Abstract
The frequency, duration, and intensity of extreme thermal events are increasing and are projected to further increase by the end of the century1,2. Despite the considerable consequences of temperature extremes on biological systems3,4,5,6,7,8, we do not know which species and locations are most exposed worldwide. Here we provide a global assessment of land vertebrates’ exposures to future extreme thermal events. We use daily maximum temperature data from 1950 to 2099 to quantify future exposure to high frequency, duration, and intensity of extreme thermal events to land vertebrates. Under a high greenhouse gas emission scenario (Shared Socioeconomic Pathway 5–8.5 (SSP5–8.5); 4.4 °C warmer world), 41.0% of all land vertebrates (31.1% mammals, 25.8% birds, 55.5% amphibians and 51.0% reptiles) will be exposed to extreme thermal events beyond their historical levels in at least half their distribution by 2099. Under intermediate-high (SSP3–7.0; 3.6 °C warmer world) and intermediate (SSP2–4.5; 2.7 °C warmer world) emission scenarios, estimates for all vertebrates are 28.8% and 15.1%, respectively. Importantly, a low-emission future (SSP1–2.6, 1.8 °C warmer world) will greatly reduce the overall exposure of vertebrates (6.1% of species) and can fully prevent exposure in many species assemblages. Mid-latitude assemblages (desert, shrubland, and grassland biomes), rather than tropics9,10, will face the most severe exposure to future extreme thermal events. By 2099, under SSP5–8.5, on average 3,773 species of land vertebrates (11.2%) will face extreme thermal events for more than half a year period. Overall, future extreme thermal events will force many species and assemblages into constant severe thermal stress. Deep greenhouse gas emissions cuts are urgently needed to limit species’ exposure to thermal extremes.
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Data availability
The NEX-GDDP CMIP6 climate data layer for the five GCMs were obtained from the NEX-GDDP CMIP6 webpage (https://nccs.nasa.gov/services/data-collections/land-based-products/NEX-GDDP-CMIP6; accessed January 2022). The NEX-GDDP CMIP5 climate data layer for the five GCMs were obtained from Amazon web services (https://data.nasa.gov/Earth-Science/Amazon-Web-Services-NASA-Earth-Exchange-NEX-Global/7yme-6yjr; accessed November 2020). Climate data for the low-emission scenario were downloaded from the original CMIP6 runs (coarse resolution) from the Copernicus Climate Data Store (https://cds.climate.copernicus.eu; accessed January 2022). ECMFW ERA5 data were obtained from Copernicus Climate Data Store (https://cds.climate.copernicus.eu; accessed November 2020). Species distribution data are available for mammals and amphibians from the IUCN (https://iucn.org; accessed November 2020), birds from BirdLife International (https://birdlife.org; accessed November 2020); reptiles from GARD initiative (https://doi.org/10.5061/dryad.9cnp5hqmb; accessed November 2020). Physiological thermal tolerance data were obtained from the GlobTherm database (https://doi.org/10.1038/sdata.2018.22; accessed November 2020). Source data are provided with this paper.
Code availability
The R codes associated with the study are available at FigShare (https://doi.org/10.6084/m9.figshare.16641079).
Change history
06 February 2023
A Correction to this paper has been published: https://doi.org/10.1038/s41586-023-05785-3
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Acknowledgements
We thank the staff at the IUCN for making the species distribution data publicly available; J. Rosenblatt for allowing us to use his server. U.R. and S.M. acknowledge funding from the Israeli Science Foundation (grant no. ISF-406/19); G.M. is supported by the Swiss Institute for Dryland Environmental and Energy Research, and the Planning and Budgeting Committee postdoctoral fellowships. Climate scenarios used were from the NEX-GDDP CMIP6 dataset, prepared by the Climate Analytics Group and NASA Ames Research Center using the NASA Earth Exchange, and distributed by the NASA Center for Climate Simulation (NCCS). We acknowledge the computational resources provided by the High-Performance Computation facility at the Ben-Gurion University of the Negev (BGU HPC) and the Ben-Gurion University of the Negev Department of Computer Science clusters (BGU ISE-CS-DT).
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G.M. conceived the study, developed the methods, handled all data processing, performed the analyses and generated the figures with input from T.I., S.M. and U.R. All of the authors contributed to writing of the manuscript.
