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作 者:代海军[1] 何怀江[1] 赵秀海[1] 张春雨[1] 汪金松[1] 杨松[1]
机构地区:[1]北京林业大学森林资源与生态系统过程北京市重点实验室,北京100083
出 处:《应用与环境生物学报》2013年第4期718-722,共5页Chinese Journal of Applied and Environmental Biology
基 金:国家林业公益性行业科研专项(200904022);国家"十二五"科技支撑项目(2012BAC01B03);北京市共建项目专项(2012)资助~~
摘 要:为了解阔叶红松林的生物量和碳储量,按照不同径级,采用全收获法对阔叶红松林主要针叶树红松和阔叶树紫椴的地上地下生物量进行分析.利用胸径(DBH)、树高(H)及胸径-树高(D2H)作为变量建立两个树种各器官生物量异速生长模型.结果表明:(1)11株红松的整株生物量变化范围为6.99-1 165.30 kg/株,叶、枝、干、根的生物量相对分配百分数分别为6.54%、18.33%、53.14%和21.99%.10株紫椴的整株生物量变化范围为10.83-1 004.31 kg/株,叶、枝、干、根的生物量相对分配百分数分别为1.80%、16.21%、56.39%和25.60%;(2)两个树种的地上生物量与地下生物量均呈现显著线型关系(P<0.001),拟合方程系数红松为0.30,紫椴为0.27;(3)基于胸径(DBH)建立红松和紫椴各器官的生物量模型可解释量分别超过了96%和90%,与其比较,利用树高(H)为变量建立两者的模型可解释量有所降低,采用胸径-树高(D2H)作为变量建立的生物量模型未能显著提高预测精度.综合模型解释量和回归系数显著性可知,胸径是建立两个树种各器官生物量模型的可靠变量.To better understand biomass and carbon storage of the broadleaf and Korean pine mixed forest, this paper analyzed the above- and belowground biomass of two dominant tree species Korean pine (Pinus koraiensis) and linden (Tilia amurensis) with harvest method along different diameter order. Biomass allometric models for each organ of the two species were established with diameter at breast height (DBH), tree height (H) and diameter-height (DZH). The results showed the whole plant biomass variation range of 11 Korean pine trees was 6.99-1165.30 kg for each tree, the biomass relative percentage of leaf, branch, stem and root as 6.54%, 18.33%, 53.14% and 21.99%, respectively. The total biomass variation range of 10 linden trees was 10.83-1004.31 kg for each tree, the relative ratio of leaf, branch, stem, and root biomass being 1.80%, 16.21%, 56.39% and 25.60%, respectively. There was a significant and linear relationship between the aboveground biomass and underground biomass for both species (P 〈 0.001). The model coefficient of Korean pine and linden was 0.30 and 0.27, respectively. The models based on DBH for each organ biomass of Korean pine and linden could explain more than 96% and 90% in data respectively. On the other hand, the interpretation of models with H as a variable was low. The prediction accuracy of biomass models with D2H as a variable was not significantly higher than that of others. Considering the interpretation and significance of regression coefficient models, DBH is a reliable variable to establish biomass model for each organ of the two species. Fig 2, Tab 4, Ref31
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