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The impact of the 2015/2016 El Nino on global photosynthesis using satellite remote sensing

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dc.contributor.authorLuo, Xiangzhong-
dc.contributor.authorKeenan, Trevor F.-
dc.contributor.authorFisher, Joshua B.-
dc.contributor.authorJimenez-Munoz, Juan-Carlos-
dc.contributor.authorChen, Jing M.-
dc.contributor.authorJiang, Chongya-
dc.contributor.authorJu, Weimin-
dc.contributor.authorPerakalapudi, Naga-Vineet-
dc.contributor.authorRyu, Youngryel-
dc.contributor.authorTadic, Jovan M.-
dc.date.accessioned2024-03-20T06:05:22Z-
dc.date.available2024-03-20T06:05:22Z-
dc.date.created2019-06-14-
dc.date.created2019-06-14-
dc.date.created2019-06-14-
dc.date.issued2018-11-
dc.identifier.citationPhilosophical Transactions of the Royal Society B: Biological Sciences, Vol.373 No.1760, p. 20170409-
dc.identifier.issn0962-8436-
dc.identifier.urihttps://hdl.handle.net/10371/199180-
dc.description.abstractThe El Nino-Southern Oscillation exerts a large influence on global climate regimes and on the global carbon cycle. Although El Nino is known to be associated with a reduction of the global total land carbon sink, results based on prognostic models or measurements disagree over the relative contribution of photosynthesis to the reduced sink. Here, we provide an independent remote sensing-based analysis on the impact of the 2015-2016 El Nino on global photosynthesis using six global satellite-based photosynthesis products and a global solar-induced fluorescence (SIF) dataset. An ensemble of satellite-based photosynthesis products showed a negative anomaly of -0.7 +/- 1.2 PgC in 2015, but a slight positive anomaly of 0.05 +/- 0.89 PgC in 2016, which when combined with observations of the growth rate of atmospheric carbon dioxide concentrations suggests that the reduction of the land residual sink was likely dominated by photosynthesis in 2015 but by respiration in 2016. The six satellite-based products unanimously identified a major photosynthesis reduction of -1.1 +/- 0.52 PgC from savannahs in 2015 and 2016, followed by a highly uncertain reduction of -0.22 +/- 0.98 PgC from rainforests. Vegetation in the Northern Hemisphere enhanced photosynthesis before and after the peak El Nino, especially in grasslands (0.33 +/- 0.13 PgC). The patterns of satellite-based photosynthesis ensemble mean were corroborated by SIF, except in rainforests and South America, where the anomalies of satellite-based photosynthesis products also diverged the most. We found the inter-model variation of photosynthesis estimates was strongly related to the discrepancy between moisture forcings for models. These results highlight the importance of considering multiple photosynthesis proxies when assessing responses to climatic anomalies. This article is part of a discussion meeting issue 'The impact of the 2015/2016 El Nino on the terrestrial tropical carbon cycle: patterns, mechanisms and implications'.-
dc.language영어-
dc.publisherRoyal Society of London-
dc.titleThe impact of the 2015/2016 El Nino on global photosynthesis using satellite remote sensing-
dc.typeArticle-
dc.identifier.doi10.1098/rstb.2017.0409-
dc.citation.journaltitlePhilosophical Transactions of the Royal Society B: Biological Sciences-
dc.identifier.wosid000446692700015-
dc.identifier.scopusid2-s2.0-85054776898-
dc.citation.number1760-
dc.citation.startpage20170409-
dc.citation.volume373-
dc.description.isOpenAccessN-
dc.contributor.affiliatedAuthorRyu, Youngryel-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.subject.keywordPlusGROSS PRIMARY PRODUCTION-
dc.subject.keywordPlusCARBON UPTAKE-
dc.subject.keywordPlusCHLOROPHYLL FLUORESCENCE-
dc.subject.keywordPlusINTERANNUAL VARIABILITY-
dc.subject.keywordPlusSEMIARID ECOSYSTEMS-
dc.subject.keywordPlusCO2-
dc.subject.keywordPlusLAND-
dc.subject.keywordPlusEFFICIENCY-
dc.subject.keywordPlusCLIMATE-
dc.subject.keywordPlusMODEL-
dc.subject.keywordAuthorENSO-
dc.subject.keywordAuthorgross primary productivity-
dc.subject.keywordAuthorsolar-induced fluorescence-
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  • College of Agriculture and Life Sciences
  • Department of Landscape Architecture and Rural System Engineering
Research Area Crop, Forest Carbon, Sensing Network, Water Cycles

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