Improved dryland carbon flux predictions with explicit consideration of water-carbon coupling

Upscaling in situ carbon flux measurements using remotely sensed and meteorological observations in a machine learning algorithm leads to improved estimates of average uptake, and interannual variability in global drylands.

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Autores principales:	Mallory L. Barnes, Martha M. Farella, Russell L. Scott, David J. P. Moore, Guillermo E. Ponce-Campos, Joel A. Biederman, Natasha MacBean, Marcy E. Litvak, David D. Breshears
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Geology QE1-996.5 Environmental sciences GE1-350
Acceso en línea:	https://doaj.org/article/cc09b7906fa14313a1c796d37d5d2281
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spelling	oai:doaj.org-article:cc09b7906fa14313a1c796d37d5d22812021-12-05T12:08:38ZImproved dryland carbon flux predictions with explicit consideration of water-carbon coupling10.1038/s43247-021-00308-22662-4435https://doaj.org/article/cc09b7906fa14313a1c796d37d5d22812021-12-01T00:00:00Zhttps://doi.org/10.1038/s43247-021-00308-2https://doaj.org/toc/2662-4435Upscaling in situ carbon flux measurements using remotely sensed and meteorological observations in a machine learning algorithm leads to improved estimates of average uptake, and interannual variability in global drylands.Mallory L. BarnesMartha M. FarellaRussell L. ScottDavid J. P. MooreGuillermo E. Ponce-CamposJoel A. BiedermanNatasha MacBeanMarcy E. LitvakDavid D. BreshearsNature PortfolioarticleGeologyQE1-996.5Environmental sciencesGE1-350ENCommunications Earth & Environment, Vol 2, Iss 1, Pp 1-9 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Geology QE1-996.5 Environmental sciences GE1-350
spellingShingle	Geology QE1-996.5 Environmental sciences GE1-350 Mallory L. Barnes Martha M. Farella Russell L. Scott David J. P. Moore Guillermo E. Ponce-Campos Joel A. Biederman Natasha MacBean Marcy E. Litvak David D. Breshears Improved dryland carbon flux predictions with explicit consideration of water-carbon coupling
description	Upscaling in situ carbon flux measurements using remotely sensed and meteorological observations in a machine learning algorithm leads to improved estimates of average uptake, and interannual variability in global drylands.
format	article
author	Mallory L. Barnes Martha M. Farella Russell L. Scott David J. P. Moore Guillermo E. Ponce-Campos Joel A. Biederman Natasha MacBean Marcy E. Litvak David D. Breshears
author_facet	Mallory L. Barnes Martha M. Farella Russell L. Scott David J. P. Moore Guillermo E. Ponce-Campos Joel A. Biederman Natasha MacBean Marcy E. Litvak David D. Breshears
author_sort	Mallory L. Barnes
title	Improved dryland carbon flux predictions with explicit consideration of water-carbon coupling
title_short	Improved dryland carbon flux predictions with explicit consideration of water-carbon coupling
title_full	Improved dryland carbon flux predictions with explicit consideration of water-carbon coupling
title_fullStr	Improved dryland carbon flux predictions with explicit consideration of water-carbon coupling
title_full_unstemmed	Improved dryland carbon flux predictions with explicit consideration of water-carbon coupling
title_sort	improved dryland carbon flux predictions with explicit consideration of water-carbon coupling
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/cc09b7906fa14313a1c796d37d5d2281
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Improved dryland carbon flux predictions with explicit consideration of water-carbon coupling

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