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Leaf water content contributes to global leaf trait relationships
Leaf functional traits are important indicators of plant growth and ecosystem dynamics. Despite a wealth of knowledge about leaf trait relationships, a mechanistic understanding of how biotic and abiotic factors quantitatively influence leaf trait variation and scaling is still incomplete. We propos...
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/PMC9492732/ https://www.ncbi.nlm.nih.gov/pubmed/36130948 http://dx.doi.org/10.1038/s41467-022-32784-1 |
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author | Wang, Zhiqiang Huang, Heng Wang, Han Peñuelas, Josep Sardans, Jordi Niinemets, Ülo Niklas, Karl J. Li, Yan Xie, Jiangbo Wright, Ian J. |
author_facet | Wang, Zhiqiang Huang, Heng Wang, Han Peñuelas, Josep Sardans, Jordi Niinemets, Ülo Niklas, Karl J. Li, Yan Xie, Jiangbo Wright, Ian J. |
author_sort | Wang, Zhiqiang |
collection | PubMed |
description | Leaf functional traits are important indicators of plant growth and ecosystem dynamics. Despite a wealth of knowledge about leaf trait relationships, a mechanistic understanding of how biotic and abiotic factors quantitatively influence leaf trait variation and scaling is still incomplete. We propose that leaf water content (LWC) inherently affects other leaf traits, although its role has been largely neglected. Here, we present a modification of a previously validated model based on metabolic theory and use an extensive global leaf trait dataset to test it. Analyses show that mass-based photosynthetic capacity and specific leaf area increase nonlinearly with LWC, as predicted by the model. When the effects of temperature and LWC are controlled, the numerical values for the leaf area-mass scaling exponents converge onto 1.0 across plant functional groups, ecosystem types, and latitudinal zones. The data also indicate that leaf water mass is a better predictor of whole-leaf photosynthesis and leaf area than whole-leaf nitrogen and phosphorus masses. Our findings highlight a comprehensive theory that can quantitatively predict some global patterns from the leaf economics spectrum. |
format | Online Article Text |
id | pubmed-9492732 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-94927322022-09-23 Leaf water content contributes to global leaf trait relationships Wang, Zhiqiang Huang, Heng Wang, Han Peñuelas, Josep Sardans, Jordi Niinemets, Ülo Niklas, Karl J. Li, Yan Xie, Jiangbo Wright, Ian J. Nat Commun Article Leaf functional traits are important indicators of plant growth and ecosystem dynamics. Despite a wealth of knowledge about leaf trait relationships, a mechanistic understanding of how biotic and abiotic factors quantitatively influence leaf trait variation and scaling is still incomplete. We propose that leaf water content (LWC) inherently affects other leaf traits, although its role has been largely neglected. Here, we present a modification of a previously validated model based on metabolic theory and use an extensive global leaf trait dataset to test it. Analyses show that mass-based photosynthetic capacity and specific leaf area increase nonlinearly with LWC, as predicted by the model. When the effects of temperature and LWC are controlled, the numerical values for the leaf area-mass scaling exponents converge onto 1.0 across plant functional groups, ecosystem types, and latitudinal zones. The data also indicate that leaf water mass is a better predictor of whole-leaf photosynthesis and leaf area than whole-leaf nitrogen and phosphorus masses. Our findings highlight a comprehensive theory that can quantitatively predict some global patterns from the leaf economics spectrum. Nature Publishing Group UK 2022-09-21 /pmc/articles/PMC9492732/ /pubmed/36130948 http://dx.doi.org/10.1038/s41467-022-32784-1 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 Wang, Zhiqiang Huang, Heng Wang, Han Peñuelas, Josep Sardans, Jordi Niinemets, Ülo Niklas, Karl J. Li, Yan Xie, Jiangbo Wright, Ian J. Leaf water content contributes to global leaf trait relationships |
title | Leaf water content contributes to global leaf trait relationships |
title_full | Leaf water content contributes to global leaf trait relationships |
title_fullStr | Leaf water content contributes to global leaf trait relationships |
title_full_unstemmed | Leaf water content contributes to global leaf trait relationships |
title_short | Leaf water content contributes to global leaf trait relationships |
title_sort | leaf water content contributes to global leaf trait relationships |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9492732/ https://www.ncbi.nlm.nih.gov/pubmed/36130948 http://dx.doi.org/10.1038/s41467-022-32784-1 |
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