Trait-based projections of climate change effects on global biome distributions

Aim: Climate change will likely modify the global distribution of biomes, but the magnitude of change is debated. Here, we followed a trait-based, statistical approach to model the influence of climate change on the global distribution of biomes. Location: Global. Methods: We predicted the global di...

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Published in:Diversity and Distributions
Main Authors: Boonman C. C. F., Huijbregts M. A. J., Benitez-Lopez A., Schipper A. M., Thuiller W., Santini L.
Other Authors: Boonman, C. C. F., Huijbregts, M. A. J., Benitez-Lopez, A., Schipper, A. M., Thuiller, W., Santini, L.
Format: Article in Journal/Newspaper
Language:English
Published: John Wiley and Sons Inc 2022
Subjects:
Online Access:http://hdl.handle.net/11573/1614901
https://doi.org/10.1111/ddi.13431
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author Boonman C. C. F.
Huijbregts M. A. J.
Benitez-Lopez A.
Schipper A. M.
Thuiller W.
Santini L.
author2 Boonman, C. C. F.
Huijbregts, M. A. J.
Benitez-Lopez, A.
Schipper, A. M.
Thuiller, W.
Santini, L.
author_facet Boonman C. C. F.
Huijbregts M. A. J.
Benitez-Lopez A.
Schipper A. M.
Thuiller W.
Santini L.
author_sort Boonman C. C. F.
collection Sapienza Università di Roma: CINECA IRIS
container_issue 1
container_start_page 25
container_title Diversity and Distributions
container_volume 28
description Aim: Climate change will likely modify the global distribution of biomes, but the magnitude of change is debated. Here, we followed a trait-based, statistical approach to model the influence of climate change on the global distribution of biomes. Location: Global. Methods: We predicted the global distribution of plant community mean specific leaf area (SLA), height and wood density as a function of climate and soil characteristics using an ensemble of statistical models. Then, we predicted the probability of occurrence of biomes as a function of the three traits with a classification model. Finally, we projected changes in plant community mean traits and corresponding changes in biome distributions to 2070 for low (RCP 2.6; +1.2°C) and extreme (RCP 8.5; +3.5°C) future climate change scenarios. Results: We estimated that under the low climate change scenario (sub)tropical biomes will expand (forest by 18%–22%, grassland by 9%–14% and xeric shrubland by 5%–8%), whereas tundra and temperate broadleaved and mixed forests contract by 30%–34% and 16%–21%, respectively. Our results also indicate that over 70%–75% of the current distribution of temperate broadleaved and mixed forests and temperate grasslands is projected to shift northwards. These changes become amplified under the extreme climate change scenario in which tundra is projected to lose more than half of its current extent. Main conclusions: Our results indicate considerable imminent alterations in the global distribution of biomes, with possibly major consequences for life on Earth. The level of accuracy of our model given the limited input data and the insights on how trait–environment relationships can influence biome distributions suggest that trait-based correlative approaches are a promising tool to forecast vegetation change and to provide an independent, complementary line of evidence next to process-based vegetation models.
format Article in Journal/Newspaper
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op_doi https://doi.org/10.1111/ddi.13431
op_relation info:eu-repo/semantics/altIdentifier/wos/WOS:000715891000001
volume:28
issue:1
firstpage:25
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journal:DIVERSITY AND DISTRIBUTIONS
http://hdl.handle.net/11573/1614901
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spelling ftunivromairis:oai:iris.uniroma1.it:11573/1614901 2025-05-18T14:07:43+00:00 Trait-based projections of climate change effects on global biome distributions Boonman C. C. F. Huijbregts M. A. J. Benitez-Lopez A. Schipper A. M. Thuiller W. Santini L. Boonman, C. C. F. Huijbregts, M. A. J. Benitez-Lopez, A. Schipper, A. M. Thuiller, W. Santini, L. 2022 http://hdl.handle.net/11573/1614901 https://doi.org/10.1111/ddi.13431 eng eng John Wiley and Sons Inc place:111 RIVER ST, HOBOKEN 07030-5774, NJ USA info:eu-repo/semantics/altIdentifier/wos/WOS:000715891000001 volume:28 issue:1 firstpage:25 lastpage:37 numberofpages:13 journal:DIVERSITY AND DISTRIBUTIONS http://hdl.handle.net/11573/1614901 doi:10.1111/ddi.13431 info:eu-repo/semantics/openAccess biome distribution climate change Gaussian mixture model global vegetation plant height specific leaf area traits-based model wood density info:eu-repo/semantics/article 2022 ftunivromairis https://doi.org/10.1111/ddi.13431 2025-04-24T14:16:52Z Aim: Climate change will likely modify the global distribution of biomes, but the magnitude of change is debated. Here, we followed a trait-based, statistical approach to model the influence of climate change on the global distribution of biomes. Location: Global. Methods: We predicted the global distribution of plant community mean specific leaf area (SLA), height and wood density as a function of climate and soil characteristics using an ensemble of statistical models. Then, we predicted the probability of occurrence of biomes as a function of the three traits with a classification model. Finally, we projected changes in plant community mean traits and corresponding changes in biome distributions to 2070 for low (RCP 2.6; +1.2°C) and extreme (RCP 8.5; +3.5°C) future climate change scenarios. Results: We estimated that under the low climate change scenario (sub)tropical biomes will expand (forest by 18%–22%, grassland by 9%–14% and xeric shrubland by 5%–8%), whereas tundra and temperate broadleaved and mixed forests contract by 30%–34% and 16%–21%, respectively. Our results also indicate that over 70%–75% of the current distribution of temperate broadleaved and mixed forests and temperate grasslands is projected to shift northwards. These changes become amplified under the extreme climate change scenario in which tundra is projected to lose more than half of its current extent. Main conclusions: Our results indicate considerable imminent alterations in the global distribution of biomes, with possibly major consequences for life on Earth. The level of accuracy of our model given the limited input data and the insights on how trait–environment relationships can influence biome distributions suggest that trait-based correlative approaches are a promising tool to forecast vegetation change and to provide an independent, complementary line of evidence next to process-based vegetation models. Article in Journal/Newspaper Tundra Sapienza Università di Roma: CINECA IRIS Diversity and Distributions 28 1 25 37
spellingShingle biome distribution
climate change
Gaussian mixture model
global vegetation
plant height
specific leaf area
traits-based model
wood density
Boonman C. C. F.
Huijbregts M. A. J.
Benitez-Lopez A.
Schipper A. M.
Thuiller W.
Santini L.
Trait-based projections of climate change effects on global biome distributions
title Trait-based projections of climate change effects on global biome distributions
title_full Trait-based projections of climate change effects on global biome distributions
title_fullStr Trait-based projections of climate change effects on global biome distributions
title_full_unstemmed Trait-based projections of climate change effects on global biome distributions
title_short Trait-based projections of climate change effects on global biome distributions
title_sort trait-based projections of climate change effects on global biome distributions
topic biome distribution
climate change
Gaussian mixture model
global vegetation
plant height
specific leaf area
traits-based model
wood density
topic_facet biome distribution
climate change
Gaussian mixture model
global vegetation
plant height
specific leaf area
traits-based model
wood density
url http://hdl.handle.net/11573/1614901
https://doi.org/10.1111/ddi.13431