Leaf water content contributes to global leaf trait relationships
Wang, Zhiqiang (Southwest Minzu University. Institute of Qinghai-Tibetan Plateau)
Huang, Heng (Texas A&M University. Department of Biological and Agricultural Engineering)
Wang, Han (Tsinghua University. Department of Earth System Science)
Peñuelas, Josep (Centre de Recerca Ecològica i d'Aplicacions Forestals)
Sardans i Galobart, Jordi (Centre de Recerca Ecològica i d'Aplicacions Forestals)
Niinemets, Ülo (Estonian University of Life Sciences. Institute of Agricultural and Environmental Sciences)
Niklas, Karl J. (Cornell University. School of Integrative Plant Science)
Li, Yan (Zhejiang A&F University. State Key Laboratory of Subtropical Silviculture)
Xie, Jiangbo (Zhejiang A&F University. State Key Laboratory of Subtropical Silviculture)
Wright, Ian J. (Macquarie University. Department of Biological Sciences)

Date:	2022
Abstract:	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. Leaf functional traits are increasingly used as proxies for plant functions. Here, the authors show that leaf water affects other leaf traits and is a better predictor of whole-leaf photosynthesis and leaf area than leaf nitrogen or phosphorus content.
Grants:	Agencia Estatal de Investigación PID2019−110521GB-I00 Agencia Estatal de Investigación PID2020-115770RB-I Agència de Gestió d'Ajuts Universitaris i de Recerca 2017/SGR−1005 Agència de Gestió d'Ajuts Universitaris i de Recerca 2020/PANDE00117 European Commission 610028
Rights:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original.
Language:	Anglès
Document:	Article ; recerca ; Versió publicada
Subject:	Plant ecology ; Ecological modelling
Published in:	Nature communications, Vol. 13 (September 2022) , art. 5525, ISSN 2041-1723

DOI: 10.1038/s41467-022-32784-1
PMID: 36130948

9 p, 2.3 MB

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