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dc.contributor.authorNelson, J.A.
dc.contributor.authorPérez-Priego, O.
dc.contributor.authorZhou, S.
dc.contributor.authorPoyatos, R.
dc.contributor.authorZhang, Y.
dc.contributor.authorBlanken, P.D.
dc.contributor.authorGimeno, T.E.
dc.contributor.authorWohlfahrt, G.
dc.contributor.authorDesai, A.R.
dc.contributor.authorGioli, B.
dc.contributor.authorLimousin, J.M.
dc.contributor.authorBonal, D.
dc.contributor.authorPaul-Limoges, E.
dc.contributor.authorScott, R.L.
dc.contributor.authorVarlagin, A.
dc.contributor.authorFuchs, K.
dc.contributor.authorMontagnani, L.
dc.contributor.authorWolf, S.
dc.contributor.authorDelpierre, N.
dc.contributor.authorBerveiller, D.
dc.date.accessioned2021-05-10T11:13:23Z
dc.date.available2021-05-10T11:13:23Z
dc.date.issued2020
dc.identifier.citationGLOBAL CHANGE BIOLOGY: 26 (12): 6916-6930 (2020)es_ES
dc.identifier.issn13541013
dc.identifier.urihttp://hdl.handle.net/10810/51339
dc.description.abstractWe apply and compare three widely applicable methods for estimating ecosystem transpiration (T) from eddy covariance (EC) data across 251 FLUXNET sites globally. All three methods are based on the coupled water and carbon relationship, but they differ in assumptions and parameterizations. Intercomparison of the three daily T estimates shows high correlation among methods (R between .89 and .94), but a spread in magnitudes of T/ET (evapotranspiration) from 45% to 77%. When compared at six sites with concurrent EC and sap flow measurements, all three EC‐based T estimates show higher correlation to sap flow‐based T than EC‐based ET. The partitioning methods show expected tendencies of T/ET increasing with dryness (vapor pressure deficit and days since rain) and with leaf area index (LAI). Analysis of 140 sites with high‐quality estimates for at least two continuous years shows that T/ET variability was 1.6 times higher across sites than across years. Spatial variability of T/ET was primarily driven by vegetation and soil characteristics (e.g., crop or grass designation, minimum annual LAI, soil coarse fragment volume) rather than climatic variables such as mean/standard deviation of temperature or precipitation. Overall, T and T/ET patterns are plausible and qualitatively consistent among the different water flux partitioning methods implying a significant advance made for estimating and understanding T globally, while the magnitudes remain uncertain. Our results represent the first extensive EC data‐based estimates of ecosystem T permitting a data‐driven perspective on the role of plants’ water use for global water and carbon cycling in a changing climate.es_ES
dc.description.sponsorshipWe acknowledge insightful discussions with Dario Papale and apologize for having a cappuccino after lunch. We further acknowledge Ulrich Weber for preparing the cappuccino. M.G. acknowledges funding by Swiss National Science Foundation project ICOS‐CH Phase 2 20FI20_173691. L.Š. was supported by the Ministry of Education, Youth and Sports of the Czech Republic within the CzeCOS program, grant number LM2015061, and by SustES‐Adaptation strategies for sustainable ecosystem services and food security under adverse environmental conditions (CZ.02.1.01/0.0/0.0/16_019/0000797). G.W. acknowledges support by the Austrian National Science Fund (FWF, project I03859) and the Province of South Tyrol (“Cycling of carbon and water in mountain ecosystems under changing climate and land use”). R.P. was supported by grants CGL2014‐55883‐JIN, RTI2018‐095297‐J‐I00 (Spain), and by a Humboldt Research Fellowship for Experienced Researchers (Germany). This work used eddy covariance data acquired and shared by the FLUXNET community, including these networks: Ameri‐Flux, AfriFlux, AsiaFlux, CarboAfrica, CarboEuropeIP, CarboItaly, CarboMont, ChinaFlux, Fluxnet‐Canada, GreenGrass, ICOS, KoFlux, LBA, NECC, OzFlux‐TERN, TCOS‐Siberia, and USCCC. The ERA‐Interim reanalysis data are provided by ECMWF and processed by LSCE. The FLUXNET eddy covariance data processing and harmonization was carried out by the European Fluxes Database Cluster, AmeriFlux Management Project, and Fluxdata project of FLUXNET, with the support of CDIAC and ICOS Ecosystem Thematic Center, and the OzFlux, ChinaFlux, and AsiaFlux offices. Open access funding enabled and organized by Projekt DEAL.es_ES
dc.language.isoenges_ES
dc.publisherGLOBAL CHANGE BIOLOGYes_ES
dc.relationinfo:eu-repo/grantAgreement/MINECO/RTI2018‐095297‐J‐I00es_ES
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/es/*
dc.subjectecohydrologyes_ES
dc.subjecteddy covariancees_ES
dc.subjectevaporationes_ES
dc.subjectevapotranspirationes_ES
dc.subjectFLUXNETes_ES
dc.subjecttranspirationes_ES
dc.titleEcosystem transpiration and evaporation: Insights from three water flux partitioning methods across FLUXNET siteses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.holder© 2020 The Authors. Global Change Biology published by John Wiley & Sons Ltdes_ES
dc.rights.holderAtribución-NoComercial-CompartirIgual 3.0 España*
dc.relation.publisherversionhttps://dx.doi.org/10.1111/gcb.15314es_ES
dc.identifier.doi10.1111/gcb.15314
dc.contributor.funderFWF
dc.contributor.funderAustrian National Science Fund
dc.contributor.funderMinistry of Education
dc.contributor.funderYouth and Sports of the Czech Republic
dc.contributor.funderSwiss National Science Foundation
dc.contributor.funderChinaFlux


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© 2020 The Authors. Global Change Biology published by John Wiley & Sons Ltd
Except where otherwise noted, this item's license is described as © 2020 The Authors. Global Change Biology published by John Wiley & Sons Ltd