Calibrating predicted diameter distribution with additional information

The diameter distribution of the growing stock is an essential starting poi nt in many forest management planning problems. There are several methods f or predicting the diameter distribution of a stand, varying from methods wh ich utilize theoretical distribution functions to nonparametric methods. Us ually the predicted diameter distribution is scaled so that the stem number corresponds to the measured value. However, if stem number and basal area are both known, it may be difficult to predict a distribution that gives co rrect estimates for both these characteristics. Such diameter distributions can be obtained using an approach adopted from sampling theory-calibration estimation. In this study, the diameter distributions of Scots pine were p redicted with two different methods, the Weibull and percentile based metho ds, and then calibrated with additional information. The calibration reduce d the RMSE of stand variables computed from the predicted distribution.