A theoretical and empirical assessment of stomatal optimization modeling

Area of Science:

• Plant Physiology
• Ecology
• Biophysics

Background:

• Stomatal control models are crucial for predicting plant responses and improving carbon cycle models.
• Current models vary in how they calculate the 'penalty' for stomatal opening, a key divergence point.
• Optimality theory suggests stomata balance carbon gain against a penalty for water loss.

Purpose of the Study:

• To compare and evaluate 10 different stomatal optimization models.
• To assess how penalty functions influence model predictions of stomatal responses to environmental factors.
• To identify key criteria for effective stomatal control modeling.

Main Methods:

• Compared penalty functions of 10 models against seven criteria for realistic solutions.
• Quantitatively tested model performance using multiple leaf gas-exchange datasets.
• Evaluated model predictive skill based on penalty function characteristics and parameterization.

Main Results:

• Models with penalty functions meeting the seven criteria showed better predictive skills.
• Fewer, physiologically-based fitting parameters correlated with improved model performance.
• Stomatal models incorporating stress-induced hydraulic failure as a penalty function were most effective.

Conclusions:

• Penalty function formulation is critical for accurate stomatal modeling.
• Hydraulics-based penalty functions offer superior predictive capabilities.
• A new, proposed model with a validated hydraulics-based penalty function demonstrates high predictive skill.