Chinese FLUX Observation and Research Network (ChinaFLUX) Thematic Observation Datasets Zone II Versions ZH3 Vol 6 (1) 2021
An observation dataset of carbon and water fluxes in a mixed coniferous broad-leaved forest at Dinghushan,Southern China (2003 – 2010)
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Abstract & Keywords
Abstract: The carbon-water cycle process in terrestrial ecosystems is a critical ecological process in the global ecosystems, and the scientific quantitation of carbon water flux in the carbon-water cycle of forest ecosystem is key to accurately quantifying the carbon-water process in terrestrial ecosystems. The eddy covariance is a micro-meteorological method that is currently used to monitor carbon-water flux and to achieve an accurate quantification of these fluxes in forest ecosystems. The technique provides a solid foundation for the study of carbon source/sink contribution of forest ecosystems in carbon sequestration. As a core member of Chinese Ecosystem Research Network (CERN) and National Ecosystem Research Network of China (CNERN), Dinghushan Forest Ecosystem Research Station (the Station) has been monitoring carbon and water fluxes in a mixed broadleaf-conifer forest, a major forest type in low subtropical China since the end of 2002, which is now in line with an improved standardization procedure. Among the major forest types, the mixed broadleaf-conifer forest is a typical forest at Dinghushan, and also a common forest type in lower subtropical China. According to the unified technical specifications of ChinaFLUX, the Station has carried out a 17-year of standardized monitoring of carbon-water flux and key meteorological elements in the mixed coniferous broad-leaved forest ecosystem from 2003 to 2010. The statistically systematized and analyzed dataset presents the dynamic measurement data of carbon water fluxes in the mixed coniferous broad-leaved forest from 2003 to 2010 at Dinghushan. The dataset also includes the information on the process of dataset construction. The setup and data sharing of the carbon-water flux database provide critical data for deep studies on the carbon, water and energy exchange between the forest canopy and atmospheric boundary layers, in the context of water and heat pattern under global change. The dataset is a strong support for forest management and ecosystem service function evaluation in this lower subtropical area.
Keywords: Key words: Dinghushan National Nature Reserve; eddy covariance methods; mixed coniferous broad-leaved forest; carbon-water flux; meteorological factor
Dataset Profile
TitleAn observation dataset of carbon and water fluxes in a mixed coniferous broad-leaved forest at Dinghushan (2003 – 2010)
Data authorsLI Yuelin, YAN Junhua, MENG Ze, HUANG Jianqiang, ZHANG Leiming, CHEN Zhi, LIU Shizhong, CHU Guowei, ZHANG Qianmei, ZHANG Deqiang
Data corresponding authorLi Yuelin (; Yan Junhua (
Time rangeFrom January 2003 to December 2010
Geographical scopeDinghushan National Nature Reserve of China, 23°09′21"N–23°11′30"N, 112°30′39"E–112°33′41"E.
Data format*.xls
Data volume35 MB
Data service system<>
Sources of fundingNational Science Foundation of China (31670453, 31961143023); Strategic Priority Research Program of the Chinese Academy of Sciences (XDA19020302); Dinghushan Forest Ecosystem Positioning Research Station of the National Science and Technology Infrastructure Platform, Chinese Ecosystem Research Network (CERN); Operation Service Project of National Scientific Observation and Research Field Station of Dinghushan Forest Ecosystem in Guangdong, Ministry of Science and Technology of the People’s Republic of China.
Dataset compositionThe dataset is composed of routine meteorological data (air temperature, air relative humidity, vapor pressure, wind speed, wind direction, soil temperature, soil moisture, solar radiation, photosynthetic active radiation, and precipitation, etc.) and carbon and water fluxes (gross ecosystem primary productivity, ecosystem respiration, net ecosystem productivity, latent heat flux, sensible heat flux), forming data products of half-hour, daily, monthly, and yearly scales.
Article and author information
Li Yuelin
Yan Junhua
Meng Ze
Huang Jianqiang
Zhang Leiming
Chen Zhi
Liu Shizhong
Chu Guowei
Zhang Qianmei
Zhang Deqiang
Publication records
Released: Nov. 23, 2020 ( VersionsZH2
Published: March 30, 2021 ( VersionsZH3