title: [Compatible biomass models for main tree species with measurement error in Heilongjiang Province of Northeast China].
abstract: Based on the biomass data of 516 sampling trees, and by using non-linear error-in-variable modeling approach, the compatible models for the total biomass and the biomass of six components including aboveground part, underground part, stem, crown, branch, and foliage of 15 major tree species (or groups) in Heilongjiang Province were established, and the best models for the total biomass and components biomass were selected. The compatible models based on total biomass were developed by adopting the method of joint control different level ratio function. The heteroscedasticity of the models for total biomass was eliminated with log transformation, and the weighted regression was applied to the models for each individual component. Among the compatible biomass models established for the 15 major species (or groups) , the model for total biomass had the highest prediction precision (90% or more), followed by the models for aboveground part and stem biomass, with a precision of 87.5% or more. The prediction precision of the biomass models for other components was relatively low, but it was still greater than 80% for most test tree species. The modeling efficiency (EF) values of the total, aboveground part, and stem biomass models for all the tree species (or groups) were over 0.9, and the EF values of the underground part, crown, branch, and foliage biomass models were over 0.8.
authors.affiliation: School of Forestry, Northeast Forestry University, Harbin 150040, China. donglihu2006@163.com
authors.forename: Li-hu
authors.initials: LH
authors.lastname: Dong
authors.forename: Feng-ri
authors.initials: FR
authors.lastname: Li
authors.forename: Wei-wei
authors.initials: WW
authors.lastname: Jia
authors.forename: Fu-xiang
authors.initials: FX
authors.lastname: Liu
authors.forename: He-zhi
authors.initials: HZ
authors.lastname: Wang
mesh_terms: D018533:Biomass; D002681:China; D017753:Ecosystem; D008954:Models, Biological; D014197:Trees / Q000145:classification / Q000254:growth & development*