Modeling tree diameters using mixtures of skewed Student’s t and related distributions

Abstract

The size structure of tree populations making up a forest stand provides a scientific basis for evaluating the forest resources and scheduling future silviculture treatments. We evaluated the efficiency of the skewed Student’s t (ST) model to predict the distributions of various complex diameter at breast height (DBH) data. The ST model was compared with finite mixtures of selected functions (gamma, log-normal, and Weibull). Additionally, two scenarios were employed to determine the number of components: (1) the use of the Bayesian information criterion and (2) visual analysis of the histogram of the DBH relative frequencies. The ST model demonstrated the highest degree of flexibility for fitting the DBH distributions. It outperformed other competitors in modeling the DBH variables in terms of all implemented scenarios. It possesses a high degree of flexibility. This model should be used to fit the DBH distributions of multigeneration forest patches with diverse size structures.