The Use of Composite Estimators for Estimating Forest Biomass and Growth from Permanent Sample Plots Established by the Angle Count Method
John Paul McTague
Rayonier, Inc. and University of Georgia
The private corporate forest landowners of the United States have long abandoned the practice on relying upon permanent sample plots (PSPs) to measure the components of forest growth. Many of the PSPs were inexpensively established using the Bitterlich angle count method, however they furnished estimates of growth with high variance or with non-additive properties of biomass/volume (V2 ? [V1 + ?V]). McTague (2010) proposed a new unbiased variable basal area factor that is weakly correlated, in some forest conditions, to the conventional Bitterlich estimator. Gains in precision are possible by using composite estimates that weighted inversely by variance between the new and conventional estimators. This paper will demonstrate that the Bitterlich estimator is a special case of a composite estimate between the new variable basal area factor and its antithetic counterpart. When the new estimator is extended to the application of estimating change in forest stock or standing inventory from remeasured forest plots, it is possible to obtain unbiased, efficient, additive, and inexpensive estimates of growth.