18 resultados para ChinaFLUX


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作为中国陆地生态系统通量观测网络(ChinaFLUX)的组成部分,利用涡度相关技术对千烟洲红壤丘陵区亚热带人工针叶林2倍和3倍冠层高度CO2等湍流通量进行了长期观测.采用谱分析、方差相似性关系和能量平衡闭合分析3种测试手段对2003年千烟洲人工林两个高度的湍流通量测定数据质量进行了分析.研究结果表明:(ⅰ)两个测定高度的三维风速,CO2,H2O和温度的功率谱在惯性子区内基本符合-2/3定律,而CO2,H2O和温度与垂直风速的协谱在惯性子区内也基本符合-4/3定律.谱分析表明大尺度运动对物质和能量传输的贡献

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Through 2-3-year (2003-2005) continuous eddy covariance measurements of carbon dioxide and water vapor fluxes, we examined the seasonal, inter-annual, and inter-ecosystem variations in the ecosystem-level water use efficiency (WUE, defined as the ratio of gross primary production, GPP, to evapotranspiration, ET) at four Chinese grassland ecosystems in the Qinghai-Tibet Plateau and North China. Representing the most prevalent grassland types in China, the four ecosystems are an alpine swamp meadow ecosystem, an alpine shrub-meadow ecosystem, an alpine meadow-steppe ecosystem, and a temperate steppe ecosystem, which illustrate a water availability gradient and thus provide us an opportunity to quantify environmental and biological controls on ecosystem WUE at different spatiotemporal scales. Seasonally, WUE tracked closely with GPP at the four ecosystems, being low at the beginning and the end of the growing seasons and high during the active periods of plant growth. Such consistent correspondence between WUE and GPP suggested that photosynthetic processes were the dominant regulator of the seasonal variations in WUE. Further investigation indicated that the regulations were mainly due to the effect of leaf area index (LAI) on carbon assimilation and on the ratio of transpiration to ET (T/ET). Besides, except for the swamp meadow, LAI also controlled the year-to-year and site-to-site variations in WUE in the same way, resulting in the years or sites with high productivity being accompanied by high WUE. The general good correlation between LAI and ecosystem WUE indicates that it may be possible to predict grassland ecosystem WUE simply with LAI. Our results also imply that climate change-induced shifts in vegetation structure, and consequently LAI may have a significant impact on the relationship between ecosystem carbon and water cycles in grasslands.

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Acknowledgements. This work was mainly funded by the EU FP7 CARBONES project (contracts FP7-SPACE-2009-1-242316), with also a small contribution from GEOCARBON project (ENV.2011.4.1.1-1-283080). This work used eddy covariance data acquired by the FLUXNET community and in particular by the following networks: AmeriFlux (U.S. Department of Energy, Biological and Environmental Research, Terrestrial Carbon Program; DE-FG02-04ER63917 and DE-FG02-04ER63911), AfriFlux, AsiaFlux, CarboAfrica, CarboEuropeIP, CarboItaly, CarboMont, ChinaFlux, Fluxnet-Canada (supported by CFCAS, NSERC, BIOCAP, Environment Canada, and NRCan), GreenGrass, KoFlux, LBA, NECC, OzFlux, TCOS-Siberia, USCCC. We acknowledge the financial support to the eddy covariance data harmonization provided by CarboEuropeIP, FAO-GTOS-TCO, iLEAPS, Max Planck Institute for Biogeochemistry, National Science Foundation, University of Tuscia, Université Laval and Environment Canada and US Department of Energy and the database development and technical support from Berkeley Water Center, Lawrence Berkeley National Laboratory, Microsoft Research eScience, Oak Ridge National Laboratory, University of California-Berkeley, University of Virginia. Philippe Ciais acknowledges support from the European Research Council through Synergy grant ERC-2013-SyG-610028 “IMBALANCE-P”. The authors wish to thank M. Jung for providing access to the GPP MTE data, which were downloaded from the GEOCARBON data portal (https://www.bgc-jena.mpg.de/geodb/projects/Data.php). The authors are also grateful to computing support and resources provided at LSCE and to the overall ORCHIDEE project that coordinate the development of the code (http://labex.ipsl.fr/orchidee/index.php/about-the-team).