Allometric Models for Estimating Stem Volume, Biomass and Carbon Stocks in Sal Forests of Western Himalayas

Allometric equations provide a quantitative framework that aids in forest management, carbon accounting, and ecological research. Nevertheless, few studies have developed allometric equations for this species in this part of India, which differs ecologically from the other parts of India where most allometric studies have been done. To fill this gap, we developed allometric equations to estimate the volume, biomass, and carbon In the Sal forest of the Poanta Sahib Forest Division of Himachal Pradesh. We selected the pure plantation area of Shorea robusta. Thirty trees were selected randomly in each of the diameter classes (10-20 to 80-90 cm), and in each diameter class, ten trees each In the large, medium, and small categories were measured for diameter at breast height (DBH) and tree height. Therefore, in all240samples, trees were measured. The tree volume, biomass, and carbon were estimated using linear and non-linear functions. For each dependent variable (volume, biomass, or carbon), we compared models using multiple measures of goodness-of-fit as well as Thell's-U statistics and, lastly, cross-validation to assure further adequacy. For all of the selected parameters, the power function (Y =a (D2H) x), where Y is the dependent variable, D is the diameter at breast height, and H is the tree height, was the best fitted. To estimate stem volume based on dbh with an adjusted R2 value of (0.981), based on height (R2 value 0.722), basal area (R2 value 0.981), and D2H (R2 value 0.999), homogenously for biomass, the power function was best fitted with adjusted values of (0.918) based on diameter at breast height, (0.722) height, (0.981) based on basal area, and (0.999) based on D2H. Similarly, an adjusted R2 value for biomass carbon with diameter at breast height as an independent variable was 0.981, height as an independent variable was 0.722, basal area was 0.981, and D2H was 0.999. After testing the model, the power function fit the best among all linear and non-linear functions, and the combination of both diameter and height (D2H) was the best variable with 99 percent accuracy.