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  Evaluating the convergence between eddy covariance and biometric methods for assessing carbon budgets of forests

Campioli, M., Malhi, Y., Vicca, S., Luyssaert, S., Papale, D., Peñuelas, J., et al. (2016). Evaluating the convergence between eddy covariance and biometric methods for assessing carbon budgets of forests. Nature Communications, 7: 13717. doi:10.1038/ncomms13717.

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http://dx.doi.org/10.1038/ncomms13717 (Publisher version)
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 Creators:
Campioli, M., Author
Malhi, Y., Author
Vicca, S., Author
Luyssaert, S., Author
Papale, D., Author
Peñuelas, J., Author
Reichstein, Markus1, Author           
Migliavacca, Mirco2, Author           
Arain, M. A., Author
Janssens, I. A., Author
Affiliations:
1Department Biogeochemical Integration, Dr. M. Reichstein, Max Planck Institute for Biogeochemistry, Max Planck Society, ou_1688139              
2Biosphere-Atmosphere Interactions and Experimentation, Dr. M. Migliavacca, Department Biogeochemical Integration, Dr. M. Reichstein, Max Planck Institute for Biogeochemistry, Max Planck Society, ou_1938307              

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Free keywords: In-situ Observations
 Abstract: The eddy-covariance (EC) micro-meteorological technique and the ecology-based biometric methods (BM) are the primary methodologies to quantify CO2 exchange between terrestrial ecosystems and the atmosphere (net ecosystem production, NEP) and its two components, ecosystem respiration and gross primary production. Here we show that EC and BM provide different estimates of NEP, but comparable ecosystem respiration and gross primary production for forest ecosystems globally. Discrepancies between methods are not related to environmental or stand variables, but are consistently more pronounced for boreal forests where carbon fluxes are smaller. BM estimates are prone to underestimation of net primary production and overestimation of leaf respiration. EC biases are not apparent across sites, suggesting the effectiveness of standard post-processing procedures. Our results increase confidence in EC, show in which conditions EC and BM estimates can be integrated, and which methodological aspects can improve the convergence between EC and BM.

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 Dates: 2016-10-272016-12-142016
 Publication Status: Issued
 Pages: -
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 Table of Contents: -
 Rev. Type: -
 Identifiers: Other: BGC2563
DOI: 10.1038/ncomms13717
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Project name : BACI
Grant ID : 640176
Funding program : Horizon 2020 (H2020)
Funding organization : European Commission (EC)

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Title: Nature Communications
  Abbreviation : Nat. Commun.
Source Genre: Journal
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Publ. Info: London : Nature Publishing Group
Pages: - Volume / Issue: 7 Sequence Number: 13717 Start / End Page: - Identifier: ISSN: 2041-1723
CoNE: https://pure.mpg.de/cone/journals/resource/2041-1723