Forcing additivity of biomass tables: some empirical results

Abstract

Three methods for insuring the additivity of biomass tables are described and their application to a sample of trees illustrated. The advantages and drawbacks of each method are identified and the results obtained compared with each other. All three methods yield biomass tables that are not significantly different from each other (at least for the sample data used), but their estimated precision and conditions of applicability are different. At least one of the methods can be applied to the cases where the weights to use in the least squares regression procedure may differ from one to the next tree component, when sample data of some component are missing from some sample trees and when nonlinear seem better than linear regression functions.