Biomass equations for four shrub species in subtropical China

Estimation of shrub biomass can provide more accurate estimates of forest biomass and carbon sequestration. We developed species-specific biomass regression models for four common shrub species, Chinese loropetal (Loropetalum chinense), white oak (Quercus fabri), chastetree (Vitex negundo var. cannabifolia), and Gardenia (Gardenia jasminoides), in southeast China. The objective of this study was to derive appropriate regression equations for estimation of shrub biomass. The results showed that the power model and the quadratic model are the most appropriate forms of equation. CA (canopy area, m(2)) as the sole independent variable was a good predictor of leaf biomass. D (2) H, where D is the basal diameter (cm) and H is the shrub height (cm), is a good predictor of branch and root biomass, except for V. negundo var. cannabifolia and the root biomass of L. chinense. For total biomass, D (2) is the best variable for estimation of L. chinense and G. jasminoides, and D (2) H is the best variable for estimation of Q. fabri and V. negundo var. cannabifolia. Although variables D (2), D (2) H, and H are the preferred predictors for biomass estimation, CV (canopy projected volume, m(3)) could be used alone to predict branch, root, and total biomass in shrub species with acceptable accuracy and precision.