Additional biomass estimation alternatives: nonlinear two- and three-stage least squares and full information maximum likelihood for slash pine

Abstract

A system of nonlinear biomass component equations was developed for slash pine (Pinus elliottii Engelm. var. elliottii) trees using an econometric approach in which endogenous right-hand-side variables were included in some equations. The system was fitted to component biomass data from 306 slash pine trees sampled in the southeastern United States with weighted two-stage (2SLS) and three-stage (3SLS) least squares and full information maximum-likelihood (FIML) estimation methods. The predictive performances of the system fitted with these three estimation methods were ranked based on an array of statistics, and the ranking follows the order of FIML > 3SLS > 2SLS. The new system performed as well or better than previously published biomass equation systems developed using the aggregation and disaggregation approaches and fitted to the same data. The results demonstrated that the econometric approaches such as FIML and 3SLS have the potential to be useful for tree biomass modeling.