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The prediction of the distribution of quantitative variables in a forest stand is of great interest to forest managers, for the evaluation of forest resources and scheduling of future silvicultural treatments. The aim of this research was to model the distribution of quantitative variables for Quercus brantii var. persica in protected, degraded and natural forests of Iran. Gamma, beta, normal, lognormal, exponential and Weibull probability distribution functions were fitted to the height, DBH and canopy distribution of trees. Variables of distribution functions were estimated using the maximum…mehr

Produktbeschreibung
The prediction of the distribution of quantitative variables in a forest stand is of great interest to forest managers, for the evaluation of forest resources and scheduling of future silvicultural treatments. The aim of this research was to model the distribution of quantitative variables for Quercus brantii var. persica in protected, degraded and natural forests of Iran. Gamma, beta, normal, lognormal, exponential and Weibull probability distribution functions were fitted to the height, DBH and canopy distribution of trees. Variables of distribution functions were estimated using the maximum likelihood estimation method. Actual probability and probability which derived from functions was compared using Kolmogorov-Smirnov and Anderson-Darling tests.
Autorenporträt
Mehrdad Mirzaei, PhD student of Forestry at the University of Guilan (Iran). Working as a reviewerand executive director in different journals. Did many researches in biometrics of forest inventories, probability distribution and application of GIS in forest inventory. The aouther of several articles published in international journal.