Species-specific models for estimating aboveground biomass (AGB) are the accurate means of quantifying species’ carbon pools. Cola laurifolia Mast., a dominant and multi-purpose riparian species along the Mouhoun River in Burkina Faso have a regressive population. Few scientific studies exist concerning this riparian species population and carbon stock capacity. This study aims to allow this gap by formulating a species-specific allometric model for assessing with direct method for Cola laurifolia leave, branches, stem and whole AGB. Parameters used to perform models are tree diameter at breast height (DBH), basal diameter at 20 cm (D20), height (H), and mean crown diameter (CD) using data from 30 trees. Population structure shows a low regeneration potential at all of the studied river zones (i.e. upstream, intermediate and downstream zones). The carbon stock was found to be 54.14 kg C tree-1 and 9.24 Mg C. ha-1. The density of C. laurifolia was higher in downstream zone, and consequently the carbon stock was higher in these areas. The log-log linear model is the best-fitted form incorporated DBH and H as predictors. This form is best fitted for the three tree components (i.e. leaves, branches, stem) and the AGB. The AGB model is more accurate with high coefficient of determination and low RSE (R²=0.92; RSE=0.28) contrasted with leaves models. The global model has the best goodness of fit because of a low relative error (-0.213 %) compared to the use of three component models. The accuracy of our species-specific model confirms the need to develop such models for greater accuracy in AGB estimations.

The continuously increasing interest in carbon market call for adequate approaches to assess and monitor the growth and carbon of tree species. Species-specific models for estimating aboveground biomass (AGB) are the accurate means of quantifying species’ carbon pools. This study aimed at developing allometric equation for Cola laurifolia Mast., a dominant and multi-purpose riparian species along the Mouhoun River in Burkina Faso. The study first used a destructive sampling approach on thirty trees individuals of different diameter classes after collecting their dendrometric data. Explanatory parameters used to build the models were tree diameter at breast height (Dbh), basal diameter at 20 cm (D20), height (H), and mean crown diameter (MCd). Model development involved looking at different forms of models and different compartments of the tree (leaves, branches, stems and total above ground biomass). Subsequently, field inventory data were collected in protected and communal areas along three zones of the Mouhoun river (upstream, midstream and downstream) to assess and compare the carbon stock in the different areas and also characterize their population (assessment of regeneration status of the species). The results showed that the log-log linear model was the best-fitted form for the three tree compartments (i.e., leaf, branch, stem) and the total AGB, and incorporated Dbh and H as predictors. The total AGB model was more accurate with the highest goodness of fit (high R2) low residual standard error (RSE) (R²=0.92; RSE=0.28) as compared to the three component models. Nevertheless, all the allometric equations established for the prediction of leaves, stem, branches and total aboveground biomass were statically significant (p≤0.0001). The study also showed that the population structure of the species reflects a low regeneration potential along the studied river zones (i.e., upstream, intermediate and downstream zones), calling for initiatives to address the issue. The carbon stock was found to be 56.40 kg C tree-1 and 9.24 Mg C. ha-1. The density of C. laurifolia was higher in downstream zone, and consequently the carbon stock was higher in these areas. The study also compared the outputs from existing generalized allometric models to our newly developed specific-equation and found that they overestimate or underestimate the carbon stock of C. laurifolia. The results confirm the value of species-specific model which therefore calls for more effort to develop such models for all dominant species for greater accuracy in AGB estimations at scale.