Allometric models for accurate estimation of aboveground biomass of teak in tropical dry forests of India

Abstract

For accurate estimation of teak biomass, it is necessary to develop allometric models for different stem diameter classes (D classes). In this study, we harvested teak trees in the tropical dry forest region of India in 10 D classes, measured biomass of foliage, branch, bole, and the total aboveground part, and developed regression models for the nondestructive estimation of foliage, branch, bole, and aboveground biomass with the help of wood density (ρ), stem diameter (D), and plant height (H). Models used for the prediction of biomass of tree components were of the linear, logistic, Gompertz, and Chapman forms. These models explained more than 90% variability in the biomass of each component of teak. For foliage biomass only, the model with just D as the estimator exhibited greater R2 and lower standard error of estimate and average deviation. For branch, bole, and aboveground biomass, the models including ρ, D, and H had greater R2 and lower standard error of estimate. Our study detected that logistic models are more appropriate for broad diameter ranges and linear models for small D classes. The regression models developed in our study can be applied separately for the 10 D classes, and this could minimize the error occurring during nondestructive estimation of biomass of teak in different D classes.