Modelling of Allometric Equations for Biomass Estimate in Deciduous Forest

Abstract

This paper aimed to test and adjust allometric models to estimate biomass in a Deciduous Forest. The data were obtained from seven 12 x 12 m plots, from which 91 trees were cut down. Only trees with diameter at breast height (DBH) greater than 5 cm were measured, and the fitting of the models was performed based on the DBH, total height (H) and total dry biomass (DAB) for each individual tree. The adjusted equations with no stratification presented adjusted determination coefficients (R 2 aj) ranging from 0.726 to 0.972 and standard errors in percentage (Syx%) from 33.5 to 119.6. The best adjusted model for nonstratified dataset was obtained by the Stepwise procedure, leading to the equation: DAB = β0 + β1.(DBH 3) + β2.H + β3.(DBH 3 .H), with 0.954 of R 2 aj and 44.0 of Syx%. For stratified dataset, only the diameter class higher than 15 cm presented acceptable results, with 0.968 of R 2 aj and 26.5 of Syx%. The current database has shown good quality measurements for fitting stochastic models to estimate the biomass of each tree.

Correlations between dendrometric and allometric variables of Eucalyptus benthamii under agroforestry systems in the subtropic of Brazil

“…However, the biomass components of leaves and branches did not show adherence to normal distribution (Table 1; Figure 2). This lack of normality is often found in biomass data, making it a problem for modeling based on linear regression (Gujarati & Porter, 2009;Balbinot et al 2019;Trautenmüller et al, 2019). The ways to overcome the lack of normality are: (i) transformation of the data, but not indicating when the additivity of the biomass component equations must be reached (Sanquetta et al 2015;Behling et al 2018), (ii) the use of non-linear regression (Huy et al 2016;Trautenmüller et al 2021) that employ other forms of adjusting the coefficients other than the Ordinary Least Squares or, (iii) applying stratification to the data, thus, each group presents normality (Behling et al 2018;Balbinot et al 2019).…”

Determination of the biomass stock in a mixed plantation of Pinus taeda L. and Pinus elliottii Engelm.

“…Measuring the biomass of all trees in a plantation is impractical given the constraints of time and resources (Watzlawick et al 2013;Trautenmüller et al 2019). In general, forest biomass is evaluated using four techniques, namely the medium tree (Trautenmüller et al 2019), stratified tree (by diameter class), area unit (Balbinot et al 2017;Trautenmüller et al 2019), and regression (Balbinot et al 2019) techniques; these techniques are further divided into direct (destructive) and indirect (non-destructive) methods. For any of the above biomass assessment techniques, a forest inventory must initially be performed.…”

“…Meanwhile, in the indirect method, biomass is estimated using regression models based on independent variables (diameter at breast height and total tree height) obtained from the forest inventory and dependent variables (dry matter weight of the total tree and its components) obtained using the direct method (Balbinot et al 2019).…”