Whole-plant optimality predicts changes in leaf nitrogen under variable CO₂ and nutrient availability.

Area of Science:

• Ecology
• Plant Physiology
• Ecosystem Science

Background:

• Vegetation nutrient limitation is crucial for understanding ecosystem responses to global change.
• Leaf nitrogen (N) content is plastic under altered nutrient availability, but current models struggle to capture these dynamics, leading to inaccurate ecosystem predictions.

Purpose of the Study:

• To develop and test an optimality approach for improved representation of leaf N content in vegetation models.
• To address limitations in existing empirical and optimality-based models that fail to capture observed changes in leaf N.

Main Methods:

• Proposed an optimality model maximizing whole-plant growth, incorporating a lagged response of foliar N to account for trait plasticity.
• Tested model variants against empirical data from Free-Air CO2 Enrichment (FACE) and N fertilization experiments.
• Compared the new optimality model with a previous approach based on canopy carbon export.

Main Results:

• The canopy carbon export model inaccurately predicted decreasing leaf N with increasing N availability.
• The proposed optimality model, maximizing plant growth, successfully reproduced observed patterns of leaf N content.
• The new model demonstrates biologically realistic changes in leaf N under varying nutrient conditions.

Conclusions:

• An optimality approach maximizing whole-plant growth offers a more accurate representation of leaf N dynamics than existing methods.
• This improved model can enhance the accuracy of ecosystem-level predictions, especially under transient environmental conditions.
• The study highlights the importance of considering whole-plant growth and lagged responses for modeling plant traits.