Allometric models for predicting above ground biomass and organic carbon stock of four Acacia species in the Sudanian zone of West Africa

Carbon sequestration in plant is of great attention due to its concerns about global climate change. In the present investigation we developed species-specific allometric models to predict above ground biomass of Acacia gourmaensis and Acacia dudgeoni. To determine the most appropriate predictor variables in order to produce a general allometric relationship, a stepwise multiple regression technique was used. A total of one hundred and thirty (130) trees (30 for Acacia gourmaensis; 35 for Acacia dudgeoni; 33 for Acacia tortilis and 32 for Acacia nilotica) were clear-felled and immediately separated into components: stem branches and leaves. The green weight of each component sample was measured and was thereafter dried in the oven until constant weight was attained. Allometric equations were developed for each species to estimate stem, branch, leaf and total above ground biomass. The best-fit models found for estimating tree component biomass and total above ground biomass production were of the linear form. All the components models have low Residual Standard Error (RSE), meaning the models performed well. The aboveground biomass rate of carbon sequestered was estimated using ash method. The mean percentage of carbon content in the above ground biomass were 53,43%; for A. gourmaensis; 53,39% for A. dudgeoni; 54,75% for A. nilotica and 55,38% for A. tortilis. The current established allometric equations may allow a rapid estimate of Acacia species above ground biomass and carbon stock in Sudanian zone and aid in a sustainable management of these species.