Biomass Modelling of Androstachys johnsonii Prain: A Comparison of Three Methods to Enforce Additivity

Abstract EN

Three methods of enforcing additivity of tree component biomass estimates into total tree biomass estimates for Androstachys johnsonii Prain were studied and compared, namely, the conventional (CON) method (a method that consists of using the same independent variables for all tree component models, and for total tree model, and the same weights to enforce additivity), seemingly unrelated regression (SUR) with parameter restriction, and nonlinear seemingly unrelated regression (NSUR) with parameter restriction.

The CON method was found to be statistically superior to any other method of enforcing additivity, yielding excellent fit statistics and unbiased biomass estimates.

The NSUR method ranked second best but was found to be biased.

The SUR method was found to be the worst; it exhibited large bias and had a poor fit for the biomass.

Therefore, we recommend that only the CON and NSUR methods should be used for further estimates, provided that their limitations are considered, that is, exclusion of contemporaneous correlations for the CON method and consideration of the significant bias of the NSUR method.