Leaf water content contributes to global leaf trait relationships

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作者
Zhiqiang Wang
Heng Huang
Han Wang
Josep Peñuelas
Jordi Sardans
Ülo Niinemets
Karl J. Niklas
Yan Li
Jiangbo Xie
Ian J. Wright
机构
[1] Southwest Minzu University,Sichuan Zoige Alpine Wetland Ecosystem National Observation and Research Station
[2] Southwest Minzu University,Institute of Qinghai
[3] University of California,Tibetan Plateau
[4] Berkeley,Department of Environmental Science, Policy, and Management
[5] Texas A&M University,Department of Biological and Agricultural Engineering
[6] Tsinghua University,Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies
[7] CSIC,Institute of Agricultural and Environmental Sciences
[8] Global Ecology Unit,Plant Biology Section, School of Integrative Plant Science
[9] CREAF-CSIC-UAB,State Key Laboratory of Subtropical Silviculture
[10] CREAF,Hawkesbury Institute for the Environment
[11] Estonian University of Life Sciences,Department of Biological Sciences
[12] Kreutzwaldi 1,undefined
[13] Cornell University,undefined
[14] Zhejiang A&F University,undefined
[15] Western Sydney University,undefined
[16] Macquarie University,undefined
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摘要
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.
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