An ecological framework linking scales across space and time based on self-thinning

Area of Science:

• Ecology
• Ecological modeling
• Dynamical systems theory

Background:

• Scaling ecological processes across spatial and temporal scales is a fundamental challenge.
• Accurate predictions require robust theoretical frameworks and supporting data.
• Existing methods often struggle to integrate local variations into larger-scale predictions.

Purpose of the Study:

• To develop a general theoretical framework for scaling ecological processes in space and time.
• To incorporate a novel dynamical formulation of self-thinning into ecological models.
• To provide a method for calculating rates of change for plant biomass, volume, and carbon at various scales.

Main Methods:

• Adoption of a dynamical systems approach.
• Development of a new dynamical formulation for self-thinning.
• Calculation of rates of change for total and average plant properties based on individual plant characteristics.
• Incorporation of regular and stochastic disturbance into the framework.

Main Results:

• Demonstrated how local-scale statistics, such as size variation among individuals, lead to nonlinear variations at larger scales.
• Showcased the ability to calculate rates of change for plant dry mass, volume, and carbon.
• Established that stochastic disturbance at patch scales can be approximated as regular disturbance at ecosystem scales.
• Validated the dynamical formulation of self-thinning as a generic scaling framework.

Conclusions:

• A dynamical formulation of self-thinning provides a versatile framework for scaling ecological processes.
• The approach effectively integrates local variations and disturbances for improved ecosystem-level predictions.
• This theoretical framework has broad applicability beyond carbon accounting in ecological sciences.