利用2011年采集的150株西藏天然冷杉数据,采用度量误差联立方程组方法同时进行整体建模和分段建模,分别建立了西藏冷杉一元、二元生物量与材积相容性模型,并分析对比两者拟合效果.结果表明:不论是一元、二元模型,采用整体建模方法都难以准确描述冷杉生物量、材积随胸径变化情况,导致径阶16 cm以下的林木立木材积和生物量估计值均小于实际值,径阶越小,偏差越大,其中4 cm径阶的预估偏差甚至达到了20%~30%;而采用分段建模方法能有效解决上述有偏估计的问题,模型改进效果十分良好,各径阶均无系统偏差;分段建立的地上生物量和立木材积方程,不论一元或二元模型,其预估精度分别达到了93.5%、92.8%以上,一元分段地下生物量方程预估精度也在91.5%以上.%Based on the tree volume and biomass data of 150 Abies in Tibet, the compatible tree volume and biomass equations and biomass conversion functions were constructed by using the error-in-variable simultaneous equations and segmented modeling approach,and the fitting effect between the two models were analyzed and compared.The results show that: The whole single-tree equations is very difficult to accurately describe the biomass and tree volume with DBH variation,the whole simulation equations for single-tree tree volume and biomass may result in obvious biased estimation for small young trees(DBH<16 cm), the prediction deviation reached 20% or even more than 30% in 4 cm diameter grade. But the segmented modeling approach can resolve the problem of systematically biased estimation in small diameter classes for commonly-used tree volume and biomass equations. Through the one or two variable-based segmented equations,both the prediction precision (P) of tree volume and above-ground biomass estimates for the whole data are more than 93.5%, 92.8%,and through the one variables-based segmented equations,the prediction precision (P) of below-ground biomass estimates for the whole data is more than 91.5%.
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