Prediction and Evaluation of Biomass in Eucalyptus urophylla × E.tereticornis at Different Stand Ages in Leizhou Peninsula
Biomass allocation characteristics of Eucalyptus urophylla × E. tereticornis at different stand ages were analyzed,and the optimal growth model was constructed and screened to provide reference for effectively estimating the biomass of different component organs of the tree species E. urophylla × E. tereticornis. To do this,trees of various ages (1,3,5,7,and 8 years old) growing in the Leizhou Peninsula,Zhanjiang,Guangdong Province,were sampled. The biomass of various organs such as wood,bark,branches,leaves,and roots were measured,and the aboveground biomass as well as the total biomass of individual trees were calculated. Diameter at breast height (D) and tree height (H),as well as the derived variables,including DH,and D2H,were used as predictive variables to construct a biomass model for prediction of the biomass of various organs,aboveground parts and total of individual trees of E. urophylla × E. tereticornis at different ages. The prediction accuracies were compared and the optimal model was selected. The results showed that the biomass distribution pattern of various organs was significantly affected by stand age. As stand age increased,the proportion of wood biomass increased continuously and stabilized at about 70％. Also,the proportion of biomass accounted for by each of bark,branches and leaves decreased continuously,whilst the proportion of biomass accounted for by roots was relatively stable. Most of the biomass equations constructed with D,H,DH and D2H as predictive variables could achieve relatively high prediction accuracy and could be applied to the biomass assessment of E. urophylla × E. tereticornis. The optimal independent variables varied according to different organs. By introducing the stand age factor into models,the predictive accuracy of models for each biomass organ,aboveground biomass and total biomass were improved.
Eucalyptus urophylla × E. tereticornisbiomass allocationstand agebiomass model prediction,model evaluation
万方数据
维普
