Plantation forests are crucial for landscape rehabilitation and carbon sequestration. However, the efficacy of these plantations in carbon sequestration in Ethiopia remains uncertain due to a lack of robust, species- and site-specific biomass estimation models. This study addresses this gap by developing and validating allometric models for estimating aboveground biomass (AGB) and carbon (C) stocks of plantation forests. Allometric models were developed using data from 69 harvested trees of three species: Eucalyptus globulus, Cupressus lusitanica, and Pinus patula. AGB was regressed against diameter at breast height (DBH) as the sole predictor, with stepwise inclusion of height (H), crown area and wood density. Model performance was evaluated using fit statistics, including Pseudo-R2 and mean prediction error (MPE). The model that incorporated both DBH and H as predictors provided the best fit (Pseudo-R2 > 0.90, p < 0.001) and achieved the lowest MPE (1.47–5.67%) across all species. The findings indicated a mean C stock of 121.6 Mg C ha−1 in the plantations studied. Our models provide valuable insights for forest management and improve the accuracy of AGB and C stock estimations in the study area and similar ecosystems. The estimated C stocks can serve as a benchmark for assessing future C dynamics.
Reta et al. (Sat,) studied this question.