Effects of Sample Plot Size and Prediction Models on Diameter Distribution Recovery

Distribution of tree diameters in a stand is characterized using models that predict diameter moments and/or percentiles in conjunction with a mathematical system to recover the parameters of an assumed statistical distribution. Studies have compared Weibull diameter distribution recovery systems but arrived at different conclusions regarding the best approach for recovering a stand's diameter distribution from predicted stand-level statistics. We assessed the effects of sample plot size and diameter moments/percentiles prediction models on the accuracy of three approaches used in recovering Weibull distribution parameters-method of moments, percentile method, and moments-percentile hybrid method. Data from five plot sizes, four of which were virtually created from existing larger plots, from unthinned loblolly pine (Pinus taeda) plantations, were used to fit moments/percentile prediction models and to evaluate the accuracy of the diameter distribution recovered using three approaches. Both plot size and prediction model form affected the accuracy of the recovery approaches as indicated by the changes in their ranking from one plot size to another for the same model form. The method of moments approach ranked best when the evaluation error index did not account for tree stumpage value, but the moments-percentile hybrid approach ranked best when stumpage value was considered. Study Implications: Diameter distribution recovery techniques make it possible to disaggregate trees per unit area, predicted by the whole stand growth and yield models, into diameter and utilization product classes. Thus, the techniques provide insights into stand structure, which can guide management decisions such as thinning and selection harvesting. The techniques are also used to generate yield tables by product class, which are important inputs into harvest scheduling optimization programs. An accurate diameter recovery technique is therefore critical to forest management and planning. Based on the findings of this study, the best approach of developing a diameter distribution recovery system for unthinned loblolly pine plantations would be to use the hybrid approach, with tree diameter data collected from plots of at least one-tenth hectare. The well-known (and, most likely, widely used) method of moments approach may not be the best choice. For predicting stand diameter moments and order statistics used in a diameter distribution recovery system, it would be best to use a linear additive model that incorporates a measure of stand density, such as relative spacing and/or number of trees per unit area, and a measure of the stand's stage of development, such as dominant height and/or age.