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Several nonlinear, individual tree crown-height increment equations were tested for their ability to predict annual crown-height increment in thinned and unthinned loblolly pine plantations. The selected model contained tree height (HT), tree crown ratio (CR) raised to the one-half power, age (A), and a measure of competition. The distance-dependent and the distance-independent models were the same form; however, the competition index (CI) in the distance-dependent model was replaced by the ratio of quadratic mean diameter to tree dbh (DR) for the distance-independent model. The individual-tree increment models were used as a basis for a stand-level crown-height increment model. The independent variables were collapsed to stand-level statistics; the model contained average height of dominant and codominant trees (HD), average crown ratio (R), and age (A). Unlike the individual-tree models, raising the average crown ratio to 0.5 did not improve the fit. Hypothesis tests revealed that thinning, both its intensity and the elapsed time since its occurrence, had a significant effect on crown-height increment. A thinning variable, T, which accounted for thinning intensity and the interval since thinning, was developed and incorporated into the final individual-tree and stand-level increment models. Predictions of crown-height increment were improved using models with the T variable as compared to those with no thinning allowance. For. Sci. 38(3):594-610.
Thomas M. Brooks Professor of Forest Biometrics, Department of Forestry, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061-0324
Publication date: August 1, 1992
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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.