Study on Biomass Models of Artificial Young Forest in the Northwestern Alpine Region of China

The artificial young forest is an important component of ecosystems, and biomass models are for estimating the carbon storage ecosystems. However, research on lacking. In this study, data 96 saplings three tree species from southern foot Qilian Mountains were collected. These data, coupled with allometric growth equations nonlinear joint estimation method, used to establish independent, component-additive, total-control compatible estimate wood Picea crassifolia (Picea Kom.), Sabina przewalskii (Sabina Pinus tabulaeformis (Pinus tabuliformis Carr.). distribution characteristics components (branch, leaf, trunk, root biomass) goodness fit also analyzed. results showed that (1) multiple regression two independent variables (MRWTIV) superior univariate all species. Base diameter was best-fitting variable model tabulaeformis, addition base crown as MRWTIV can significantly improve accuracy. Tree height przewalskii, accuracy; (2) component-additive model. constructed by method less accurate than models. they maintained good compatibility among enabled more robust estimates regional biomass; (3) crassifolia, aboveground ratio each total highest leaf (26%–68%), followed branch (10%–46%) trunk (11%–55%) biomass, higher underground biomass. conclusion, optimal at sampling site a multivariate It well provide basis future research.