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<p>The lack of accurate biomass estimation for <i>Vachellia tortilis</i> in Ethiopia’s Central Rift Valley (CRV) hinders the sustainable management of bioenrgy resources, leading to unregulated exploitation. This study aimed to develop species-specific allometric equations to accurately determine the biomass of <i>V. tortilis</i> for sustainable bioenergy production in Adami Tulu Jido Kombolcha district, semi-arid area of Ethiopia. Using systematic sampling design across 31 plots, destructive sampling was performed on fifteen representative trees. The best performing model for predicting total aboveground biomass (AGB) was the non-linear power function Y = β<sub>1</sub>d<sub>sh</sub><sup>β2</sup>h<sup>β3</sup>, which utilized both diameter at stump height (d<sub>sh</sub>) and total height (h). This model achieved the highest precision (R<sup>2</sup> =0. 97, D = 0.90) and lower error (RMSE = 36.55&#xa0;kg, MPE = 0.605&#xa0;kg). Results indicated that the crown (branch + foliage) contributes significantly to total biomass, accounting for 70% of the AGB. This research provides the scientific community with a high-precision tool for ecological modeling in semi-arid area of Ethiopia. Also essential for policymakers, to regulate charcoal production and establishing sustainable harvesting quotas to ensure forest resilience.</p>

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Aboveground biomass estimation of Vachellia tortilis (Forssk. Galasso & Banfi) for sustainable bioenergy production in the Central Rift Valley, Ethiopia

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月23日

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  • Abeje Eshete,
  • Desalegn Getnet,
  • Zewdu Yilma,
  • Dereje Chimsa,
  • Elsabet Befikadu

摘要

The lack of accurate biomass estimation for Vachellia tortilis in Ethiopia’s Central Rift Valley (CRV) hinders the sustainable management of bioenrgy resources, leading to unregulated exploitation. This study aimed to develop species-specific allometric equations to accurately determine the biomass of V. tortilis for sustainable bioenergy production in Adami Tulu Jido Kombolcha district, semi-arid area of Ethiopia. Using systematic sampling design across 31 plots, destructive sampling was performed on fifteen representative trees. The best performing model for predicting total aboveground biomass (AGB) was the non-linear power function Y = β1dshβ2hβ3, which utilized both diameter at stump height (dsh) and total height (h). This model achieved the highest precision (R2 =0. 97, D = 0.90) and lower error (RMSE = 36.55 kg, MPE = 0.605 kg). Results indicated that the crown (branch + foliage) contributes significantly to total biomass, accounting for 70% of the AGB. This research provides the scientific community with a high-precision tool for ecological modeling in semi-arid area of Ethiopia. Also essential for policymakers, to regulate charcoal production and establishing sustainable harvesting quotas to ensure forest resilience.