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Evaluating the convergence between eddy-covariance and biometric methods for assessing carbon budgets of forests
The eddy-covariance (EC) micro-meteorological technique and the ecology-based biometric methods (BM) are the primary methodologies to quantify CO(2) exchange between terrestrial ecosystems and the atmosphere (net ecosystem production, NEP) and its two components, ecosystem respiration and gross prim...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5171944/ https://www.ncbi.nlm.nih.gov/pubmed/27966534 http://dx.doi.org/10.1038/ncomms13717 |
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author | Campioli, M. Malhi, Y. Vicca, S. Luyssaert, S. Papale, D. Peñuelas, J. Reichstein, M. Migliavacca, M. Arain, M. A. Janssens, I. A. |
author_facet | Campioli, M. Malhi, Y. Vicca, S. Luyssaert, S. Papale, D. Peñuelas, J. Reichstein, M. Migliavacca, M. Arain, M. A. Janssens, I. A. |
author_sort | Campioli, M. |
collection | PubMed |
description | The eddy-covariance (EC) micro-meteorological technique and the ecology-based biometric methods (BM) are the primary methodologies to quantify CO(2) 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. |
format | Online Article Text |
id | pubmed-5171944 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-51719442016-12-23 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. Reichstein, M. Migliavacca, M. Arain, M. A. Janssens, I. A. Nat Commun Article The eddy-covariance (EC) micro-meteorological technique and the ecology-based biometric methods (BM) are the primary methodologies to quantify CO(2) 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. Nature Publishing Group 2016-12-14 /pmc/articles/PMC5171944/ /pubmed/27966534 http://dx.doi.org/10.1038/ncomms13717 Text en Copyright © 2016, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Campioli, M. Malhi, Y. Vicca, S. Luyssaert, S. Papale, D. Peñuelas, J. Reichstein, M. Migliavacca, M. Arain, M. A. Janssens, I. A. Evaluating the convergence between eddy-covariance and biometric methods for assessing carbon budgets of forests |
title | Evaluating the convergence between eddy-covariance and biometric methods for assessing carbon budgets of forests |
title_full | Evaluating the convergence between eddy-covariance and biometric methods for assessing carbon budgets of forests |
title_fullStr | Evaluating the convergence between eddy-covariance and biometric methods for assessing carbon budgets of forests |
title_full_unstemmed | Evaluating the convergence between eddy-covariance and biometric methods for assessing carbon budgets of forests |
title_short | Evaluating the convergence between eddy-covariance and biometric methods for assessing carbon budgets of forests |
title_sort | evaluating the convergence between eddy-covariance and biometric methods for assessing carbon budgets of forests |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5171944/ https://www.ncbi.nlm.nih.gov/pubmed/27966534 http://dx.doi.org/10.1038/ncomms13717 |
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