文献类型：期刊文献

中文题名：广东省木荷单木生物量模型的建立

英文题名：Construction of single tree biomass models for Schima superba in Guangdong Province

作者：何潇[1] 李海奎[1]

第一作者：何潇

机构：[1]中国林业科学研究院资源信息研究所,北京100091

年份：2018

卷号：45

期号：6

起止页码：1071-1076

中文期刊名：安徽农业大学学报

外文期刊名：Journal of Anhui Agricultural University

收录：CSTPCD;;CSCD:【CSCD_E2017_2018】；

基金：广东省林业科技专项"广东主要碳汇造林树种生物量模型研建"(2015-02);广东省林业科技创新平台建设项目"广东省碳汇计量监测创新平台建设"(2016CXPT03)共同资助

语种：中文

中文关键词：单木生物量;可加性模型;木荷;广东省

外文关键词：single tree biomass;additive system;Schima superba;Guangdong Province

分类号：S758.1

摘要：单木生物量模型是森林生物量估算的基础。实测广东境内90株木荷的数据,伐倒前测量胸径、树高等测树因子;伐倒后,树干分为3段测定树干和树皮的鲜重;树冠分为3层,每层选取3～5个标准枝,并分别称枝、叶的鲜质量,取样后带回实验室;在85℃恒温下烘干至恒质量,根据样品鲜质量和干质量计算含水率,然后利用各部分的含水率推算样木树干、树皮、树枝及树叶等各部分干质量,最后汇总得到地上部分干质量。利用获得的生物量数据,以相对生长模型为基础,采用加权回归估计消除异方差,建立可加性生物量模型,拟合地上部分及各个分量的生物量。结果表明,可加性生物量模型系统中,树干生物量模型精度最高,确定系数达0.90以上,树叶生物量模型的精度最低,但确定系数也达0.74,树枝和树皮生物量模型确定系数均大于0.80;木荷树干生物量占地上生物量的比重最大,其次是树枝和树皮生物量,树叶生物量所占比重最低,随着径阶的增加,树干生物量不断增加,树枝生物量略有增加,树皮所占比重变化不大,树叶生物量所占比例持续降低。模型的建立有助于精确估算广东省木荷生物量,为碳汇计量提供基础数据和模型支撑。
Single tree biomass model is the basis of forest biomass estimation. Based on the measured data of 90 strains of Schima superba in Guangdong Province, we measured the DBH and tree height before felled. After felled, the trunk was divided into 3 sections to measure the fresh weight of the stem and bark;the tree-crown was divided into 3 layers with selection of 3-5 standard branches in each layer, and the fresh weights of the branches and leaves were measured, respectively. This samples were taken to laboratory and dried to constant weight under 85℃ constant temperature. According to the fresh and dry weight, the moisture content in each sample was calculated, and then the moisture content in each part was used to calculate the dry weight in samples of stem, bark, branches stem, bark, branches and leaves, and finally the dry weight of the above-ground biomass was summarized. Based on the allometric model, using the obtained biomass data and weighted regression estimation method to eliminate heteroscedasticity, we established an additive biomass model to fit the aboveground biomass and each part biomass. The results showed that: in the additive biomass model system, the accuracy of the stem biomass model was the highest with the coefficient of determination of above 0.90;the accuracy of the leaf biomass model was the lowest with the coefficient of determination of 0.74, and the coefficients of determination of the biomass index of the branches and bark were all above 0.80. Schima superba biomass accounted for the largest proportion of above-ground biomass, followed by dendritic and bark biomass, and the leaf biomass accounted for the lowest proportion. As the diameter increased, the biomass of the stem increased and the biomass of branches increased slightly. The proportion of bark biomass did not change much, and the proportion of leaf biomass continued to decrease. The establishment of the model would be helpful to accurately estimate the biomass of Schima superba in Guangdong Province and provide basic data and model support for carbon sink measurement.