Predicting mean aboveground forest biomass and its associated variance

An approach to simplify the prediction of average aboveground forest biomass values and their associated variability is presented in this study. The advantage of the proposed approach is based on the fact that it can be applied to any form of equation describing tree size-shape relationships and to any tree species. The proposed approach was tested against a tree-level dataset comprising of 1211 pairs of aboveground tree biomass (M) and tree diameter (D) values. The compiled trees were grouped into several D classes and average M estimates (mu(M)) with their associated variances (sigma(M)) were predicted for each class based on second-order Taylor expansion formulas. Nineteen beech (Fagus moesiaca Cz.) plots were also used to derive mu(M) and sigma(M) estimates on an area basis in order to test the applicability of the approach on forest scale. The only assumption made was that the simple allometric model M = aD(b) can accurately describe the M-D relationship. The results indicated that the mere recording of D distribution and appropriate selection of a and b values may provide very good estimates for mu(M) and sigma(M) both at global and forest level. It is therefore concluded that biomass studies related to carbon sequestration, biofuel potential, ecophysiological processes and management practices are considerably simplified. (C) 2008 Elsevier B.V. All rights reserved.