Modelling functional trait acclimation for trees of different height in a forest light gradient: emergent patterns...

Area of Science:

• Plant Physiology
• Forest Ecology
• Ecosystem Modeling

Background:

• Forest trees undergo significant functional trait changes during development from saplings to canopy adults.
• The adaptive significance of these trait changes, particularly concerning carbon gain, is not fully understood.

Purpose of the Study:

• To explore the carbon gain hypothesis using a mechanistic model.
• To investigate how functional traits acclimate to maximize net growth in forest trees of varying heights and light availability.

Main Methods:

• Developed a mechanistic model integrating plant structure, photosynthesis, and stomatal conductance.
• Simulated trait responses to tree height and light intensity under the assumption of carbon gain maximization.

Main Results:

• Simulations predicted increases in leaf area, sapwood area, and leaf photosynthetic capacity with tree height and light.
• Crown stomatal conductance and transpiration also increased, impacting the carbon budget.
• Identified shared patterns between forest and exposed trees, including decreasing leaf water potential and intercellular CO2 with height, and stable capacity balances.

Conclusions:

• Mechanistic modeling of carbon gain maximization predicts functional trait acclimation and capacity balance maintenance in forest trees.
• Model predictions align qualitatively with some empirical observations, but direct testing of capacity balances is scarce.
• Further empirical research is needed to validate the predicted patterns of trait acclimation and functional balances in trees across forest light gradients.