A modeling framework for inferring tree growth and allocation from physiological, morphological and allometric...

Area of Science:

• Ecology
• Forest Science
• Plant Physiology

Background:

• Forest succession, diversity, and function depend on species-specific growth, allocation, and mortality.
• Tree physiology and allometric constraints, linked to labile carbon status, influence these processes.
• Understanding labile carbon pools and allocation is crucial for predicting tree growth and forest dynamics.

Purpose of the Study:

• To develop and present the Allometrically Constrained Growth and Carbon Allocation (ACGCA) model.
• To explicitly couple tree growth, mortality, allometries, and labile carbon dynamics.
• To provide a framework for improved prediction of tree growth, mortality, and forest dynamics.

Main Methods:

• Developed the ACGCA model integrating allometry, physiology, and carbon allocation.
• Coupled labile carbon status with growth, mortality, and allometric constraints.
• Simulated model behavior using forest gap dynamics and parameters for loblolly pine and red maple.

Main Results:

• The ACGCA model provides a semi-mechanistic basis for predicting tree death.
• The model's allocation scheme satisfies both allometric relationships and carbon dynamics.
• Simulations reproduced species-specific growth and mortality patterns consistent with shade tolerance and succession status.

Conclusions:

• The ACGCA model offers a novel framework for understanding tree physiological states.
• Explicitly coupling carbon dynamics improves predictions of tree growth and mortality.
• This approach enhances our ability to predict forest dynamics and ecological responses.