ecological data. Given our collective findings, attempts to generalize climate change projections for purported “indicator species” to larger groups can be misleading, even within narrowly-defined and highly specialized ensembles. Moreover, we found a strong link between recent historical SDM outputs and species-tailored variables (e.g., seep-related variables), but many of these variables lacked future projections under climate change and were thus not directly usable to forecast climate change responses. Lastly, our findings also highlight research and conservation needs for our study species under climate change, such as identifying taxonomic scales of niche variation and protecting in-situ climatic refugia.

These data include field-collected observations of the occurrence of adult and larval amphibians at 174 sites in 14 watersheds at Yosemite National Park from 2007 through 2021. Also included in the data are potential variables affecting site occurrence, probability of reproduction, and probability of detection of amphibians, including static site-specific variables like site size and elevation, and dynamic variables including surveyors, when surveys occurred, and site- and year-specific weather variables. These data were used to fit the models in the accompanying publication and can be used with the associated code to replicate the results found in the publication.

These data include field-collected observations of the occurrence of adult and larval amphibians at 174 sites in 14 watersheds at Yosemite National Park from 2007 through 2021. Also included in the data are potential variables affecting site occurrence, probability of reproduction, and probability of detection of amphibians, including static site-specific variables like site size and elevation, and dynamic variables including surveyors, when surveys occurred, and site- and year-specific weather variables. These data were used to fit the models in the accompanying publication and can be used with the associated code to replicate the results found in the publication.

Environmental and demographic information used in population projections. This dataset is associated with the following publication: Awkerman, J., and C. Greenberg. Projected Climate and Hydroregime Variability Constrain Ephemeral Wetland-Dependent Amphibian Populations in Simulations of Southern Toads. Ecologies. MDPI, Basel, SWITZERLAND, 3(2): 235-248, (2022).