LAUSR

Tree diameter measurements are repetitive, time-consuming, and laborious but necessary to obtain the diameter distribution of the stands. Tree diameter distribution provides much of the information necessary for sustainable management and can be predicted with high accuracy, thus saving time and financial resources. Permanent sample plots that belong to a permanent sampling network located in a protected area in the South Western Carpathians in Romania were used in this study. We compared two theoretical distribution functions and predicted or recovered their parameters using parameter prediction and parameter recovery methods. Five modeling approaches based on maximum likelihood and the method of moments were used to predict the diameter distribution of unmanaged mixed uneven-aged stands. Parameter recovery methods outperformed parameter prediction methods while the left-truncated Weibull distribution outperformed the complete Weibull distribution. The accuracy obtained by the best modeling approach measured by the relative root mean squared error (%RMSE) reaches up to 12.6% when the sums of the diameters are raised to the third power and only 0.02% and 4.8% for the sums of the second powers and the sum of the diameters respectively. This research is the first of this kind in Romania and can serve as an example of alternative solutions to the yield tables in estimating the volume of mixed uneven-aged stands and can be easily implemented into forest growth models to predict the diameter distribution in the absence of tree lists.