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# Data for "Using abundance distributions along environmental gradients to forecast range shifts" [https://doi.org/10.5061/dryad.6m905qg37](https://doi.org/10.5061/dryad.6m905qg37) ## Description of the data and file structure The data here represent the 71 species that we included in our analyses. Each row represents a single species. The column titles provided have been (re)labeled for clarity and consistency across studies. "Hist" in column titles refers to data from the historical periods and "curr" are data from the current/re-survey periods. Any questions regarding this file or data structure can be directed to Peter Billman at: [peter.billman@uconn.edu](mailto:Peter.billman@uconn.e) ## Sharing/Access information ###### Data were derived from the following eight studies: * Barrows, C. W., Sweet, L. C., Rangitsch, J., Lalumiere, K., Green, T., Heacox, S., . . . Rodgers, J. E. (2020). Responding to increased aridity: Evidence for range shifts in lizards across a 50-year time span in Joshua Tree National Park. *Biological Conservation*, **248**: 108667. * Carilla, J., Halloy, S., Cuello, S., Grau, A., Malizia, A., & Cuesta, F. (2018). Vegetation trends over eleven years on mountain summits in NW Argentina. *Ecology and Evolution*, **8**: 11554-11567. * Forero-Medina, G., Joppa, L., & Pimm, S. L. (2011). Constraints to species’ elevational range shifts as climate changes. *Conservation Biology*, **25**: 163-171. * Freeman, B. G., Scholer, M. N., Ruiz-Gutierrez, V., & Fitzpatrick, J. W. (2018). Climate change causes upslope shifts and mountaintop extirpations in a tropical bird community. *PNAS*, **115**: 11982-11987. * Menéndez, R., González-Megías, A., Jay-Robert, P., & Marquéz-Ferrando, R. (2014). Climate change and elevational range shifts: evidence from dung beetles in two European mountain ranges. *Global Ecology and Biogeography*, **23**: 646-657. * Moret, P., Aráuz, M. d. l. Á., Gobbi, M., Barragán, Á., & Didham, R. (2016). Climate warming effects in the tropical Andes: first evidence for upslope shifts of Carabidae (Coleoptera) in Ecuador. *Insect Conservation and Diversity*, **9**: 342-350. * Neate-Clegg, M. H. C., Stuart, S. N., Mtui, D., Şekercioğlu, Ç. H., & Newmark, W. D. (2021). Afrotropical montane birds experience upslope shifts and range contractions along a fragmented elevational gradient in response to global warming. *PloS one*, **16**: e0248712. * Wen, Z., Wu, Y., Ge, D., Cheng, J., Chang, Y., Yang, Z., . . . Yang, Q. (2017). Heterogeneous distributional responses to climate warming: evidence from rodents along a subtropical elevational gradient. *BMC Ecology*, **17**: 1-9. ## **Column Descriptions** * *ID:* unique ID for all species included (#) * *Species*: scientific name of species (genus + species) * *Count_Historical*: raw abundance in the historical sampling period (#) * *Count_Current*: raw abundance in the recent sampling period (#) * *Hist_Lower_Lim*: historical lower range limit (m) * *Hist_Upper_Lim*: historical upper range limit (m) * *Hist_Optimal*: historical optimum/abundance-weighted-mean elevation (m) * *Hist_Midpoint*: historical midpoint elevation (lower + upper elevational limit divided by two) (m) * *Hist_Elev_Range_Extent_Half*: elevational range of species divided by two (m) * *Hist_Lean_Meters*: overall lean by which a species optimum is above or below its midpoint (m) * *Hist_Lean_Percent*: lean metric from above but standardized by elevational range extent of species (%) * *Lower_Lim_Shift_Meters*: shift distance of lower range limit over time (m) * *Rate_Lower_Per_Year*: range-limit shift distance divided by time span between surveys (m/year) * *Rate_Lower_Decade*: range-limit shift distance divided by time span between surveyed, multiplied by ten (m/decade) * *Curr_Lower*: current lower range limit (m) * *Curr_Upper*: current upper range limit (m) * *Curr_Optimal*: current optimum/abundance-weighted-mean elevation (m) * *Curr_Midpoint*: current midpoint elevation (lower + upper elevational limit divided by two) (m) * *Curr_Elevational_Range_Extent_Half*: elevational range of species divided by two (m) * *Curr_Lean_Meters*: overall lean by which a species optimum is above or below its midpoint (m) * *Curr_Lean_Percent*: lean metric from above but standardized by elevational range extent of species (%) * *Citation*: original study from which data were derived * *Taxa*: taxonomic group to which a species belongs * *Continent*: continent where original study was conducted * Missing data code: NA Globally, many species’ distributions are shifting in response to contemporary climate change. However, the direction and rate of shifts remain difficult to predict, impeding managers' abilities to allocate resources most effectively. Here, we explore a new approach for forecasting species' range-limit shifts that requires only abundance data along environmental (eg elevational) gradients. We hypothesized that species’ abundance distributions could provide information on the likelihood of future range-limit shifts. We tested this prediction using data from several transect studies that compared historical and contemporary distributions. Consistent with our prediction, we found that strong asymmetry in abundance distributions (ie “leaning” distributions) indeed preceded species’ lower-limit range shifts (Fisher's exact test P < 0.001, R2 = 0.28). Accordingly, surveying abundances along environmental gradients may be one promising, cost-effective method for forecasting local shifts. Ideally, practitioners will be able to incorporate this approach into species-specific management planning and to inform on-the-ground conservation efforts. Data were extracted from eight cited peer-reviewed studies in total. These studies cover a range of species, biomes, and regions across the globe. The accompanying data here have been centralized and processed to include the key metrics we discuss in our manuscript such as the historical and current range limits, species' midpoints, optimum elevations, leans in meters, leans as percentages, and lower-range limits shift rates per year and decade. 

