Sky T.C. Button Donald J. Brown Jonah Piovia-Scott 20250226 raster digital data https://doi.org/10.5066/P148UUAU 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 were modeled to better understand the contemporary distributions of and potential risks posed by climate change to groundwater-dependent amphibians in the Pacific Northwest, USA. Appropriate uses include (but are not necessarily limited to) informing future surveys to detect additional populations, identifying/protecting potential climatic refugia, and informing the conservation status classification of our study species. 20241022 ground condition Complete None planned Pacific Northwest -119.7070 -112.7637 52.2682 45.3984 ISO 19115 Topic Category biota None SDM Refugia Amphibian Climate Change Species Distribution Model Indicator Species USGS Thesaurus climate change USGS Metadata Identifier USGS:67451e8ad34e6d1dac3a7086 None Pacific Northwest Washington Idaho Oregon British Columbia Montana None. Please see 'Distribution Info' for details. None. Users are advised to read the dataset's metadata thoroughly to understand appropriate use and data limitations. Sky Button physical

14204 NE Salmon Creek Ave

Vancouver Washington 98686 860-212-7155 Committee members Jesse Brunner and Caren Goldberg provided invaluable feedback on the manuscript prior to submission. This research was funded by a faculty grant from the Northwest Climate Adaptation Science Center (NW CASC). Windows 11; R Version 4.4.1; ArcGIS Pro 3.3. File names and data sizes vary among raster layers. All data are modeled estimates as opposed to "true" values. However, model accuracy was maximized by choosing a subset of predictor variables that best maximized cross-validated boosted regression tree accuracy, while pruning less important variables from the models to avoid overfitting. The data are consistent with expected ranges. Minor areas of omission include some areas of open water within large lakes (which inherently do not contain cliff-face seeps), plus some areas within ~1-2km of the Pacific Ocean, for which certain model predictor variables were not available and could not be calculated. The dataset represents modeled suitability estimates across the complete range of the study species. ~15m ~15m We generated these data by using boosted regression trees to generate estimates of the distributions of study species in relation to climate, physiography, and habitat. Response data consisted of species occurrence records (presences) and pseudo-absences (randomly selected from regions with sampling for amphibians but no records of the target species). 20241022 Sky Button Washington State University Research Assistant physical

14204 NE Salmon Creek Ave

Vancouver Washington 98686 USA 860-212-7155 sky.button@wsu.edu Raster Grid Cell 46821 67375 1 0.00027777777800000003 0.0002777777779999999 Decimal seconds WGS_1984 WGS 84 6378137.0 298.257223563 PLIDhpreds15Sep_tif_Fin.tif Predictions of contemporary relative environmental suitability for Plethodon idahoensis, generated using a holistic set of predictor variables. Producer Defined Value Unique numeric values contained in each raster cell. Producer Defined 0.0030705921817571 0.99930816888809 PLIDccpreds15Sep_tif_Fin.tif Predictions of contemporary relative environmental suitability for Plethodon idahoensis, generated using a climate projection-constrained set of predictor variables. Producer Defined Value Unique numeric values contained in each raster cell. Producer Defined 0.0038861876819283 0.997563123703 PLIDlmpreds15Sep_tif_Fin.tif Predictions of 2071-2100 relative environmental suitability for Plethodon idahoensis under an SSP370 climate scenario. Generated using a climate projection-constrained set of predictor variables. Producer Defined Value Unique numeric values contained in each raster cell. Producer Defined 0.0039624841883779 0.99915063381195 PLIDlspreds15Sep_tif_Fin.tif Predictions of 2071-2100 relative environmental suitability for Plethodon idahoensis under an SSP585 climate scenario. Generated using a climate projection-constrained set of predictor variables. Producer Defined Value Unique numeric values contained in each raster cell. Producer Defined 0.0048875827342272 0.99894309043884 PLIDmspreds15Sep_tif_Fin.tif Predictions of 2041-2070 relative environmental suitability for Plethodon idahoensis under an SSP585 climate scenario. Generated using a climate projection-constrained set of predictor variables. Producer Defined Value Unique numeric values contained in each raster cell. Producer Defined 0.0038601974956691 0.99865484237671 PLIDmmpreds15Sep_tif_Fin.tif Predictions of 2041-2070 relative environmental suitability for Plethodon idahoensis under an SSP370 climate scenario. Generated using a climate projection-constrained set of predictor variables. Producer Defined Value Unique numeric values contained in each raster cell. Producer Defined 0.0038582840934396 0.9987028837204 PLIDNorthhpreds15Sep_tif_Fin.tif Predictions of contemporary relative environmental suitability for the northern clade of Plethodon idahoensis, generated using a holistic set of predictor variables. Producer Defined Value Unique numeric values contained in each raster cell. Producer Defined 0.0048617096617818 0.99476438760757 PLIDNorthccpreds15Sep_tif_Fin.tif Predictions of contemporary relative environmental suitability for the northern clade of Plethodon idahoensis, generated using a climate projection-constrained set of predictor variables. Producer Defined Value Unique numeric values contained in each raster cell. Producer Defined 0.0044789030216634 0.99796634912491 Predictions for contemporary and potential future suitability for the study species, for different modeling types (h = holistic contemporary; cc = climate prediction-constrained [CPC] contemporary). Future predictions under different climate change scenarios/time frames are also included for CPC models (mm = mid-century SSP370; lm = late-century SSP370; ms = mid-century SSP585; ls = late-century SSP585). Button, S.T. and Piovia-Scott, J., 2024, Species distribution modeling estimates for four groundwater-dependent amphibians: U.S. Geological Survey data release, https://doi.org/10.5066/P148UUAU GS ScienceBase U.S. Geological Survey mailing address

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Denver CO 80225 United States 1-888-275-8747 sciencebase@usgs.gov Unless otherwise stated, all data, metadata and related materials are considered to satisfy the quality standards relative to the purpose for which the data were collected. Although these data and associated metadata have been reviewed for accuracy and completeness and approved for release by the U.S. Geological Survey (USGS), no warranty expressed or implied is made regarding the display or utility of the data for other purposes, nor on all computer systems, nor shall the act of distribution constitute any such warranty. Digital Data https://doi.org/10.5066/P148UUAU None. 20250226 Climate Adaptation Science Center mailing

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Reston Virginia 20192 USA n/a casc-data@usgs.gov FGDC Biological Data Profile of the Content Standard for Digital Geospatial Metadata FGDC-STD-001.1-1999