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Extended data figures and tables
Extended Data Fig. 1 Overview of methods employed for estimating species range exposure to extreme thermal events.
Illustrated using the geographical range of the Colorado river toad Incilius alvarius. Stage 1: species-specific threshold is calculated as the spatial maximum of 99% daily maximum temperature between the years 1950 to 2005 (PTmax99 – indicated by a red arrow). Stage 2 and 3: extreme thermal event metrics – frequency (F), duration (D), and intensity (I) for future (indicated by letter F before each metric) and historical (indicated by letter H before each metric) period was calculated by comparing PTmax99 with daily maximum temperature time series per grid-cell for each year. Extreme event was designated if the daily maximum temperature is above the species-specific threshold for more than 5 or 10 consecutive days. Stage 4: to designate grid-cell exposure, future extreme event metric per year was compared against the maximum of historical metric (Hfmax, Hdmax, and HImax). Stage 2 to 4 are repeated for each year (indicated by the circular arrow).
Extended Data Fig. 2 Comparisons of species-specific thresholds (PTmax99) and physiological upper thermal tolerances.
Species physiological upper thermal tolerance data [the upper boundary of the thermal neutral zone (UTNZ) for mammals and birds; critical thermal maximum (CTmax) for reptiles and amphibians] are compared against the model specific species-specific threshold (PTmax99) estimated from the NEX-GDDP CMIP6 dataset for each taxonomic group. Two-sided unadjusted P-values and ρ – Spearman’s correlation coefficient are shown. 1:1 line represented with red dashed line.
Extended Data Fig. 3 Species geographical range exposure under different thresholds and datasets.
Results presented for a–b when the minimal number of days required to define extreme thermal events was more than 10 days instead of 5 days (uses NEX-GDDP CMIP6 dataset), c–d for three different SSPs using a coarse resolution dataset (~96.5 km2 grid-cells; CMIP6 original runs), e–f estimates based on mean annual temperature (NEP-GDDP CMIP6), and g–h for data from NEX-GDDP CMIP5 dataset. (a,c, and g) percentage of species exposed in more than half of their geographical range to extreme thermal events by 2099 for combined exposure quantified by spatially aggregating exposure to all three metrics within the species range. Actual estimates from five GCMs (different point shapes) are presented (median model as solid triangle). (b,d, and h) mean percentage of range exposed to extreme thermal events over time as the combined exposure to all three metrics across species range. Side panel represents mean percentage range exposure of the median model (circles) and range (error bar with maximum and minimum model estimates). Estimate from five GCMs are presented per SSP scenario (the median model is highlighted as solid line). e–f same as in the other panel but uses mean annual temperature data (see methods). Scenarios and corresponding mean global warming by 2100 compared to pre-industrial conditions (1850–1900): SSP1–2.6 (1.8 °C), SSP2–4.5 (2.7 °C), SSP3–7.0 (3.6 °C), and SSP5–8.5 (4.4 °C).
Extended Data Fig. 4 Percentage of species exposed to extreme thermal events per assemblage averaged across 14 biome types by 2099.
Results are shown for a. frequency, b. duration, and c. intensity of extreme events for all land vertebrates and major taxonomic groups. The numbers on top of the bar plot represent the corresponding biome type (legend provided on top of the figure). Results are shown for the SSP5–8.5. Results for other scenarios are presented in Supplementary Fig. S27–S29. SSP5–8.5 corresponds to a mean global warming of 4.4 °C by 2100 compared to pre-industrial conditions (1850–1900).
Extended Data Fig. 5 Spatial patterns of vertebrate assemblages at risk due to extreme thermal events by 2099 for data using coarse resolution (~96.5 km2 grid-cell) climate data.
Assemblage level (i.e., per grid-cell) exposure was quantified as the percentage of species present in each grid-cell exposed to a–c frequency, d–f duration, and g–i intensity of extreme events beyond their historical levels (corresponding latitudinal patterns as mean value per 96.5 km2 grid latitudinal band is presented in j–l). Median estimates from five GCMs are shown. Scenarios and corresponding mean global warming by 2100 compared to pre-industrial conditions (1850–1900): SSP1–2.6 (1.8 °C), SSP2–4.5 (2.7 °C), SSP3–7.0 (3.6 °C), and SSP5–8.5 (4.4 °C).
Extended Data Fig. 6 Regionally contrasting tropical species vulnerability to mean and extreme temperatures by 2099.
