Biomass and carbon stock analysis and estimations are performed with the use of mathematical allometric models. Developing countries in Sub-Sharan Africa such as Ethiopia lack the expensive resources to develop such costly models destructively. As a result, they are left with the only option to adopt models formulated from unrelated geographic areas which usually bears error in estimation. This study estimates the biomass of indigenous trees and develop allometric model for the Egdu Forest located Oromia region, Ethiopia. Nondestructive sampling is used to collect samples where Diameter at Breast Height (DBH), local wood density (ρ), and Tree Height (H) are the estimator variable for total dry Above Ground Biomass (AGB). Trees are selected based on DBH variability on the study site and located in a delineated area of quadrat plot. A set of species-specific models to relate AGB to estimator variables are fitted to the data. The allometric equation that fit the linear models has a significant p-value (p<0.000). Model comparison and selection are based on the Akaike Information Criterion (AIC), adjusted coefficient of determination (R2) and Residual Standard Error (RSE) of the regression. Comparison of our results with those obtained using generalized pan-tropical model revealed differences in biomass estimations. The developed equations can be used for greater accuracy by researchers, forest managers and/or organization like REDD+ to calculate aboveground biomass and carbon stock of the studied species in Ethiopia.
