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Article: Large differences in terrestrial vegetation production derived from satellite-based light use efficiency models

TitleLarge differences in terrestrial vegetation production derived from satellite-based light use efficiency models
Authors
KeywordsCASA
CFix
CFlux
EC-LUE
Gross primary production (GPP)
Light use efficiency (LUE)
MODIS
VPM
VPRM
Issue Date2014
Citation
Remote Sensing, 2014, v. 6, n. 9, p. 8945-8965 How to Cite?
AbstractTerrestrial gross primary production (GPP) is the largest global CO2 flux and determines other ecosystem carbon cycle variables. Light use efficiency (LUE) models may have the most potential to adequately address the spatial and temporal dynamics of GPP, but recent studies have shown large model differences in GPP simulations. In this study, we investigated the GPP differences in the spatial and temporal patterns derived from seven widely used LUE models at the global scale. The result shows that the global annual GPP estimates over the period 2000-2010 varied from 95.10 to 139.71 Pg C·yr-1 among models. The spatial and temporal variation of global GPP differs substantially between models, due to different model structures and dominant environmental drivers. In almost all models, water availability dominates the interannual variability of GPP over large vegetated areas. Solar radiation and air temperature are not the primary controlling factors for interannual variability of global GPP estimates for most models. The disagreement among the current LUE models highlights the need for further model improvement to quantify the global carbon cycle.
Persistent Identifierhttp://hdl.handle.net/10722/321614
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorCai, Wenwen-
dc.contributor.authorYuan, Wenping-
dc.contributor.authorLiang, Shunlin-
dc.contributor.authorLiu, Shuguang-
dc.contributor.authorDong, Wenjie-
dc.contributor.authorChen, Yang-
dc.contributor.authorLiu, Dan-
dc.contributor.authorZhang, Haicheng-
dc.date.accessioned2022-11-03T02:20:14Z-
dc.date.available2022-11-03T02:20:14Z-
dc.date.issued2014-
dc.identifier.citationRemote Sensing, 2014, v. 6, n. 9, p. 8945-8965-
dc.identifier.urihttp://hdl.handle.net/10722/321614-
dc.description.abstractTerrestrial gross primary production (GPP) is the largest global CO2 flux and determines other ecosystem carbon cycle variables. Light use efficiency (LUE) models may have the most potential to adequately address the spatial and temporal dynamics of GPP, but recent studies have shown large model differences in GPP simulations. In this study, we investigated the GPP differences in the spatial and temporal patterns derived from seven widely used LUE models at the global scale. The result shows that the global annual GPP estimates over the period 2000-2010 varied from 95.10 to 139.71 Pg C·yr-1 among models. The spatial and temporal variation of global GPP differs substantially between models, due to different model structures and dominant environmental drivers. In almost all models, water availability dominates the interannual variability of GPP over large vegetated areas. Solar radiation and air temperature are not the primary controlling factors for interannual variability of global GPP estimates for most models. The disagreement among the current LUE models highlights the need for further model improvement to quantify the global carbon cycle.-
dc.languageeng-
dc.relation.ispartofRemote Sensing-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectCASA-
dc.subjectCFix-
dc.subjectCFlux-
dc.subjectEC-LUE-
dc.subjectGross primary production (GPP)-
dc.subjectLight use efficiency (LUE)-
dc.subjectMODIS-
dc.subjectVPM-
dc.subjectVPRM-
dc.titleLarge differences in terrestrial vegetation production derived from satellite-based light use efficiency models-
dc.typeArticle-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.3390/rs6098945-
dc.identifier.scopuseid_2-s2.0-84907478732-
dc.identifier.volume6-
dc.identifier.issue9-
dc.identifier.spage8945-
dc.identifier.epage8965-
dc.identifier.eissn2072-4292-
dc.identifier.isiWOS:000343093800046-

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