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林业资源管理 ›› 2018›› Issue (1): 38-43.doi: 10.13466/j.cnki.lyzygl.2018.01.006

• 科学研究 • 上一篇    下一篇

西藏自治区云杉林生物量密度模型研建

刘金山(), 张蓓, 周学武, 邢元军, 张万林   

  1. 国家林业局中南林业调查规划设计院,长沙 410014
  • 收稿日期:2017-12-13 修回日期:2018-01-02 出版日期:2018-02-28 发布日期:2020-09-27
  • 作者简介:刘金山(1986-),男,山东烟台人,工程师,硕士,主要从事森林资源监测、林业碳汇计量监测等工作。Email:xiaoshanzi00@126.com
  • 基金资助:
    国家自然科学基金项目(41171191)

Establishment of Biomass Density Model of Spruce in Tibet

LIU Jinshan(), ZHANG Bei, ZHOU Xuewu, XING Yuanjun, ZHANG Wanlin   

  1. Central South Forest Inventory and Planning Institute of State Forestry Administration,Changsha 410014,China
  • Received:2017-12-13 Revised:2018-01-02 Online:2018-02-28 Published:2020-09-27

摘要:

生物量密度模型是估算生物量和碳储量的依据。以西藏主要针叶树种云杉为研究对象,利用森林资源连续清查实测样地和样木数据,建立了云杉林生物量密度模型。结果表明:生物量密度随树高、郁闭度、胸径及林龄的增加而增加,随海拔的升高和经度的增加而减少。以海拔、郁闭度、平均胸径、经度作为解释变量构建的生物量密度非线性模型,其决定系数为0.716,总相对误差和平均系统误差控制在±1%以内,预估精度达到91.9%,可应用于实测或目测样地/小班生物量估算;以海拔、郁闭度、林龄、经度作为解释变量构建的生物量密度非线性模型,其决定系数为0.626,总相对误差和平均系统误差控制在±2%以内,预估精度达到90.6%,可应用于遥感样地/小班生物量估算;以海拔、郁闭度、胸径、林龄作为解释变量的生物量密度模型,其决定系数为0.717,总相对误差和平均系统误差控制在±2%以内,预估精度达到91.9%,可用于估算某个时间段内云杉林生物量变化或碳汇量。结合西藏森林资源连续清查或森林资源规划设计调查数据,可用于全区尺度上云杉林生物量的估算;利用林龄等因子建立的生物量模型,可掌握生物量、碳汇在空间上的分布规律及某一时期内的碳汇估算。

关键词: 云杉, 生物量, 碳汇, 生物量密度, 林龄

Abstract:

Biomass density models are the basis for estimating biomass and carbon stocks.Taking spruce of the main coniferous forest species in Tibet as research object,the spruce forest biomass density models were established by using measured sample plot and sample tree data of continuous forest resources inventory.The results showed that biomass density increased with the increase of tree height,canopy closure,DBH and forestage,and decreased with the increase of altitude and longitude.The determination coefficient of biomass density nonlinear model is 0.716,the total relative error and the average system error are controlled within±1%,and the estimated accuracy is 91.9%.Since the model is constructed with altitude,canopy closure,mean diameter at breast height and longitude as explanatory variables,it can be applied to the measured or visual sample or small class biomass estimation.The determination coefficient of biomass density nonlinear model is 0.626,the total relative error and the average system error are controlled within ±2%,and the estimated accuracy is 90.6%.Since the model is constructed with elevation,canopy closure,forest age and longitude as explanatory variables,which can be applied to remote sensing sample or small class biomass estimation.The determination coefficient of biomass density nonlinear model is 0.717,the total relative error and the average system error are controlled within ±2%,and the estimated accuracy is 91.9%.Since the model is constructed with elevation,canopy closure,mean diameter at breast height and forest age as explanatory variables,it can be applied to estimate the biomass or carbon sinks of spruce forest in a given period.Combined with the data of continuous forest resources inventory or forest resources planning and design in Tibet,it can be used for estimating the biomass of the spruce forest on the scale of the whole region.The biomass model established by the factors such as age can be used for grasping the biomass and carbon sink distribution law,and carbon sink estimates for a certain period.

Key words: spruce, biomass, carbon sink, biomass density, forest age

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