Accurate estimating aboveground biomass (AGB) is essential for quantifying carbon stocks and assessing the climate-mitigation potential of agroforestry systems. However, many existing biomass models in Uganda and other eastern African countries were developed for natural forests, rely on limited sample sizes, or employ generalized equations that may not adequately represent trees grown under smallholder agroforestry setting This study developed species-specific allometric equations to estimate AGB for seven agroforestry tree species in northern Uganda: Acacia polyacantha, Albizia lebbeck, Gmelina arborea, Maesopsis eminii, Markhamia lutea, Melia volkensii, and Senna siamea. Destructive sampling was conducted on 36–44 trees per species across a range of diameter classes and management regimes in Gulu, Amuru, Nwoya, and Oyam districts. Diameter at breast height (D), tree height (H), and crown radius (CR) were fitted as predictors of AGB using nonlinear maximum-likelihood regression models. Model performance was assessed using coefficient of determination (R2), root mean square error (SE), prediction error (PE%), Akaike Information Criterion (AIC), and repeated k-fold cross-validation. The selected models explained most of the variation in AGB (R2 = 0.90–0.99) and PE% below 3.5%. Model structure varied among species: for M. eminii and S. siamea, D alone adequately explained AGB variation, whereas other species required combinations of D with H or CR. Comparison with previously developed models revealed that generalised or pantropical equations produced biased estimates. Therefore, the developed species-specific equations provide reliable tools for estimating AGB and carbon stocks in smallholder agroforestry systems and woodlots in northern Uganda, supporting carbon accounting and restoration monitoring.
Tag: allometric equation
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.
New species-specific allometric models for above- and below-ground biomass and carbon content of young mangroves
Mangroves restoration plays a vital role in climate change mitigation, with carbon sequestration capability as a key indicator. However, most existing allometric models used for biomass estimation are developed from mature trees and are unsuitable for young mangroves due to limitations in the availability of predictor variables. These models rely on diameter at breast height (DBH) to predict biomass, making them inapplicable for young mangroves in the early restoration phase, which do not yet have a measurable DBH. This study develops species-specific allometric equations for estimating aboveground (AGB) and belowground biomass (BGB) of young mangroves across four species: Bruguiera gymnorrhiza, Kandelia candel, Rhizophora apiculata, and Rhizophora mucronata. Samples were collected using destructive methods along with structural measurement to develop species-specific allometric models using simple power equation and compared with existing models. Biomass distribution was highest in the stem, followed by branches and stilt-roots, then lowest in roots. Carbon content was relatively uniform among different tree components, except for lower values in roots. AGB proportion generally exceeded BGB, except in R. apiculata, with root-to-shoot ratios ranging from 0.43 to 1.31. The best AGB and BGB models showed high goodness of fit (Adj R² = 0.94–0.95 and 0.83–0.97, respectively). Validation showed species-specific performance varied among AGB models (RMSE = 0.07–0.20; MAPE = 0.15–0.25) and among BGB models (RMSE = 0.04–0.43; MAPE = 0.13–0.40). Compared to existing allometric models for mangrove saplings, these new models enhance biomass estimation accuracy for young mangroves that are essential in restoration monitoring and complement existing equations suited for mature trees. Notably, this study provides the first allometric model for K. candel in Indonesia and includes BGB estimates, which are still limited in mangroves research.