Predicting Diameter Distributions in Mixed Forests in Southern Mexico

Understanding the diameter structure of a stand is crucial for making informed decisions regarding silviculture and forest management. This is achieved by collecting forest inventory data and applying them to probability density functions. The objective of this study was to identify the optimal probability density function for describing the diameter distribution in a mixed temperate forest in Oaxaca, Mexico. Circular sampling plots of 1000 m² were established, and the diameter at breast height (DBH) and total height of 16,863 trees of the 25 most important timber species were measured. Four probability density functions (Weibull 2P, Log-Normal, Log-Logistic, and Burr) were fitted by using maximum likelihood approach for different silvicultural treatments. The predictive ability of the functions was evaluated using bias, root mean square error, Kolmogorov-Smirnov statistic and graphical analyses. In terms of accuracy and parsimony, the Burr function demonstrated the best performance, followed by the Log-Normal and Log-Logistic functions. Consequently, the Burr function is recommended for modeling the diameter distribution of stands under different treatments in the study site.