# Data for "Using abundance distributions along environmental gradients to forecast range shifts" [https://doi.org/10.5061/dryad.6m905qg37](https://doi.org/10.5061/dryad.6m905qg37) ## Description of the data and file structure The data here represent the 71 species that we included in our analyses. Each row represents a single species. The column titles provided have been (re)labeled for clarity and consistency across studies. "Hist" in column titles refers to data from the historical periods and "curr" are data from the current/re-survey periods. Any questions regarding this file or data structure can be directed to Peter Billman at: [peter.billman@uconn.edu](mailto:Peter.billman@uconn.e) ## Sharing/Access information ###### Data were derived from the following eight studies: * Barrows, C. W., Sweet, L. C., Rangitsch, J., Lalumiere, K., Green, T., Heacox, S., . . . Rodgers, J. E. (2020). Responding to increased aridity: Evidence for range shifts in lizards across a 50-year time span in Joshua Tree National Park. *Biological Conservation*, **248**: 108667. * Carilla, J., Halloy, S., Cuello, S., Grau, A., Malizia, A., & Cuesta, F. (2018). Vegetation trends over eleven years on mountain summits in NW Argentina. *Ecology and Evolution*, **8**: 11554-11567. * Forero-Medina, G., Joppa, L., & Pimm, S. L. (2011). Constraints to species’ elevational range shifts as climate changes. *Conservation Biology*, **25**: 163-171. * Freeman, B. G., Scholer, M. N., Ruiz-Gutierrez, V., & Fitzpatrick, J. W. (2018). Climate change causes upslope shifts and mountaintop extirpations in a tropical bird community. *PNAS*, **115**: 11982-11987. * Menéndez, R., González-Megías, A., Jay-Robert, P., & Marquéz-Ferrando, R. (2014). Climate change and elevational range shifts: evidence from dung beetles in two European mountain ranges. *Global Ecology and Biogeography*, **23**: 646-657. * Moret, P., Aráuz, M. d. l. Á., Gobbi, M., Barragán, Á., & Didham, R. (2016). Climate warming effects in the tropical Andes: first evidence for upslope shifts of Carabidae (Coleoptera) in Ecuador. *Insect Conservation and Diversity*, **9**: 342-350. * Neate-Clegg, M. H. C., Stuart, S. N., Mtui, D., Şekercioğlu, Ç. H., & Newmark, W. D. (2021). Afrotropical montane birds experience upslope shifts and range contractions along a fragmented elevational gradient in response to global warming. *PloS one*, **16**: e0248712. * Wen, Z., Wu, Y., Ge, D., Cheng, J., Chang, Y., Yang, Z., . . . Yang, Q. (2017). Heterogeneous distributional responses to climate warming: evidence from rodents along a subtropical elevational gradient. *BMC Ecology*, **17**: 1-9. ## **Column Descriptions** * *ID:* unique ID for all species included (#) * *Species*: scientific name of species (genus + species) * *Count_Historical*: raw abundance in the historical sampling period (#) * *Count_Current*: raw abundance in the recent sampling period (#) * *Hist_Lower_Lim*: historical lower range limit (m) * *Hist_Upper_Lim*: historical upper range limit (m) * *Hist_Optimal*: historical optimum/abundance-weighted-mean elevation (m) * *Hist_Midpoint*: historical midpoint elevation (lower + upper elevational limit divided by two) (m) * *Hist_Elev_Range_Extent_Half*: elevational range of species divided by two (m) * *Hist_Lean_Meters*: overall lean by which a species optimum is above or below its midpoint (m) * *Hist_Lean_Percent*: lean metric from above but standardized by elevational range extent of species (%) * *Lower_Lim_Shift_Meters*: shift distance of lower range limit over time (m) * *Rate_Lower_Per_Year*: range-limit shift distance divided by time span between surveys (m/year) * *Rate_Lower_Decade*: range-limit shift distance divided by time span between surveyed, multiplied by ten (m/decade) * *Curr_Lower*: current lower range limit (m) * *Curr_Upper*: current upper range limit (m) * *Curr_Optimal*: current optimum/abundance-weighted-mean elevation (m) * *Curr_Midpoint*: current midpoint elevation (lower + upper elevational limit divided by two) (m) * *Curr_Elevational_Range_Extent_Half*: elevational range of species divided by two (m) * *Curr_Lean_Meters*: overall lean by which a species optimum is above or below its midpoint (m) * *Curr_Lean_Percent*: lean metric from above but standardized by elevational range extent of species (%) * *Citation*: original study from which data were derived * *Taxa*: taxonomic group to which a species belongs * *Continent*: continent where original study was conducted * Missing data code: NA Globally, many species’ distributions are shifting in response to contemporary climate change. However, the direction and rate of shifts remain difficult to predict, impeding managers' abilities to allocate resources most effectively. Here, we explore a new approach for forecasting species' range-limit shifts that requires only abundance data along environmental (eg elevational) gradients. We hypothesized that species’ abundance distributions could provide information on the likelihood of future range-limit shifts. We tested this prediction using data from several transect studies that compared historical and contemporary distributions. Consistent with our prediction, we found that strong asymmetry in abundance distributions (ie “leaning” distributions) indeed preceded species’ lower-limit range shifts (Fisher's exact test P < 0.001, R2 = 0.28). Accordingly, surveying abundances along environmental gradients may be one promising, cost-effective method for forecasting local shifts. Ideally, practitioners will be able to incorporate this approach into species-specific management planning and to inform on-the-ground conservation efforts. Data were extracted from eight cited peer-reviewed studies in total. These studies cover a range of species, biomes, and regions across the globe. The accompanying data here have been centralized and processed to include the key metrics we discuss in our manuscript such as the historical and current range limits, species' midpoints, optimum elevations, leans in meters, leans as percentages, and lower-range limits shift rates per year and decade. 

AbstractSpecies are frequently responding to contemporary climate change by shifting to higher elevations and poleward to track suitable climate space. However, depending on local conditions and species’ sensitivity, the nature of these shifts can be highly variable and difficult to predict. Here, we examine how the American pika (Ochotona princeps), a philopatric, montane lagomorph, responds to climatic gradients at three spatial scales. Using mixed‐effects modeling in an information‐theoretic approach, we evaluated a priori model suites regarding predictors of site occupancy, relative abundance, and elevational‐range retraction across 760 talus patches, nested within 64 watersheds across the Northern Rocky Mountains of North America, during 2017–2020. The top environmental predictors differed across these response metrics. Warmer temperatures in summer and winter were associated with lower occupancy, lower relative abundances, and greater elevational retraction across watersheds. Occupancy was also strongly influenced by habitat patch size, but only when combined with climate metrics such as actual evapotranspiration. Using a second analytical approach, acute heat stress and summer precipitation best explained retraction residuals (i.e., the relative extent of retraction given the original elevational range of occupancy). Despite the study domain occurring near the species’ geographic‐range center, where populations might have higher abundances and be at lower risk of climate‐related stress, 33.9% of patches showed evidence of recent extirpations. Pika‐extirpated sites averaged 1.44℃ warmer in summer than did occupied sites. Additionally, the minimum elevation of pika occupancy has retracted upslope in 69% of watersheds (mean: 281 m). Our results emphasize the nuance associated with evaluating species’ range dynamics in response to climate gradients, variability, and temperature exceedances, especially in regions where species occupy gradients of conditions that may constitute multiple range edges. Furthermore, this study highlights the importance of evaluating diverse drivers across response metrics to improve the predictive accuracy of widely used, correlative models.

AbstractSpecies are frequently responding to contemporary climate change by shifting to higher elevations and poleward to track suitable climate space. However, depending on local conditions and species’ sensitivity, the nature of these shifts can be highly variable and difficult to predict. Here, we examine how the American pika (Ochotona princeps), a philopatric, montane lagomorph, responds to climatic gradients at three spatial scales. Using mixed‐effects modeling in an information‐theoretic approach, we evaluated a priori model suites regarding predictors of site occupancy, relative abundance, and elevational‐range retraction across 760 talus patches, nested within 64 watersheds across the Northern Rocky Mountains of North America, during 2017–2020. The top environmental predictors differed across these response metrics. Warmer temperatures in summer and winter were associated with lower occupancy, lower relative abundances, and greater elevational retraction across watersheds. Occupancy was also strongly influenced by habitat patch size, but only when combined with climate metrics such as actual evapotranspiration. Using a second analytical approach, acute heat stress and summer precipitation best explained retraction residuals (i.e., the relative extent of retraction given the original elevational range of occupancy). Despite the study domain occurring near the species’ geographic‐range center, where populations might have higher abundances and be at lower risk of climate‐related stress, 33.9% of patches showed evidence of recent extirpations. Pika‐extirpated sites averaged 1.44℃ warmer in summer than did occupied sites. Additionally, the minimum elevation of pika occupancy has retracted upslope in 69% of watersheds (mean: 281 m). Our results emphasize the nuance associated with evaluating species’ range dynamics in response to climate gradients, variability, and temperature exceedances, especially in regions where species occupy gradients of conditions that may constitute multiple range edges. Furthermore, this study highlights the importance of evaluating diverse drivers across response metrics to improve the predictive accuracy of widely used, correlative models.