Species-specific allometric models for reducing uncertainty in estimating above ground biomass at Moist Evergreen Afromontane Forest of Ethiopia.

An allometric equation is used to convert easily measured tree variables into biomass. However, limited species-specific biomass equations are available for native tree species grown in various biomes of Ethiopia. The available pantropic generic equation has resulted in biases owing to the uncertainty of the generic model estimation due to the difference in tree nature and response to growth conditions. The objective of the study is, thus, to develop a species-specific allometric equation for reducing uncertainty in biomass estimation at the Moist Evergreen Afromontane Forest in south-central Ethiopia. Five tree species were selected for model development, these selected trees were harvested and weighed in the field. The measured above-ground biomass data related to easily measured tree variables: diameter at stump height, diameter at breast height (dbh), crown diameter, and total tree height. The developed model evaluated and compared with previously published model by using measures of goodness of fit such as coefficient of determination (R), total relative error, mean prediction error, root mean square error, and Akaike information criteria. The analysis showed that a model with dbh as a single predictor variable was selected as the best model for the estimation of above-ground biomass. It gives the highest R for Syzygium guineense (0.992) and the lowest for Bersama abyssinica (0.879). The additions of other tree variables did not improve the model The pantropic model by Brown overestimates the biomass by 9.6-77.8% while both Chave models resulted in an estimation error of 12-50.3%. Our findings indicated that species-specific allometric equations outperformed both site-specific and pantropic models in estimating above-ground biomass by giving 0.1% up to 7.9% estimation error for the respective tree species.