Literature DB >> 11813417

[Vegetation carbon storage and density of forest ecosystems in China].

X Wang1, Z Feng, Z Ouyang.   

Abstract

To improve the estimation of carbon pool of forest ecosystems is very important in studying their CO2 emission and uptake. The estimation of vegetation carbon pool in China has just begun. There is a significant difference among estimates from different methods applied. Based on forest inventory recorded by age class, the vegetation carbon storage of forest ecosystems in China was estimated to be 3.26-3.73 Pg, accounting for 0.6-0.7% of the global pool. The carbon densities were difference among forest types and provinces, in range of 6.47-118.14 Mg.hm-2. There is an incremental tendency from southeast to north and west. This trend is negatively related with the change in population density in logarithmic mode, which indicates that the actual forest carbon density is prominently determined by human activities.

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Year:  2001        PMID: 11813417

Source DB:  PubMed          Journal:  Ying Yong Sheng Tai Xue Bao        ISSN: 1001-9332


  3 in total

1.  Eddy covariance and biometric measurements show that a savanna ecosystem in Southwest China is a carbon sink.

Authors:  Xuehai Fei; Yanqiang Jin; Yiping Zhang; Liqing Sha; Yuntong Liu; Qinghai Song; Wenjun Zhou; Naishen Liang; Guirui Yu; Leiming Zhang; Ruiwu Zhou; Jing Li; Shubin Zhang; Peiguang Li
Journal:  Sci Rep       Date:  2017-02-01       Impact factor: 4.379

2.  Assessment of Carbon Density in Natural Mountain Forest Ecosystems at Northwest China.

Authors:  Li Dai; Yufang Zhang; Lei Wang; Shuanli Zheng; Wenqiang Xu
Journal:  Int J Environ Res Public Health       Date:  2021-02-21       Impact factor: 3.390

3.  Spatial and temporal patterns of carbon storage in forest ecosystems on Hainan island, southern China.

Authors:  Hai Ren; Linjun Li; Qiang Liu; Xu Wang; Yide Li; Dafeng Hui; Shuguang Jian; Jun Wang; Huai Yang; Hongfang Lu; Guoyi Zhou; Xuli Tang; Qianmei Zhang; Dong Wang; Lianlian Yuan; Xubing Chen
Journal:  PLoS One       Date:  2014-09-17       Impact factor: 3.240

  3 in total

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