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Title: A structurally based analytic model for estimation of biomass and fuel loads of woodland trees
Author: Tausch, Robin J.;
Source: Natural Resource Modeling. 22(4): 463-488.
Publication Series: Scientific Journal (JRNL)
Description: Allometric/structural relationships in tree crowns are a consequence of the physical, physiological, and fluid conduction processes of trees, which control the distribution, efficient support, and growth of foliage in the crown. The structural consequences of these processes are used to develop an analytic model based on the concept of branch orders. A set of interrelated equations describe the relationships between structural characteristics, including the distribution of a tree's foliage and the partitioning of the structural components within the crown for the efficient support of that foliage. The foliage biomass distribution in a tree crown and the geometric relationships between the branch orders supporting that distribution are used to define a functional depth that is used to compute an associated functional crown volume. These are computed first for the foliage and then for each of the tree's branch orders. Each functional crown volume is linearly related to its respective biomass component. These consistent linear relationships are demonstrated first with data from pinyon pine and then with data from Utah juniper and Valencia orange trees. The structural changes and associated biomass distribution changes suggest that crown growth is controlled from the outside in, with the resulting structural changes an emergent property of crown adjustment to the annual addition of new foliage. The relationships derived are potentially applicable across a range of additional tree species, in other woody species and applicable over a wide range of locations and conditions.
Keywords: allometry, tree biomass, crown structure, fuel loads, crown growth patterns, tree form
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Tausch, Robin J. 2009. A structurally based analytic model for estimation of biomass and fuel loads of woodland trees. Natural Resource Modeling. 22(4): 463-488.
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