Allometric models for estimating fuelwood and above-ground wood dry mass of pruned Faidherbia albida trees in northern Cameroon

In Cameroon’s Sudano-Sahelian zone, rising fuelwood demand is jeopardising Faidherbia albida agroforestry parklands. Faced with these alarming pressures and ongoing climate challenges, evaluating sustainable management practices and the contribution of F. albida agroforestry parklands to climate change mitigation has become a pressing priority. In these agro-ecosystems, total and rotational crown pruning are common practices, traditionally aimed at fuelwood and livestock feed collection. However, its impact on the trade-off between leaf removal and pod production remains poorly documented, particularly regarding long-term fuelwood yield potential. This research aims to develop tools for estimating the above-ground wood dry mass of F. albida components in the context of their use as renewable fuelwood and their carbon storage potential. Allometric equations for the different tree components were developed using data from the most recent pruning event (2023) of F. albida trees that had undergone three complete crown-pruning cycles over the past two decades. The predictors used to estimate fuelwood and above-ground wood dry mass were diameter at breast height (D, in cm), crown area (Ca, in m²), and total tree height (H, in m). The best-performing equations for each tree components relied on structurally meaningful combinations of these variables: (i) D²Ca, capturing the combined influence of stem size and crown development for estimating fuelwood obtained after pruning (DWpr, R²adj = 0.84) and the total above-ground wood dry mass of F. albida (TDWb, R²adj = 0.85), corresponding to the sum of DWpr and the post-pruning wood dry mass remaining after pruning (DWUpr); and (ii) D, reflecting the effect of stem diameter for predicting DWUpr, (R²adj = 0.76). The best crown area-only models for predicting DWpr and TDWb showed strong explanatory power, with adjusted R² values of 0.82 and 0.64, respectively. The integration of structural characteristics visible from space, such as the tree crown area, provides promising prospects for large-scale bio-mass mapping using satellite images and remote sensing methods.

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