森林工程2026，Vol.42Issue(4)：738-748,11.DOI:10.7525/j.issn.1006-8023.2026.04.008
小兴安岭4种主要灌木生物量可加性模型
Additive Biomass Models for Four Main Shrub Species in Xiaoxing'an Mountains
摘要
Abstract
Based on the biomass data from 140 sampled shrubs of Philadelphus schrenkii,Acanthopanax senticosus,Corylus mandshurica,and Sorbaria sorbifolia,the total biomass and univariate and bivariate additive biomass models of each component for the four main shrub species in Xiaoxing'an Mountains was developed.Using the allometric equations as the base model,the likelihood analysis was employed to determine the error structure of organ-specific biomass mod-els.Optimal biomass models for individual organs were integrated with aboveground and total biomass equations to form a system of simultaneous equations,which was fitted using the seemingly unrelated regression.The established additive biomass models for four shrub species were evaluated using the leave-one-out cross-validation method.The results indi-cated that log-transformed linear regression validated by the likelihood analysis was suitable for modeling organ-specific biomass of four shrub species.Incorporating height improved the predictive accuracy of the additive biomass models.The optimal additive models exhibited adjusted values ranging from 0.7062 to 0.9831,with mean absolute percentage errors between 13%and 42%.The models for total biomass,aboveground biomass,and stem biomass demonstrated su-perior performance compared to those for foliage and root biomass.关键词
灌木/生物量/异速生长/似乎不相关回归/可加性模型Key words
Shrubs/biomass/allometry/seemingly unrelated regressions/additive models分类
农业科技引用本文复制引用
郭羽,崔崧,刘延滨,潘美言,孙国芝,孙一萌,肖锐..小兴安岭4种主要灌木生物量可加性模型[J].森林工程,2026,42(4):738-748,11.基金项目
黑龙江省省属科研院所科研业务费项目(QN2024-09 （）
YB2024-04). （）
