Dong Li-hu, Li Feng-ri, Jia Wei-wei, Liu Fu-xiang, Wang He-zhi
School of Forestry, Northeast Forestry University, Harbin 150040, China.
Ying Yong Sheng Tai Xue Bao. 2011 Oct;22(10):2653-61.
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.
基于516株采样树木的生物量数据,采用非线性测量误差建模方法,建立了黑龙江省15种主要树种(或类群)总生物量以及地上部分、地下部分、树干、树冠、树枝和树叶6个组分生物量的兼容模型,并筛选出总生物量和各组分生物量的最优模型。基于总生物量的兼容模型采用联合控制不同水平比例函数的方法构建。通过对数变换消除总生物量模型的异方差性,并对各单一组分模型应用加权回归。在为15种主要树种(或类群)建立的兼容生物量模型中,总生物量模型的预测精度最高(90%以上),其次是地上部分和树干生物量模型,精度在87.5%以上。其他组分生物量模型的预测精度相对较低,但大多数测试树种仍大于80%。所有树种(或类群)总生物量、地上部分和树干生物量模型的建模效率(EF)值均超过0.9,地下部分、树冠、树枝和树叶生物量模型的EF值超过0.8。