Species specific and multi-species allometric models for estimating aboveground biomass of native perennial plant species grown in the agricultural landscape of Central Ethiopia

Agroforestry plays a significant role in climate change mitigation and thus buffers the pressure on forest resources. However, owing to the lack of accurate biomass models, the contribution of these systems towards carbon storage remains poorly understood, which makes it difficult to implement climate change mitigation initiatives. Besides, most of the biomass predictions for trees grown in agricultural lands rely on the models developed for natural forests. This study therefore aimed to develop species-specific and multi-species allometric equations for predicting the aboveground biomass (AGB) of native perennial plant species in the agricultural landscape of central Ethiopia. Ninety-five individuals representing six perennial plant species with diameter at breast height ranging from 3.5 to 65 cm were destructively harvested. Diameter at breast height (DBH), total height (ht), wood bulk density (wbd), and crown diameter (cd) were used as predictors of the AGB. The study found that DBH was the best single predictor of AGB for Oldeania alpina and Faidherbia albida, with options for other species. Multiple variable models combining DBH-ht exhibited the highest predictive capacity for AGB in Erythrina brucei, Albizia schimperiana, and Croton macrostachyus, whereas the combination of DBH–cd and DBH–ht–wbd–cd best predicted the AGB of Acacia abyssinica and mixed species, respectively. Species-specific and mixed-species models showed the best predictive capacity for AGB compared to other frequently used regional and pan-tropical models. The findings of the study suggest that mixed-species AGB models will be used when species-specific allometric models are not available at a given site.