Dynamic Model for Caragana korshinskii Shrub Aboveground Biomass Based on Theoretical and Allometric Growth Equations

As one of the ways to achieve carbon neutralization, shrub biomass plays an important role for natural resource management decision making in arid regions. To investigate biomass dynamic variations of Caragana korshinskii, a typical shrub found in the arid desert area of Ningxia, northwest China, we combined a nonlinear simultaneous (NLS) equation system with theoretical growth (TG) and allometric growth (AG) equations. On the basis of a large biomass survey dataset and analytical data of shrub stems, four methods (NOLS, NSUR, 2SLS, and 3SLS) of the NLS equations system were combined with the TG and AG equations. A model was subsequently established to predict the AGB growth of C. korshinskii. The absolute mean residual (AMR), root mean system error (RMSE), and adjusted determination coefficient (adj-R-2) were used to evaluate the performance of the equations. Results revealed that the NSUR method of the NLS equations had better performance than other methods and the independent equations for BD and H growth and AGB. Additionally, the NSUR method exhibited extremely significant differences (p < 0.0001) when compared with the equations without heteroscedasticity on the basis of the likelihood ratio (LR) test, which used the power function (PF) as the variance function. The NSUR method of the NLS equations was an efficient method for predicting the dynamic growth of AGB by combining the TG and AG equations and could estimate the carbon storage for shrubs accurately, which was important for stand productivity and carbon sequestration capacity.

Automated summary

Investigating the biomass dynamic variations of the Caragana korshinskii shrub in the arid desert area of Ningxia, China, this study developed a model to predict its growth and accurately estimate its carbon storage. The NSUR method of the NLS equations system outperformed other methods and was efficient for predicting AGB growth. This research has significant implications for natural resource management and carbon neutralization efforts.