Bivariate map showing assemblage level percentage of vertebrate species exposure to extreme thermal events and mean annual temperature (a). For extreme thermal events, combined exposure was quantified by spatially aggregating exposure to all three metrics across the species range (same as in Fig. 1b), percentage of species exposure was then aggregated within each ~24.1 km2 grid-cells. b latitudinal patterns for assemblage level exposure to extreme thermal events (yellow) and mean annual temperatures (blue) are shown. Smoothened line represents generalized additive model fits of the percentage of species exposure against the latitude value of each grid-cell (GAM; both two-sided unadjusted P < 0.001). Median estimates from five GCMs are shown. Results are presented for the SSP5–8.5 scenario – 4.4 °C of warming by 2099 compared to pre-industrial conditions (1850–1900).
Extended Data Fig. 7 Spatial patterns of mammal assemblages at risk due to extreme thermal events by 2099.
Assemblage level (i.e., per grid-cell) exposure was quantified as the percentage of species present in each grid-cell exposed to a–c frequency, d–f duration, and g–i intensity of extreme events greater than the historical levels. Latitudinal patterns as the mean value per ~24.1 km2 latitudinal band are shown in j–l. See Supplementary Fig. S12 to S15 for results using SSP3–7.0. Maps show median estimates from five GCMs. Scenarios and corresponding mean global warming by 2100 compared to pre-industrial conditions (1850–1900): SSP1–2.6 (1.8 °C), SSP2–4.5 (2.7 °C), SSP3–7.0 (3.6 °C), and SSP5–8.5 (4.4 °C).
Extended Data Fig. 8 Spatial patterns of bird assemblages at risk due to extreme thermal events by 2099.
Assemblage level (i.e., per grid-cell) exposure was quantified as the percentage of species present in each grid-cell exposed to a–c frequency, d–f duration, and g–i intensity of extreme events greater than the historical levels. Latitudinal patterns as the mean value per ~24.1 km2 latitudinal band are shown in j–l. See Supplementary Fig. S12 to S15 for results using SSP3–7.0. Maps show median estimates from five GCMs. Scenarios and corresponding mean global warming by 2100 compared to pre-industrial conditions (1850–1900): SSP1–2.6 (1.8 °C), SSP2–4.5 (2.7 °C), SSP3–7.0 (3.6 °C), and SSP5–8.5 (4.4 °C).
Extended Data Fig. 9 Spatial patterns of amphibian assemblages at risk due to extreme thermal events by 2099.
Assemblage level (i.e., per grid-cell) exposure was quantified as the percentage of species present in each grid-cell exposed to a–c frequency, d–f duration, and g–i intensity of extreme events greater than the historical levels. Latitudinal patterns as the mean value per ~24.1 km2 latitudinal band are shown in j–l. See Supplementary Fig. S12 to S15 for results using SSP3–7.0. Maps show median estimates from five GCMs. Scenarios and corresponding mean global warming by 2100 compared to pre-industrial conditions (1850–1900): SSP1–2.6 (1.8 °C), SSP2–4.5 (2.7 °C), SSP3–7.0 (3.6 °C), and SSP5–8.5 (4.4 °C).
Extended Data Fig. 10 Spatial patterns of reptilian assemblages at risk due to extreme thermal events by 2099.
Assemblage level (i.e., per grid-cell) exposure was quantified as the percentage of species present in each grid-cell exposed to a–c frequency, d–f duration, and g–i intensity of extreme events greater than the historical levels. Latitudinal patterns as the mean value per ~24.1 km2 latitudinal band are shown in j–l. See Supplementary Fig. S12 to S15 for results using SSP3–7.0. Maps show median estimates from five GCMs. Scenarios and corresponding mean global warming by 2100 compared to pre-industrial conditions (1850–1900): SSP1–2.6 (1.8 °C), SSP2–4.5 (2.7 °C), SSP3–7.0 (3.6 °C), and SSP5–8.5 (4.4 °C).
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Supplementary Discussion; Supplementary Figs. 1-41; Supplementary Tables 1 and 2 and Supplementary References.
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Murali, G., Iwamura, T., Meiri, S. et al. Future temperature extremes threaten land vertebrates. Nature 615, 461–467 (2023). https://doi.org/10.1038/s41586-022-05606-z
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DOI: https://doi.org/10.1038/s41586-022-05606-z
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