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黑龙江东部地区樟子松人工林单木生物量研究
引用本文:贾炜玮,姜生伟,李凤日.黑龙江东部地区樟子松人工林单木生物量研究[J].辽宁林业科技,2008(3):5-9.
作者姓名:贾炜玮  姜生伟  李凤日
作者单位:1. 东北林业大学,黑龙江,哈尔滨,150040
2. 东北林业大学,黑龙江,哈尔滨,150040;辽宁省林业厅,辽宁,沈阳,110001
基金项目:教育部科学技术研究项目
摘    要:文章研究以黑龙江东部地区不同年龄、不同密度及不同立地条件的樟子松(Pinus sylvestris var. mongolica )人工林作为研究对象,基于 26块标准地中139株标准木的树干解析和生物量数据,以树木各测树因子为自变量建立樟子松人工林单木的树干、树枝、树叶及全树重的生物量预测模型;并研究了不同年龄樟子松林分的生物量结构.研究结果表明:樟子松人工林单木各分量生物量的最优模型形式均为CAR模型,各最优模型的变量主要为胸径(D)和树高(H)因子,D2H能够很好地反映树干的干重,胸径和树高能够很好地反映树枝、树叶及全树重的变化;樟子松单株生物量随着年龄的增大而增加,树干的生物量占全树重的比例随年龄的增大而增大,枝和叶的生物量变化趋势与树干相反,都随着年龄的增大而减小.文中研究的不同年龄阶段樟子松人工林的生物量结构变化规律及相应的预测模型,可为进一步了解樟子松人工林生物量的积累提供依据.

关 键 词:樟子松人工林  生物量  模型
文章编号:1001-1714(2008)03-0005-05
修稿时间:2008年4月16日

Biomass of Single Tree of Pinus sylvestris var. mongolica in Eastern Heilongjiang
JIA Wei-wei,JIANG Sheng-wei,LI Feng-ri.Biomass of Single Tree of Pinus sylvestris var. mongolica in Eastern Heilongjiang[J].Liaoning Forestry Science and Technology,2008(3):5-9.
Authors:JIA Wei-wei  JIANG Sheng-wei  LI Feng-ri
Abstract:In this paper,taking Pinus sylvestris var.mongolica plantations with different ages,densities and site qualities in eastern Heilongjiang as studying objective and based on the data of stem analysis and biomass from 139 sample trees in 26 plots,biomass predicting models of stem,branch,leaves and total height of a single tree were formulated by using the measurement factors as independent variables.The biomass structure of Pinus sylvestris var.mongolica plantations with different ages was also studied.The results showed that: the optimization biomass models of various components were CAR models and the best variables were diameter at breast height(D) and height(H) which indicated the changes of branch,leaves and total weight,and the combination of D and H(D2H) showed the changes of dry weight of stem.The biomass of a single tree and the ratio of stem biomass increased with the age;contrarily,the ratio of branch and leaves biomass decreased with the age.The changing rules of biomass structure of Pinus sylvestris var.mongolica plantations in different ages and the predicting models in this paper could provide a theoretical basis for further understanding the biomass accumulation.
Keywords:Pinus sylvestris var  mongolica  biomass  model
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