Global biodiversity is undergoing rapid declines, driven in large part by changes to land use and climate. Global models help us to understand the consequences of environmental changes for biodiversity, but tend to neglect important geographical variation in the sensitivity of biodiversity to these changes. Here we test whether biodiversity responses to climate change and land-use change differ among biomes (geographical units that have marked differences in environment and species composition). We find the strongest negative responses to both pressures in tropical biomes and in the Mediterranean. A further analysis points towards similar underlying drivers for the sensitivity to each pressure: we find both greater reductions in species richness in the types of land use most disturbed by humans and more negative predicted responses to climate change in areas of lower climatic seasonality, and in areas where a greater proportion of species are near their upper temperature limit. Within the land most modified by humans, reductions in biodiversity were particularly large in regions where humans have come to dominate the land more recently. Our results will help to improve predictions of how biodiversity is likely to change with ongoing climatic and land-use changes, pointing toward particularly large declines in the tropics where much future agricultural expansion is expected to occur. This finding could help to inform the development of the post-2020 biodiversity framework, by highlighting the under-studied regions where biodiversity losses are likely to be greatest.
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All data required to run the analyses are published on FigShare: https://doi.org/10.6084/m9.figshare.12674372.
All code used in the analyses is publicly available at: https://github.com/timnewbold/BiomeSpecificResponsesPublic.
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This work was supported by a Royal Society University Research Fellowship to T.N. J.J.W. and A.E. were supported by research grants from the Royal Society, awarded to T.N.
The authors declare no competing interests.
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Extended Data Fig. 1 Map of sites with data in the PREDICTS database used for analysing land-use responses.
Points are coloured by one of the classifications of biomes, which we used in our analyses.
Results are shown for three community-level measures of biodiversity: total sampled species richness, total sampled community abundance, and community-average range size. The last is a measure of the inverse of the endemicity of species within communities, and is the average of the range sizes of all sampled species in the community, weighted by sampled abundance. All values are expressed as a percentage change relative to primary vegetation as the baseline. Numbers in parentheses are the lower and upper bounds of the 95% confidence limits.
Extended Data Fig. 3 Statistics for mixed-effects models of species richness with different land-use groupings.
Species richness was modelled as a function of both land use (using the different combinations as shown here) and biome (using the finest division into 11 different biomes). Shown are the model degrees of freedom (DF), difference in AIC compared with the best-fitting model (ΔAIC), and the conditional and marginal R2 values72. The best-fitting model is shown in italics, while the land-use combination used in the final models is shown in bold. PV = Primary Vegetation; SV = Secondary Vegetation; PF = Plantation Forest; CR = Cropland; PA = Pasture; Agric. = Cleared Agriculture (Cropland + Pasture); Harv. = Harvested agriculture (Plantation Forest + Cropland); Human = Human-dominated Land use (Plantation Forest + Cropland + Pasture).
Species richness was modelled as a function of both land use (using the finest division into five different land-use categories) and biome (using the different combinations as shown here). Shown are the model degrees of freedom (DF), difference in AIC compared with the best fitting model (ΔAIC), and the conditional and marginal R2 values72. The best-fitting model is shown in italics, while the biome combination used in the final models is shown in bold. BF = Boreal Forests/Taiga; TeCF = Temperate Conifer Forests; TeBF = Temperate Broadleaf and Mixed Forests; TrCF = Tropical and Subtropical Coniferous Forests; TrDBF = Tropical and Subtropical Dry Broadleaf Forests; TrMBF = Tropical and Subtropical Moist Broadleaf Forests; TeG = Temperate Grasslands, Savannas and Shrublands; TrG = Tropical and Subtropical Grasslands, Savannas and Shrublands; MoG = Montane Grasslands and Shrublands; MED = Mediterranean Forests, Woodlands and Scrub; DRY = Deserts and Xeric Shrublands; TeF = Temperate Forests (Coniferous and Broadleaf); TrF = Tropical Forests (Coniferous, Dry Broadleaf and Moist Broadleaf); TeMoG = Temperate and Montane Grasslands; Temp. = Temperate (Forests and Grasslands, including Montane Grasslands); Trop. = Tropical (Forests and Grasslands); NonTrop. = Non-Tropical (Boreal and Temperate Forest and Grasslands, including Montane Grasslands); For. = Forest (Boreal, Temperate and Tropical); Grass. = Grasslands (Temperate, Montane and Tropical).
a) Tropical forest; b) Tropical grasslands; c) Drylands; d) Mediterranean; e) Temperate forest; and f) Temperate grasslands. Plots show the percentage change in species richness compared to primary vegetation (PV), in secondary vegetation (SV), pasture (PAS) and areas of harvested agriculture (woody plantations and herbaceous croplands; HARV). Error bars show 95% confidence intervals. Sample sizes at the bottom of each panel refer to the number of sites in each combination of land use and biome. The final model plotted here had an R2conditional of 0.89 and an R2marginal of 0.031.
Extended Data Fig. 6 Differences in community-average range size (RCAR) among land-use types, across different biomes.
a) Tropical forest; b) Tropical grasslands; c) Drylands; d) Mediterranean; e) Temperate forest; and f) Temperate grasslands. Plots show the percentage change in species richness compared to primary vegetation (PV), in secondary vegetation (SV), pasture (PAS) and areas of harvested agriculture (woody plantations and herbaceous croplands; HARV). Error bars show 95% confidence intervals. Sample sizes at the bottom of each panel refer to the number of sites in each combination of land use and biome. The final model plotted here had an R2conditional of 0.87 and an R2marginal of 0.10.
Shown is the predicted percentage change in species richness for each °C of climate warming expected under the RCP 2.6 scenario. Results for the RCP 8.5 scenario are shown in Fig. 2. Biomes considered were tropical forests (TrF), tropical grasslands (TrG), drylands (Dry), Mediterranean (Med), temperate forest (TeF), temperate grasslands (TeG) and boreal forest (BoF). Thick horizontal black lines show median values across all grid cells within the biome, boxes extend to the first and third quartiles, and whiskers to 1.5 × the inter-quartile range.
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Newbold, T., Oppenheimer, P., Etard, A. et al. Tropical and Mediterranean biodiversity is disproportionately sensitive to land-use and climate change. Nat Ecol Evol 4, 1630–1638 (2020). https://doi.org/10.1038/s41559-020-01303-0
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