Mapping of Prosopis juliflora rate of expansion and developing species-specific allometric equations to estimate its aboveground biomass in the dry land of Ethiopia

Prosopis juliflora, one of the most invasive species in arid and semi-arid environments, can sequester considerable amounts of carbon and provide fuel wood for domestic consumption. However, the lack of species-specific allometric models limits efforts to estimate forest biomass and its potential to store carbon. We conducted this study to determine the rate of expansion of this Prosopis in arid environments and develop robust allometric models to precisely predict tree-level biomass and its carbon storage potential. The satellite image analysis showed that Prosopis continues to expand rapidly along riverbanks and accounted for 69% of the available vegetation cover in the study area. The spatial coverage of Prosopis increased by 40% within 5 years from 2016 to 2021 and has been expanding at a rate of 8% per year. The rate of Prosopis expansion calls for the application of new utilization systems like massive charcoal production which may be a great blessing to the region. For such purpose, quantification of the biomass of Prosopis from easily measured variables is essential. Hence, after destructive sampling of 45 individual trees, the relationships between three variables (diameter at stump height, DSH; height, H; and wood density, rho) and their total biomass of the aboveground parts were used to fit regression models in R software. These models were developed using DSH alone, DSH and height or in a combination of DSH, H and rho. Although DSH alone explained most of the variations (91%), adding H and rho as additional independent variables resulted in a much better prediction of biomass estimation with the lowest values of bias. Therefore, the best-selected model for the above-ground biomass (AGB) estimation of the species Prosopis is M9 (AGB = exp(-3.053 + 0.919 x ln(DSH2 x H x rho)) which presented the highest adj. R-2 value (0.985) and the lowest values of Akaike information criteria. Given narrow diameter ranges, the model can be applied beyond their valid data ranges and to other similar growth forms across the arid regions of Ethiopia.