Aboveground Biomass Models for Indigenous Tree Species in the Dry Afromontane Forest, Central Ethiopia

Abstract

The application of biomass models for quantifying forests’ above-ground biomass is essential for sustainable forest management. However, lack of knowledge in modelig biomass of individual tree growth hinders the sustainable management of Dry Afromontane forests. In this study, models to estimate above-ground biomass were developed for Rhus ruspolii, Ekebergia capensis, and Nuxia congesta. To develop the models, a total of 45 trees from different diameter classes were selected, felled, and divided into different biomass compartments. For the model’s development, diameter at breast height (DBH), total height (TH), diameter at stump height (DSH), and wood density (WD) were used as independent variables. Models’ performances were evaluated using RSE, adjusted coefficient of determination, and AIC. Also, model validations were done by using rRMSE, mean absolute deviation, bias, and coefficient of variation. Models 5 (Adj-R2 = 0.92), 6 (Adj-R2 = 0.97), and 8 (Adj-R22 = 0.82) were the best fitted models for Nuxia congesta, Ekebergia capensis, and Rhus ruspolii, respectively. The average wood densities of Ekebergia capensis, Nuxia congesta, and Rhus ruspolii were 0.59, 0.50, and 0.69, respectively. The variation between observed biomass and estimated biomass using new models was statistically not significant ( $p>0.05$ ). Thus, the biomass models developed here can be important tools to accurately estimate above-ground biomass in the Menagesha Suba forest and can be integrated into decision support tools.