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Updated: Aug 16, 2025

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
Published on: July 3, 2020
Modelling the stand dynamics after a thinning induced partial mortality: A compensatory growth perspective
Chao Li1, Hugh Barclay2, Shongming Huang3
1Canadian Wood Fibre Centre, Canadian Forest Service, Edmonton, AB, Canada.
Forest managers can now better predict stand dynamics using the TreeCG model, which simulates tree compensatory growth after partial mortality. This model aids in optimizing forest management strategies for improved yield.
Area of Science:
- Forestry Science
- Ecology
- Computational Modeling
Background:
- Managed forest stands are increasingly common, necessitating better prediction of their dynamics under disturbances.
- Understanding tree and stand responses to partial mortality is crucial for effective forest management.
- Partial mortality is a common event in stand development, influencing overall dynamics.
Purpose of the Study:
- To develop a model simulating compensatory growth in trees following partial mortality.
- To investigate tree and stand response patterns to resource redistribution after tree death.
- To provide a tool for predicting managed stand dynamics.
Main Methods:
- Developed the TreeCG (Tree's Compensatory Growth) model, an individual tree-based forest growth simulator.
- Modeled compensatory growth via resource redistribution from dead to surviving trees.
- Simplified annual growth increment simulations over long stand development periods.
Main Results:
- The TreeCG model accurately reproduced forest growth patterns from long-term thinning experiments.
- Simulated growth demonstrated compensatory growth dynamics: under-compensation, compensation-induced-equality, and over-compensation.
- Model validated against observed forest growth trajectories.
Conclusions:
- The TreeCG model can simulate stand growth under various partial harvest scenarios, aiding strategy selection.
- The model's generic nature allows refinement for specific species and sites, enhancing predictive power.
- Simulations align with natural stand growth trajectories when no intervention occurs.
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