Abstract
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.
Highlights
Forest biometricians have been using empirical models to estimate total tree biomass and its components, such as leaves, branches, fruits, bark, stems, and roots
The database is derived from black wattle (Acacia mearnsii) stands, at age 10 years, established in three different locations in the Rio Grande do Sul State (Cristal; Encruzilhada do Sul and Piratini), southern Brazil
Several authors addressed the inclusion of basic wood density in allometric models, such as Chave et al (2014), Tashi et al (2017), and Coutinho et al (2018)
Summary
Forest biometricians have been using empirical models to estimate total tree biomass and its components, such as leaves, branches, fruits, bark, stems, and roots. Allometric models take place from easy-to-measure variables such as diameter at 1.30 m above the ground (d) and total tree height (h). Direct biomass determination, more accurate, is a highly costly process. Statistical modeling has been used in forest inventories to reduce the field’s operational effort, reducing costs. Biomass modeling is usually done independently, with the models being fitted without considering the interdependence between tree components. Notwithstanding, the sum of the components’ biomasses does not produce the same result as obtained using the total biomass equation, not being biologically consistent
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
