Parsimony vs predictive and functional performance of three stomatal optimization principles in a big-leaf framework.

Area of Science:

• Ecology
• Environmental Science
• Plant Physiology

Background:

• Stomatal optimization models are crucial for estimating ecosystem water and carbon fluxes.
• Current models lack consensus on the most effective formulations for ecosystem-scale applications.

Purpose of the Study:

• To evaluate and compare different stomatal conductance formulations for ecosystem-scale modeling.
• To determine which optimization principles best align with flux tower data across diverse biomes.

Main Methods:

• Implemented three analytical stomatal conductance equations with varying water penalty functions within a big-leaf framework.
• Utilized information theory to analyze soil water and atmospheric demand impacts on evapotranspiration.
• Ranked principles by parameter uncertainty, parsimony, and predictive/functional accuracy.

Main Results:

• All tested model variants demonstrated high performance.
• Explicit plant hydraulics in water penalty functions did not significantly enhance accuracy or reduce uncertainty.
• Stomatal optimization based on water use efficiency (WUE) outperformed xylem vulnerability models.

Conclusions:

• WUE-based stomatal optimization provides more informative and less complex ecosystem-scale evapotranspiration estimates.
• Simpler models with explicit WUE principles are more effective for ecosystem applications than complex plant hydraulic models.