文献类型：期刊文献

中文题名：华北落叶松人工林生物量的估算方法

英文题名：Estimating biomass of Larix principis-rupprechtii Mayr. plantations in northern China

作者：罗云建[1,2] 王效科[2] 张小全[1,3] 朱建华[1] 侯振宏[1] 张治军[4] 褚金翔[1]

第一作者：罗云建

机构：[1]中国林业科学研究院森林生态环境与保护研究所,国家林业局森林生态环境重点实验室;[2]中国科学院生态环境研究中心,城市与区域生态国家重点实验室;[3]美国大自然保护协会中国部;[4]国家林业局昆明勘察设计院

年份：2010

卷号：34

期号：3

起止页码：51-56

中文期刊名：南京林业大学学报：自然科学版

收录：CSTPCD;;北大核心:【北大核心2008】；CSCD:【CSCD2011_2012】；

基金：科技部科研院所社会公益性研究专项(2004DIB3J103);"十一五"国家科技支撑计划(2007BAC03A07;2006BAD03A0704);国家林业局"948"项目(2006-4-17)

语种：中文

中文关键词：森林生物量;估算模型;相对生长;区域差异;华北落叶松人工林

外文关键词：forest biomass; estimation model; allometry; heterogeneity; Larix principis-rupprechtii plantation

分类号：S718.5

摘要：生物量估算参数以比值的形式描述林分蓄积量、树干生物量、地上生物量和地下生物量间的相对生长关系。为降低区域森林生物量估算及其变化的不准确性,以华北落叶松(Larix princi-pis-rupprechtii Mayr.)人工林为例,利用89块样地的实测数据,分析了关帝山林区、五台山中山区、五台山盆地区和塞罕坝林区等4个典型区域地上生物量(MA)与蓄积量(V)、地上生物量(MA)与树干生物量(MS)以及地下生物量(MR)与地上生物量(MA)间的回归方程及其区域差异。结果表明,区域MA与V方程间和MA与MS方程间存在显著差异(p<0.05),建议按区域构建MA与V以及MA与MS的方程;不同区域的MR与MA方程间无显著差异(p>0.05);整个区域的方程也有良好的回归效果(R2>0.90)。此外,利用V、MS、MA和MR间的函数关系将提高生物量估算的准确性,整体优于利用生物量估算参数和林分指标的函数关系。
Generally,biomass estimation factors are used to estimate regional forest biomass,including biomass conversion and expansion factor （BCEF）,biomass expansion factor （BEF）,basic wood density （WD） and root： shoot ratio （RSR）. Recent studies have showed the values of biomass estimation factors had large uncertainties,which were obtained using those functions between biomass estimation factors and stand measured variables （e. g. stand age,diameter and tree height）. Essentially,biomass estimation factors describe the allometries relationship between shoot biomass （MA） and standing volume （V）,between shoot biomass （MA） and stem biomass （MS）,and between root biomass （MR） and shoot biomass （MA）. To reduce the uncertainties in regional forest biomass estimates,we took Larix principis-rupprechtii Mayr. plantations as a case study,developed region-specific allometric equations for MA vs. V,MA vs. MS,and MR vs. MA,and analyzed their differences among regions （ i. e. Guandi Mountain,middle-alpine zone of Wutai Mountain,basin zone of Wutai Mountain and Saihanba Forest Region）. Results showed that there were significant differences among region-specific allometric equations for MA vs. V （p 0. 05） as well as for MA vs. MS（p 0. 05）,but there was no significant differences among region-specific allometric equations for MR vs. MA（p 0. 05）. Even so,allometric equations for entire regions had good prediction accuracy （R2 0. 90）. Considering significant differences among regionspecific allometric equations,it had better develop and select region-specific allometric equations. Moreover,regional forest biomass estimates using these allometric equations are better than using the functions between biomass estimation factors and stand measured variables.