Abstract

Million tons of carbon was found to be stored in the forest biomass with maximum storage capacity in the broadleaved trees. Developing tree biomass allometric equation being considered fundamental to determine the carbon sequestration potential of tree species. Thus, five broadleaved tree species of Quercus lamellosa, Beilschemidia sikkimensis, Castonopsis hystrix, Persea clerkania and Symplocos sumintia were destructively sampled using Randomized Branch Sampling technique (RBS) to develop allometry for aboveground biomass estimation in cool broadleaved forests in Bhutan. The total of 159 sample trees with minimum 32 trees from each species under different diameter class (5 cm < 90 cm), height class (4 m < 46 m) from four physiographic zones were sampled. The observed total aboveground dry biomass of the trees ranges from 4.12 < 5579.31 kg; 3.62 < 3464.51 kg; 5.99 < 3600.52; 8.89 < 3689.82 kg; kg and 7.08 < 2993.22 kg respectively for above five species. Linear regression was attributed to heteroskedasticity with un-equal distribution of the residual errors. While linearized regression with transformed variables exhibited the best fit line for biomass estimation. Significant prediction of aboveground tree biomass was observed with natural log base transformed linearized power function of DBH -tree height relationships (t (29) = 11.91, 1.63, p ≤ .001) R² = .98) followed by the transformed model of DBH as independent variable (t (30) = 34.31, p ≤ .001) R² = .97). Therefore, the study concluded that, linearized power function with antilog bias correction factor seemed better in predicting aboveground tree biomass of cool broadleaved species in Bhutan

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