文献类型：期刊文献

中文题名：多水平林木生物量估算方法研究

英文题名：Estimation Methods of Forest Biomass with Different Levels

作者：尹惠妍[1,2] 李海奎[1]

第一作者：尹惠妍

机构：[1]中国林业科学研究院资源信息研究所;[2]西藏大学农牧学院资源与环境学院

年份：2016

卷号：0

期号：2

起止页码：38-44

中文期刊名：西北林学院学报

外文期刊名：Journal of Northwest Forestry University

收录：CSTPCD;;北大核心:【北大核心2014】；CSCD:【CSCD_E2015_2016】；

基金：多尺度森林生物量建模产品验证技术研究(2012AA12A306)

语种：中文

中文关键词：一类清查;样地生物量;估算;模型

外文关键词：forestry inventory;;sample plot biomass;;estimation;;model

分类号：S718.556

摘要：研究不同水平下林木生物量的估算方法,林分水平不同树种组成的样地生物量估算方法,以及不同尺度生物量的扩展问题,以便于探索大区域的森林生物量估算方法。基于国家森林资源连续清查中广东省的数据资料,分别选择针叶树种马尾松、阔叶树种桉树以及针阔混交林为优势树种的182、168、129个样地数据。在单木水平上,利用已有的各树种生物量模型估算单木生物量,在样地水平上以样地蓄积为自变量,样地总生物量为因变量,分别选用方精云的转换因子连续函数法、一元截距式与一元无截距式、联立方程组截距式与联立方程组无截距式以及幂函数6种方法估算样地生物量,从计算原理和过程、方法特点、模型拟合效果等方面比较研究不同水平下林木生物量的估算方法。在样地水平上,转换因子连续函数法预估效果较差,马尾松林的样地生物量估算方法以含截距式的联立方程组模型预估效果最好,一元无截距式模型适用于针阔混交林,而桉树林的样地生物量估算方法以幂函数方程的预估效果最好。对单株树木而言,各树种的生物形态、树枝与树冠的丰富程度,以及木材密度的大小影响树木材积对生物量的贡献率大小。在样地中,树木年龄不同、大树与小树的比例的差异也会影响样地生物量。
In order to develop the methods of estimating forest biomass(EFB)in large area,this paper examined the methods of EFB in different levels,tree species,and scales.All the data were based on the results of national forest inventory in Guangdong province.Data from 182 sample plots dominated with needle tree species of Pinus massoniana,168 sample plots of broad-leaved tree Eucalyptus,and 129 sample plots of broadleaf-conifer mixed tree species were adopted.In the individual tree level,the biomass was calculated by the known models.In the plot level,6methods were used,such as the continuous function for biomass expansion factor developed by Fang Jing-yun,the function of one variable with intercept,the function of one variable without intercept,the simultaneous equations model with intercept,the simultaneous equation model without intercept,and the power function,in which sample stock volume were considered as the independent variable and sample plot biomass as the dependent variable.By means of analysis the calculation principle and process characteristics of comparative study,appropriate process to estimate sample biomass was selected.For plots with different trees,the continuous function for biomass expansion factordemonstrated poor results.Best estimation results were achieved when the simultaneous equation model with intercept was adopted for Pinus massoniana plots,and the function of one variable without intercept was applicable to the estimation of broadleaf-conifer trees.However,the power function worked best to Eucalyptus tree species.For individual tree,the biological form,the richness of branches and canopies,as well as wood density were directly related to the biomass.For plots,different tree ages and the ratio of big tree to small tree also affected the plot biomass.