Leaf water content contributes to global leaf trait relationships.

Area of Science:

• Plant Ecology
• Plant Physiology
• Ecosystem Dynamics

Background:

• Leaf functional traits are key indicators of plant health and ecosystem function.
• Existing models lack a mechanistic understanding of how biotic and abiotic factors influence leaf trait variation.
• The role of leaf water content (LWC) in leaf trait relationships has been largely overlooked.

Purpose of the Study:

• To investigate the quantitative influence of LWC on leaf trait variation and scaling.
• To test a modified metabolic theory model predicting LWC's effect on leaf traits.
• To explore LWC as a predictor of whole-leaf photosynthesis and area.

Main Methods:

• Modification of a metabolic theory-based model.
• Utilizing an extensive global leaf trait dataset for analysis.
• Controlling for temperature and LWC to analyze leaf area-mass scaling exponents.

Main Results:

• Mass-based photosynthetic capacity and specific leaf area show nonlinear increases with LWC.
• Leaf area-mass scaling exponents converge to 1.0 when temperature and LWC are controlled across diverse plant groups and ecosystems.
• Leaf water mass is a stronger predictor of photosynthesis and leaf area than nitrogen or phosphorus mass.

Conclusions:

• LWC is a critical, often neglected, factor influencing leaf traits and scaling.
• The modified model successfully predicts global patterns in leaf economics spectrum traits.
• Findings provide a more comprehensive theory for understanding plant trait variation and ecosystem dynamics.