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A Carbon Balance Model of Growth and Self-Pruning in Trees Based on Structural Relationships

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A tree growth model is formulated based on structural relationships in a carbon balance framework. Three relationships are applied: (1) an allometric relationship between crown surface area and foliage area, (2) the principle of functional balance, and (3) the pipe-model theory. These assumptions lead to a model where the sizes of the functional parts of the tree are derivable from foliage weight, except for the pruning height of the crown. This is determined by defining a "self-pruning coefficient," which controls the allocation of growth between height growth and foliage growth. The tree model is applied to an average-tree based stand growth model where both the self-pruning coefficient and tree mortality are made functions of crown coverage. The model is quantified for Scots pine growing in southern Fenno-Scandia. The overall behavior of the model is realistic. The model responds to stocking density through the rate of self-pruning, lower stocking densities leading to larger crown ratios. It also responds to changes in parameters describing site quality in a realistic way, although the differences in stand density are not as large as expected. The predicted development of the biomass compartments in individual trees agrees well with data on dominant Scots pine trees in Finland. For. Sci. 43(1):7-24.
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Keywords: Pinus sylvestris; carbon allocation; process-based model; wood quality

Document Type: Journal Article

Affiliations: Department of Forest Ecology, P.O. Box 24 (Unioninkatu 40), FI-00014 Helsinki University

Publication date: 1997-02-01

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    Forest Science is a peer-reviewed journal publishing fundamental and applied research that explores all aspects of natural and social sciences as they apply to the function and management of the forested ecosystems of the world. Topics include silviculture, forest management, biometrics, economics, entomology & pathology, fire & fuels management, forest ecology, genetics & tree improvement, geospatial technologies, harvesting & utilization, landscape ecology, operations research, forest policy, physiology, recreation, social sciences, soils & hydrology, and wildlife management.
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