Abstract: Reaumuria soongorica is a perennial semishrub that is widely distributed in the semidesert regions of China.It is one of the most typical plant species in arid deserts and shows excellent characteristics of soil fixation wind erosion prevention.Estimation of Reaumuria soongorica biomass is important for evaluating its ecological function in the desert steppe and managing desert grasslands.In this context,a predictive model is one of the important methods to estimate R.soongorica biomass.Therefore,the full digging method was used to obtain the biomass of aboveground parts and belowground roots of R.soongorica in Urat desert steppe.Regression analysis with the relevant growth model(power function W=aX^b) was applied to construct the predictive models for biomass of the aboveground parts(W₁),underground parts(W₂),and whole plant(W) based on plant height(H),crown width(C),and base diameter(D).Optimal biomass estimation models were then screened by comparing size of the discriminant coefficient R2.The results showed that (1) the estimation model W₁= 0.555×C^1.867(R²=0.866) better reflected cumulative characteristics of the aboveground biomass of a single R.soongorica plant;(2) the estimation model W₂=2.259×(D²H)^0.762(R²=0.769) better reflected cumulative characteristics of the underground biomass of R.soongorica;and (3) the estimation model W=7.057×(D²H)^0.813(R²=0.859) better reflected cumulative characteristics of the total biomass of R.soongorica.These biomass models showed high precision and were easy to implement.Our data provide a scientific basis for evaluating the ecological function of R.soongorica in Urat desert steppe and for accurately measuring the biomass of this species.

Key words: desert steppe, Reaumuria soongorica, biomass, predictive model, Urat, Inner Mongolia