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Widespread increasing vegetation sensitivity to soil moisture
Global vegetation and associated ecosystem services critically depend on soil moisture availability which has decreased in many regions during the last three decades. While spatial patterns of vegetation sensitivity to global soil water have been recently investigated, long-term changes in vegetatio...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9270344/ https://www.ncbi.nlm.nih.gov/pubmed/35803919 http://dx.doi.org/10.1038/s41467-022-31667-9 |
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author | Li, Wantong Migliavacca, Mirco Forkel, Matthias Denissen, Jasper M. C. Reichstein, Markus Yang, Hui Duveiller, Gregory Weber, Ulrich Orth, Rene |
author_facet | Li, Wantong Migliavacca, Mirco Forkel, Matthias Denissen, Jasper M. C. Reichstein, Markus Yang, Hui Duveiller, Gregory Weber, Ulrich Orth, Rene |
author_sort | Li, Wantong |
collection | PubMed |
description | Global vegetation and associated ecosystem services critically depend on soil moisture availability which has decreased in many regions during the last three decades. While spatial patterns of vegetation sensitivity to global soil water have been recently investigated, long-term changes in vegetation sensitivity to soil water availability are still unclear. Here we assess global vegetation sensitivity to soil moisture during 1982-2017 by applying explainable machine learning with observation-based leaf area index (LAI) and hydro-climate anomaly data. We show that LAI sensitivity to soil moisture significantly increases in many semi-arid and arid regions. LAI sensitivity trends are associated with multiple hydro-climate and ecological variables, and strongest increasing trends occur in the most water-sensitive regions which additionally experience declining precipitation. State-of-the-art land surface models do not reproduce this increasing sensitivity as they misrepresent water-sensitive regions and sensitivity strength. Our sensitivity results imply an increasing ecosystem vulnerability to water availability which can lead to exacerbated reductions in vegetation carbon uptake under future intensified drought, consequently amplifying climate change. |
format | Online Article Text |
id | pubmed-9270344 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-92703442022-07-10 Widespread increasing vegetation sensitivity to soil moisture Li, Wantong Migliavacca, Mirco Forkel, Matthias Denissen, Jasper M. C. Reichstein, Markus Yang, Hui Duveiller, Gregory Weber, Ulrich Orth, Rene Nat Commun Article Global vegetation and associated ecosystem services critically depend on soil moisture availability which has decreased in many regions during the last three decades. While spatial patterns of vegetation sensitivity to global soil water have been recently investigated, long-term changes in vegetation sensitivity to soil water availability are still unclear. Here we assess global vegetation sensitivity to soil moisture during 1982-2017 by applying explainable machine learning with observation-based leaf area index (LAI) and hydro-climate anomaly data. We show that LAI sensitivity to soil moisture significantly increases in many semi-arid and arid regions. LAI sensitivity trends are associated with multiple hydro-climate and ecological variables, and strongest increasing trends occur in the most water-sensitive regions which additionally experience declining precipitation. State-of-the-art land surface models do not reproduce this increasing sensitivity as they misrepresent water-sensitive regions and sensitivity strength. Our sensitivity results imply an increasing ecosystem vulnerability to water availability which can lead to exacerbated reductions in vegetation carbon uptake under future intensified drought, consequently amplifying climate change. Nature Publishing Group UK 2022-07-08 /pmc/articles/PMC9270344/ /pubmed/35803919 http://dx.doi.org/10.1038/s41467-022-31667-9 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Li, Wantong Migliavacca, Mirco Forkel, Matthias Denissen, Jasper M. C. Reichstein, Markus Yang, Hui Duveiller, Gregory Weber, Ulrich Orth, Rene Widespread increasing vegetation sensitivity to soil moisture |
title | Widespread increasing vegetation sensitivity to soil moisture |
title_full | Widespread increasing vegetation sensitivity to soil moisture |
title_fullStr | Widespread increasing vegetation sensitivity to soil moisture |
title_full_unstemmed | Widespread increasing vegetation sensitivity to soil moisture |
title_short | Widespread increasing vegetation sensitivity to soil moisture |
title_sort | widespread increasing vegetation sensitivity to soil moisture |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9270344/ https://www.ncbi.nlm.nih.gov/pubmed/35803919 http://dx.doi.org/10.1038/s41467-022-31667-9 |
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