Data from: Forecasting range shifts using abundance distributions along environmental gradients
Data files
Sep 10, 2024 version files 17.08 KB
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Billmanetal2024.csv
12.51 KB
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README.md
4.57 KB
Abstract
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.
README: Data for "Using abundance distributions along environmental gradients to forecast range shifts"
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
Sharing/Access information
- 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
Methods
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.