E-Science System for Carbon Budget Integration Research of Chinese Terrestrial Ecosystem
Received date: 2011-04-21
Revised date: 2011-11-17
Online published: 2012-02-10
Global and regional ecosystem carbon cycle research is characterized by multi-stations observation networks, multi-sources data with heterogeneous structure, multi-models meta-analysis, and collaboration of scientists across different disciplines. Based on the Chinese Terrestrial Ecosystem Flux Research Network (ChinaFLUX), we proposed an e-Carbon Science with its goals, components, and key techniques and reported current progress. ChinaFLUX e-carbon science consists of four environments (the carbon cycle data integration and service environment, the model simulating environment, the visual analysis environment, and the collaborative scientific research environment) and three application systems (terrestrial carbon budget assessment system at local, regional, and national scales). We developed an integration system of flux data acquisition-transportationstoragemanagement-processing-visualization-service sharing. ChinaFLUX e-carbon science made rapid carbon budget assessment and simulation possible, promoted the development of terrestrial ecosystem carbon cycle research and eco-informatics in China, and played an exemplary role in constructing the informatization of field station networks.
He Honglin, Zhang Li, Li Jianhui, Zhou Yuanchun, Ren Xiaoli, Yu Guirui . E-Science System for Carbon Budget Integration Research of Chinese Terrestrial Ecosystem[J]. Advances in Earth Science, 2012 , 27(2) : 246 -254 . DOI: 10.11867/j.issn.1001-8166.2012.02.0246
[1]Yu Guirui, Wen Xuefa, Sun Xiaomin, et al. Overview of China Flux and evaluation of its eddy covariance measurement[J].Agricultural and Forest Meteorology,2006, 137(3/4):125-137.
[2]Yu Guirui, Sun Xiaomin. Principles of Flux Measurement in Terrestrial Ecosytems[M]. Beijing: Higher Education Press,2006.[于贵瑞,孙晓敏. 陆地生态系统通量观测的原理与方法[M]. 北京: 高等教育出版社, 2006.]
[3]Hey A J G, Tansley S, Tolle K M. The Fourth Paradigm: Data-Intensive Scientific Discovery[J/OL].http:∥research.microsoft.com/en-us/collaboration/fourthparadigm/4th_paradigm_book_complete_lr.pdf,2009.
[4]Rich P M, Keating G N, Riggs T L, et al. A Vision for Carbon Cyberinfrastructure[EB/OL]. http:∥www.bigskyco2.org/presentations/chapman-cyberinfrastructure-18jan05.ppt,2007.
[5]Thornton P E. Biome-BGC: Modeling Effects of Disturbance and Climate Model Product[DB/OL]. Available on-line[http:∥www.daac.ornl.gov] from Oak Ridge National Laboratory Distributed Active Archive Center, Oak Ridge, Tennessee, U.S.A,2005.
[6]Agarwal D, Humphrey M, Beekwilder N, et al. A data-centered collaboration portal to support global carbon-flux analysis[J].Concurrency and Computation: Practice & Experience,2010,22(17):2 323-2 334.
[7]Hamerlinck J D, Wyckoff T B, Oakleaf J R, et al. Cyberinfrastructure for collaborative geologic carbon sequestration research: A conceptual model[J].Rocky Mountain Geology,2010, 45(2): 163-180.
[8]Yu Guirui, He Honglin, Li Jianhui. Study on the e-Science environment for carbon budget integration research of Chinese terrestrial ecosystem[J].e-Science Technology & Application,2009, 5: 21-31.[于贵瑞, 何洪林, 黎建辉. 中国陆地生态系统碳收支集成研究的e-Science环境建设探讨[J]. 科研信息化技术与应用, 2009, 5: 21-31.]
[9]Creare Inc: RBNB Data Turbine[EB/OL].http:∥www.creare.com/rbnb/index.html,2011.
[10]Cepicky J. Py WPS homepage[EB/OL].http:∥pywps.wald.intevation.org/,2009.
[11]Pullen J M, Brunton R, Brutzman D, et al. Using Web services to integrate heterogeneous simulations in a grid environment [J].Future Generation Computer Systems,2005, 21(1): 97-106.
[12]Yu Guirui, Sun Xiaomin. Flux Measurement and Research of Terrestrial Ecosystem in China[M].Beijing: Science Press,2008.[于贵瑞,孙晓敏.中国陆地生态系统的碳通量观测技术及其时空变化特征[M]. 北京: 科学出版社, 2008.]
[13]Liu Min, He Honglin, Sun Xiaomin, et al. Scientific workflow approach (Kepler) for carbon flux data processing[C]∥2009 Second International Conference on Intelligent Computation Technology and Automation,2009: 694-697.
[14]Li Chun, He Honglin, Liu Min, et al. The design and application of CO2 Flux data processing system at ChinaFLUX[J].Geo-Information Science,2008, 10(5): 854-864.[李春, 何洪林, 刘敏,等. ChinaFLUX CO2通量数据处理系统与应用[J].地球信息科学, 2008, 10(5): 854-864.]
[15]Richardson A D, Jenkins J P, Braswell B H, et al. Use of digital webcam images to track spring green-up in a deciduous broadleaf forest[J].Oecologia,2007, 152(2): 323-334.
[16]White M A, Nemani R R. Real-time monitoring and short-term forecasting of land surface phenology[J].Remote Sensing of Environment,2006, 104(1): 43-49.
[17]Ahrends H E, Brugger R, Stockli R, et al. Quantitative phenological observations of a mixed beech forest in northern Switzerland with digital photography[J].Journal of Geophysical Research-Biogeosciences,2008, 113(G04004): 1-11.
[18]Crimmins M A, Crimmins T M. Monitoring plant phenology using digital repeat photography[J].Environmental Management,2008, 41(6): 949-958.
[19]Xiao Xiangming, Zhang Qingyuan, Hollinger D, et al. Modeling gross primary production of an evergreen needle leaf forest using MODIS and climate data[J].Ecological Applications,2005, 15: 954-969.
[20]Cao Mingkui, Woodward F I. Dynamic responses of terrestrial ecosystem carbon cycling to global climate change [J]. Nature,1998,393:249-252.
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