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Partitioning of Net Fluxes

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Eddy Covariance

Part of the book series: Springer Atmospheric Sciences ((SPRINGERATMO))

Abstract

Inferring two dependent variables (R eco and GEP) from one observation (NEE) is an ill-posed problem; the same net flux can result from an indefinite number of combinations of R eco and GEP if both are simultaneously occurring or have occurred over the temporal averaging interval used to describe NEE. Hence, additional constraints or information about flux processes are needed. Most flux partitioning strategies are based on the notion that only R eco occurs at night in ecosystems dominated by C3 and/or C4 photosynthesis, while GEP is virtually zero [but not with CAM photosynthesis, San-José et~al. (2007)]. The challenge comes in extrapolating these nighttime R eco measurements to daytime conditions to estimate GEP by difference using Eq. 9.1. These difficulties are compounded by the fact that nighttime flux measurements are often compromised by stable atmospheric conditions with insufficient turbulence to satisfy the assumptions of the eddy covariance measurement system. These observations must be filtered from the eddy covariance data record (Sect. 5.3), leaving incomplete information about R eco and thereby GEP.

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Authors and Affiliations

  1. Max-Planck Institute for Biogeochemistry, 07745, Jena, Germany

    Markus Reichstein & Gitta Lasslop

  2. Department of Land Resources and Environmental Sciences, Montana State University, 173120, Bozeman, MT, 59717-3120, USA

    Paul C. Stoy

  3. Atmospheric and Oceanic Sciences, University of Wisconsin, Madison, USA

    Ankur R. Desai

  4. Department of Orgasmic and Evolutionary Biology, Harvard University Herbaria, 22 Divinity Avenue, Cambridge, MA, 02138, USA

    Andrew D. Richardson

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  1. Markus Reichstein
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Correspondence to Markus Reichstein .

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  1. Gembloux Agro-Bio Tech, Unit of Biosystem Physics, Université de Liège, Passage des Deportés 2, Gembloux, 5030, Belgium

    Marc Aubinet

  2. Dept. Economics, University of Helsinki, Helsinki, Finland

    Timo Vesala

  3. Department for Innovation in Biological,, Agro-food and Forest Systems, University of Tuscia, Via Camillo de Lellis, Viterbo, 01100, Italy

    Dario Papale

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© 2012 Springer Science+Business Media B.V.

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Reichstein, M., Stoy, P.C., Desai, A.R., Lasslop, G., Richardson, A.D. (2012). Partitioning of Net Fluxes. In: Aubinet, M., Vesala, T., Papale, D. (eds) Eddy Covariance. Springer Atmospheric Sciences. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-2351-1_9

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