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An Adjustable Predictor of Crown Profile for Stand-Grown Douglas-Fir Trees

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This study developed a method for predicting the crown profile of stand-grown trees that can be adjusted to other populations of the same species by using either measurements or predictions of the largest crown width (LCW) for trees in the alternative population. The method should be of particular interest for tree species such as Douglas-fir that have exhibited variation in crown attributes across both their geographic range and genotypes. To model crown profile, the crown was divided into two segments: the portion of the crown above the point where LCW occurs, and the portion below that point. The equation for the upper portion predicted a crown profile that ranged in shape from nearly conic to parabolic, depending on position within the crown and the social status of the tree, as indicated by the ratio of total height divided by diameter at breast height for the tree. The equation for the lower portion predicted a crown profile with a cylindrical shape. This method explained nearly 94% of the variation in crown width when used with the felled tree measurement of LCW, 87% with a measurement of LCW taken while the tree was standing, and 83% with the use of a value for LCW that was predicted from an equation developed from an independent data set. For. Sci. 45(2):217-225.
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Keywords: Crown width; crown architecture; crown area; crown modeling; crown shape

Document Type: Journal Article

Affiliations: Professor, Department of Forest Resources, Oregon State University, Corvallis, OR 97331--Phone: (541) 737-4673, Fax: (541) 737-3049

Publication date: 1999-05-01

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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.
    Forest Science is published bimonthly in February, April, June, August, October, and December.

    2016 Impact Factor: 1.782 (Rank 17/64 in forestry)

    Average time from submission to first decision: 62.5 days*
    June 1, 2016 to Feb. 28, 2017

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