【摘要】 [目的]研究建立地上生物量与地下生物量、立木材积之间相容,以及地上生物量与各分量之间可加的一体化生物量模型系统,为准确估计森林生物量提供定量依据。[方法]以新疆自治区的云杉(Picea spp.)为研究对象,基于230株和78株样木的实测地上生物量、树干材积和地下生物量数据,综合利用误差变量联立方程组方法和哑变量建模方法,研究建立集地上生物量、树干材积和地下生物量为一体,兼具相容性和可加性的二元和一元生物量模型系统,并分析一元模型是否受地域的影响。[结果]所建云杉一元和二元一体化生物量模型系统,地上生物量方程的平均预估误差在7%以下,干、皮、枝、叶各分项生物量方程的平均预估误差在10%左右,地下生物量方程的平均预估误差在15%以下,均达到了相关技术规定的预估精度要求。除了干材和树皮生物量的估计效果不如二元模型外,一元模型对其它各项生物量的估计均要优于二元模型。比例控制法和代数控制法均能解决地上生物量与干、皮、枝、叶各分项生物量之间的可加性问题,且两种方法得出的模型预估结果无显著差异。[结论]将哑变量引入误差变量联立方程组,不仅能解决地上生物量和地下生物量样本单元数不相等时如何联合建模的问题,还能同时解决地上生物量与地下生物量和立木材积之间的相容性问题及地上生物量与各分量之间的可加性问题,方法切实可行;对地上生物量、地下生物量及立木材积的估计,含区域因子的哑变量模型均要优于总体平均模型。更多还原

【Abstract】 [Objective] The purpose of this study is to develop integrated individual tree biomass equation systems,in which above-ground biomass is compatible with below-ground biomass and stem volume,and stem,bark,branches and foliage biomass are additive to above-ground biomass,for providing a quantitative basis on accurate estimation of forest biomass. [Method]Based on the mensuration data of above-and below-ground biomass from 230 and78 destructive sample trees of Picea spp. in Xinjiang,respectively,one-and two-variable integrated biomass systems with compatibility and additivity,including above-and below-ground biomass,component biomass,and stem volume,were developed using error-in-variable simultaneous equations approach and dummy variable modeling approach,and the impact of region on estimation of biomass and volume was analyzed. [Result]The mean prediction errors( MPEs) of above-ground biomass equations in the developed one-and two-variable integrated biomass systems for Picea spp. in Xinjiang were less than 7%,the MPEs of components biomass equations were about 10%,and the MPEs of below-ground biomass equations were less than 15%,which could meet the need of precision re-quirements from relevant regulation. One-variable equations were better than two-variable equations for estimation of biomass except for stem and bark biomass. Both proportion control and algebraic control methods could ensure the compatibility between above-ground biomass and component biomass,and the difference between estimates of models from the two methods was not significant. [Conclusion]Integrating dummy variable into error-in-variable simultaneous equations is a practical approach,which can simultaneously develop a system even though the numbers of above-and below-ground biomass observations are very different,and ensure not only the compatibility between above-and below-ground biomass and stem volume,but also the additivity between above-ground biomass and component biomass. For estimation of above-and below-ground biomass,and stem volume,the dummy variable models are better than population average models.更多还原