Stand biomass estimation methods for Eucalyptus grandis and Eucalyptus dunnii in Uruguay

Abstract

Biomass additivity is a desirable characteristic of a system of equations for predicting components and total biomass, since equations independently adjusted generate biologically inconsistent results. The aim of this study was to fit and compare three methods for modelling biomass: (i) total biomass individual regression, (ii) total biomass regression function calculated as the sum of separate biomass components, and (iii) simultaneous equations of biomass components based on Nonlinear Seemingly Unrelated Regression. A total of 208 trees of Eucalyptus dunnii and Eucalyptus grandis were harvested and destructively sampled to record above-ground biomass. Results indicate that a system of equations adjusted by simultaneous equations provides accurate biomass estimations, guaranteeing additivity. This model system showed good fit and good prediction performance, given that the correlation coefficient was higher than 97 % for total above-ground biomass, for both species; whereas root mean square error was 23.9 kg and 30.2 kg for E. grandis and E. dunnii, respectively. A system of biomass equations was developed for each eucalyptus species, such that the sum of the estimations of the biomass components equaled the estimate of above-ground biomass. Results showed that the systems of equations have high potential for improving the accuracy of individual tree above-ground biomass estimates for both species.

Carbon Sequestration in Carob (Ceratonia siliqua L.) Plantations under the EU Afforestation Program in Southern Spain Using Low-Density Aerial Laser Scanning (ALS) Data

“…Individual models selected for each biomass component were fitted simultaneously using the additive system of equations based on nonlinear seemingly unrelated regression (NSUR) to ensure compatibility between the total biomass and the sum of the fractions [37]. This statistical approach has been frequently used in biomass studies [38]. The Proc SQL program of SAS [49] was used to perform the routine.…”

“…The total biomass (Wt) was represented by the sum of the Wa and the below-ground dry weight biomass (Wb). Individual models selected for each biomass component were fitted simultaneously using the additive system of equations based on nonlinear seemingly unrelated regression (NSUR) [37,38]. The powder samples of the tree components were analysed for the C concentrations using a NIR macro elemental analyser (Eurovector EA 3000) according to the Dumas combustion method.…”

Biomass Estimation and Carbon Storage of Taxodium Hybrid Zhongshanshan Plantations in the Yangtze River Basin

“…A good database for developing regression equations should contain an age sequence because trees of different diameters distinguish from each other in the component proportion of the aboveground biomass. When there were several tree components in the biomass data, the additivity of models for accessing tree total, sub-total, and separate biomass fractions should be considered, owing to the inherent correlations among the biomass components measured on the same sample trees [4]. Traditional models often ignored such inherent relationships.…”

Sistemas agroforestales a partir de técnicas de forestación en zonas agrícolas degradadas bajo el contexto de cambio climático

“…Individual models selected for each biomass component were fitted simultaneously using the additive system of equations based on Nonlinear Seemingly Unrelated Regression (NSUR) to ensure compatibility between the total biomass and the sum of the fractions (Parresol 2001;Hyrigoren et al, 2021). The Proc sql program of SAS (SAS Institute 2004) was used to perform the routine.…”

“…The total biomass (Wt) was represented by the sum of Wa and the belowground dry weight biomass (Wb). Individual models selected for each biomass component were fitted and then, simultaneously using the additive system of equations based Nonlinear Seemingly Unrelated Regression (NSUR) (Parresol 2001;Hyrigoren et al, 2021).…”