A review of biomass equations for China's tree species

被引:63
|
作者
Luo, Yunjian [1 ,2 ,4 ]
Wang, Xiaoke [2 ,3 ]
Ouyang, Zhiyun [2 ]
Lu, Fei [2 ]
Feng, Liguo [1 ]
Tao, Jun [1 ]
机构
[1] Yangzhou Univ, Coll Hort & Plant Protect, Yangzhou 225009, Jiangsu, Peoples R China
[2] Chinese Acad Sci, Ecoenvironm Sci Res Ctr, State Key Lab Urban & Reg Ecol, Beijing 100085, Peoples R China
[3] Univ Chinese Acad Sci, Beijing 100049, Peoples R China
[4] Minist Educ, Joint Int Res Lab Agr & Agri Prod Safety, Yangzhou 225009, Jiangsu, Peoples R China
基金
中国国家自然科学基金; 中国博士后科学基金;
关键词
ALLOMETRIC EQUATIONS; ABOVEGROUND BIOMASS; FOREST; ALLOCATION; MODELS; SCALE; ROOT;
D O I
10.5194/essd-12-21-2020
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Tree biomass equations are the most commonly used method to estimate tree and forest biomasses at various spatial and temporal scales because of their high accuracy, efficiency and conciseness. For decades, many tree biomass equations have been reported in diverse types of literature (e.g., journals, books and reports). These scattered equations are being compiled, and tree biomass equation datasets are currently available for many geographical regions (e.g., Europe, North America and sub-Saharan Africa) and countries (e.g., Australia, Indonesia and Mexico). However, one important country stands out as an area where a large number of biomass equations have not yet been reviewed and inventoried extensively: China. Therefore, in this study, we carried out a broad survey and critical review of the literature (from 1978 to 2013) on biomass equations in China and compiled a normalized tree biomass equation dataset for China. This dataset consists of 5924 biomass equations for nearly 200 tree species and their associated background information (e.g., geographical location, climate and stand description), showing sound geographical, climatic and forest vegetation coverage across China. The dataset is freely available at https://doi.org/10.1594/PANGAEA.895244 (Luo et al., 2018) for noncommercial scientific applications, and this dataset fills an important regional gap in global biomass equations and provides key parameters for biomass estimation in forest inventory and carbon accounting studies in China.
引用
收藏
页码:21 / 40
页数:20
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