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Cited by 787

The DOI matches its Crossref record; 69 of the 69 references it cites were found in a registry or an index.

Deriving a light use efficiency model from eddy covariance flux data for predicting daily gross primary production across biomes

Open access
Yuan, Wenping, Liu, Shuguang, Zhou, Guangsheng, Zhou, Guoyi, Tieszen, Larry L., Baldocchi, Dennis, Bernhofer, Christian, Gholz, Henry, Goldstein, Allen H., Goulden, Michael L., Hollinger, David Y., Hu, Yueming, Law, Beverly E., Stoy, Paul C., Vesala, Timo, Wofsy, Steven C.·2007·Agricultural and Forest Meteorology
DOI 10.1016/j.agrformet.2006.12.001
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Abstract

The quantitative simulation of gross primary production (GPP) at various spatial and temporal scales has been a major challenge in quantifying the global carbon cycle. We developed a light use efficiency (LUE) daily GPP model from eddy covariance (EC) measurements. The model, called EC-LUE, is driven by only four variables: normalized difference vegetation index (NDVI), photosynthetically active radiation (PAR), air temperature, and the Bowen ratio of sensible to latent heat flux (used to calculate moisture stress). The EC-LUE model relies on two assumptions: First, that the fraction of absorbed PAR (fPAR) is a linear function of NDVI; Second, that the realized light use efficiency, calculated from a biome-independent invariant potential LUE, is controlled by air temperature or soil moisture, whichever is most limiting. The EC-LUE model was calibrated and validated using 24,349 daily GPP estimates derived from 28 eddy covariance flux towers from the AmeriFlux and EuroFlux networks, covering a variety of forests, grasslands and savannas. The model explained 85% and 77% of the observed variations of daily GPP for all the calibration and validation sites, respectively. A comparison with GPP calculated from the Moderate Resolution Imaging Spectroradiometer (MODIS) indicated that the EC-LUE model predicted GPP that better matched tower data across these sites. The realized LUE was predominantly controlled by moisture conditions throughout the growing season, and controlled by temperature only at the beginning and end of the growing season. The EC-LUE model is an alternative approach that makes it possible to map daily GPP over large areas because (1) the potential LUE is invariant across various land cover types and (2) all driving forces of the model can be derived from remote sensing data or existing climate observation networks.

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Citations

Cites

Show all 69 references

Research works printed but not linked: 24

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Metadata

Authors
Yuan, W., Liu, S., Zhou, G., Zhou, G., Tieszen, L. L., Baldocchi, D., Bernhofer, C., Gholz, H., Goldstein, A. H., Goulden, M. L., Hollinger, D. Y., Hu, Y., Law, B. E., Stoy, P. C., Vesala, T., & Wofsy, S. C.
Venue
Agricultural and Forest Meteorology
Publisher
Elsevier BV
Published
2007-04
Volume
143
Issue
3-4
Pages
189-207
ISSN
0168-1923 (ISSN-L)
DOI
10.1016/j.agrformet.2006.12.001
OpenAlex
W2158897782
Cited by
787
References
69
FWCI
11.30
Type
journal article
Language
en
Open access
green
Licence
www.elsevier.com/tdm/userlicense/1.0/ (tdm)

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CoChat. (2026). Citation check: Deriving a light use efficiency model from eddy covariance flux data for predicting daily gross primary production across biomes. https://app.cochat.ai/papers/10.1016/j.agrformet.2006.12.001
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Yuan, W., Liu, S., Zhou, G., Zhou, G., Tieszen, L. L., Baldocchi, D., Bernhofer, C., Gholz, H., Goldstein, A. H., Goulden, M. L., Hollinger, D. Y., Hu, Y., Law, B. E., Stoy, P. C., Vesala, T., & Wofsy, S. C. (2007). Deriving a light use efficiency model from eddy covariance flux data for predicting daily gross primary production across biomes. Agricultural and Forest Meteorology. https://doi.org/10.1016/j.agrformet.2006.12.001

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