Aboveground biomass equations for sustainable production of fuelwood in a native dry tropical afro-montane forest of Ethiopia

Abstract

Key message: Biomass equations are presented for five tree species growing in a natural forest in Ethiopia. Fitted models showed more accurate estimations than published generalized models for this dry tropical forest. Context: Biomass equations are needed to correctly quantify harvestable stock and biomass for sustainability efforts in forest management, but this kind of information is scarce in Ethiopia. Aims: This study sought to develop biomass models for five of the most common native tree species in the Chilimo dry afro-montane mixed forest in the central highlands of Ethiopia: Allophyllus abyssinicus, Olea europaea ssp. cuspidata, Olinia rochetiana, Rhus glutinosa, and Scolopia theifolia. Comparison with generalized models was intended to show the greater accuracy of the specific models. Methods: A total of 90 trees from different diameter classes were selected, felled, and divided into different biomass compartments. Biomass equation models were fitted using joint-generalized least squares regression to ensure the additivity property between the biomass compartments and total biomass. Results: These were the first models developed for these species in African tropical forests. Models were including diameter at breast height and total height as independent variables, obtaining more accurate biomass estimations using these models than from generalized models. Conclusion: Fitted models are reliable for estimating aboveground biomass in the Chilimo forest and for more general application in similar forest types. Model applicability for biomass or carbon estimation is high within forest inventory data contexts.