A Model for Basal Area Distribution in Loblolly Pine
Abstract:A method for stochastically predicting basal area distributions, called the Parameter Distribution Model, was developed. The Chapman-Richards (C-R) growth function was used as the underlying basis for the model. Two parameters of the C-R function were fixed a priori, leaving the rate parameter, k, and shape parameter, m, to be estimated from individual tree data. The Weibull distribution was fitted to the individual tree estimates of k, and empirical regression functions were developed to predict the parameters of the Weibull distribution from stand variables. A function was derived to predict m from k and observed stand variables. To apply the Parameter Distribution Model, one first predicts the number of surviving stems from a survival function. Next, one randomly selects from the appropriate Weibull distribution a k value and from it predicts an m value. The k and m values are substituted into the C-R function to predict basal area for each tree. Basal area distributions from aggregated values predicted for individual trees were compared to distributions observed in data reserved for this purpose. The two-sample K-S test was inconclusive, but the observed and predicted distributions were close, and there was good correspondence between the moments of the distributions. Forest Sci. 30:617-628.
Document Type: Journal Article
Affiliations: Associate Professor of Forestry, North Louisiana Hill Farm Experiment Station, Louisiana State University, Homer, LA 71040
Publication date: September 1, 1984
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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.
2015 Impact Factor: 1.702
Ranking: 16 of 66 in forestry
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