Prediction of aboveground biomass and carbon stock of Balanites aegyptaca, a multipurpose species in Burkina Faso

Heliyon. 2020 Aug 4;6(8):e04581. doi: 10.1016/j.heliyon.2020.e04581. eCollection 2020 Aug.

Abstract

Balanites aegyptiaca (L.) Delile is native to semi-arid regions in Africa where it is a well-known and conspicuous component of savannas. The species is highly preferred by local people because of its high socio-economic, cultural and ecological values. However, the species faces multiple environmental challenges such as desertification and human pressure. This study aimed to develop allometric models to predict aboveground biomass (AGB) of B. aegyptiaca in two climatic zones in Burkina Faso. Overall, thirty trees were sampled using destructive method in six study stands along two climatic zones. We assessed the biomass allocation to the different components of trees by computing its fraction. Furthermore, allometric models based on diameter at breast height (dbh) and basal diameter at 20 cm height (D20) were fitted separately as well as combined with crown diameter (CD) and/or tree total height (Ht). For each biomass component, non-linear allometric models were fitted. Branch biomass accounted for 64% of the AGB in the two climatic zones and increased with dbh. No significant difference in carbon content was found. However, biomass allotment (except leaves) varied across climatic zones. Although both dbh and D20 are typically used as independent variables for predicting AGB, the inclusion of the height in the equations did not significantly improve the statistical fits for B. aegyptica. However, adding CD to dbh improved significantly the equations only in the Sudano-Sahelian zone. The established allometric models can provide reliable and accurate estimation of individual tree biomass of the species in areas of similar conditions and may contribute to relevant ecological and economical biomass inventories.

Keywords: Agricultural science; Balanites aegyptiaca; Biomass allocation; Carbon content; Environmental science; Land use and landcover; Predictive equations.