HOW TO ESTIMATE BLACK WATTLE ABOVEGROUND BIOMASS FROM HETEROSCEDASTIC DATA?

• Published in: Floresta Vol. 51; no. 1; p. 28
• Main Authors: Gonçalves de Oliveira, Thiago Wendling, Coutinho, Vinícius Morais, Fiorentin, Luan Demarco, Inoue Sanquetta, Mateus Niroh, Sanquetta, Carlos Roberto, Dalla Corte, Ana Paula
• Format: Journal Article
• Language: English
• Published: 2021
• ISSN: 0015-3826; 1982-4688
• DOI: 10.5380/rf.v51i1.65236

This study developed a system of equations for predicting total aboveground and component biomass in black wattle trees. A total of 140 black wattle trees at age 10 years were measured regarding their diameter at 1.30 m height above the ground (d), total tree height (h), basic wood density (branches and stem), and biomass (stem, crown, and aboveground). We evaluated the performance of linear and nonlinear allometric models by comparing the statistics of R2adj., RRMSE%, and BIC. Nonlinear models performed better when predicting crown biomass (using only d as an independent variable), and stem and aboveground biomass (using d and h as independent variables). Adding basic density did not significantly improve biomass modeling. The residuals had non-homogeneous variance; thus, the fitted equations were weighted, with weights derived from a function containing the same independent variables of the fitted biomass function. Subsequently, we used a simultaneous set of equations to ensure that the sum of each component's estimated biomass values was equal to the total biomass values. Simultaneous fitting improved the performance of the equations by guaranteeing the components' additivity, and weighted regression allowed to stabilize error variance, ensuring the homoscedasticity of the residuals.