Improving Biomass Estimation in Ethiopian Moist Afromontane Forest Through Volume Model

Abstract

Abstract Forest biomass is estimated using a volume model, wood basic density (wbd), and biomass expansion factor (BEF). However, in Ethiopia, there is a shortage of volume models, hence the volume estimation was carried out using a generic model. As a result, estimation may be subject to bias when applied in areas outside its original geographic range of development. Consequently, there is a need for further research and data collection to enhance the accuracy and reliability of these equations. This study aims to develop species-specific volume models, biomass expansion factors, wood basic densities, and form factors for selected tree species in the moist evergreen Afromontane Forest of Ethiopia. A total of 59 trees were harvested for volume model, BEF, and wbd development. Nonlinear regression was employed to develop the models, and the developed models were compared with previously established models using goodness-of-fit measures. For the volume model, diameter at breast height explained 89 % - 99 % of the volume variation. Comparison with previously developed models indicates that the currently developed model yields the least error. The mean BEF for the study species was 1.58, while the mean wood basic density for all tree species was 0.58 g/cm3. The study demonstrated that species-specific volume models reduce errors in the estimation of forest volume and biomass.