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hal.structure.identifierLaboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] [LSCE]
dc.contributor.authorYANG, Hui
hal.structure.identifierLaboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] [LSCE]
dc.contributor.authorCIAIS, Philippe
hal.structure.identifierInteractions Sol Plante Atmosphère [UMR ISPA]
dc.contributor.authorWIGNERON, Jean-Pierre
hal.structure.identifierEvolution et Diversité Biologique [EDB]
dc.contributor.authorCHAVE, Jérôme
hal.structure.identifierGamma Remote Sensing Research and Consulting AG
dc.contributor.authorCARTUS, Oliver
hal.structure.identifierNational Sun Yat-sen University [NSYSU]
dc.contributor.authorCHEN, Xiuzhi
hal.structure.identifierSouthwest Forestry University [SWFU]
dc.contributor.authorFAN, Lei
hal.structure.identifierLaboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] [LSCE]
dc.contributor.authorGREEN, Julia
hal.structure.identifierCommonwealth Scientific and Industrial Research Organisation [Australia] [CSIRO]
dc.contributor.authorHUANG, Yuanyuan
hal.structure.identifierCentre national de recherches météorologiques [CNRM]
dc.contributor.authorJOETZJER, Emilie
hal.structure.identifierAberystwyth University
dc.contributor.authorKAY, Heather
hal.structure.identifierMathématiques et Informatique Appliquées [MIA Paris-Saclay]
dc.contributor.authorMAKOWSKI, David
hal.structure.identifierLaboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] [LSCE]
hal.structure.identifierModélisation des Surfaces et Interfaces Continentales [MOSAIC]
dc.contributor.authorMAIGNAN, Fabienne
hal.structure.identifierGamma Remote Sensing Research and Consulting AG
dc.contributor.authorSANTORO, Maurizio
hal.structure.identifierEvolution et Diversité Biologique [EDB]
dc.contributor.authorTAO, Shengli
hal.structure.identifierLaboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] [LSCE]
dc.contributor.authorLIU, Liyang
hal.structure.identifierLaboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] [LSCE]
hal.structure.identifierNational Sun Yat-sen University [NSYSU]
dc.contributor.authorYAO, Yitong
dc.date.accessioned2024-04-08T11:46:56Z
dc.date.available2024-04-08T11:46:56Z
dc.date.issued2022-06-28
dc.identifier.issn0027-8424
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/195256
dc.description.abstractEnThe 2015/16 El Niño brought severe drought and record-breaking temperatures in the tropics. Here, using satellite-based L-band microwave vegetation optical depth, we mapped changes of above-ground biomass (AGB) during the drought and in subsequent years up to 2019. Over more than 60% of drought-affected intact forests, AGB reduced during the drought, except in the wettest part of the central Amazon, where it declined 1 y later. By the end of 2019, only 40% of AGB reduced intact forests had fully recovered to the predrought level. Using random-forest models, we found that the magnitude of AGB losses during the drought was mainly associated with regionally distinct patterns of soil water deficits and soil clay content. For the AGB recovery, we found strong influences of AGB losses during the drought and of γ . γ is a parameter related to canopy structure and is defined as the ratio of two relative height (RH) metrics of Geoscience Laser Altimeter System (GLAS) waveform data—RH25 (25% energy return height) and RH100 (100% energy return height; i.e., top canopy height). A high γ may reflect forests with a tall understory, thick and closed canopy, and/or without degradation. Such forests with a high γ ( γ ≥ 0.3) appear to have a stronger capacity to recover than low- γ ones. Our results highlight the importance of forest structure when predicting the consequences of future drought stress in the tropics.
dc.language.isoen
dc.publisherNational Academy of Sciences
dc.rights.urihttp://creativecommons.org/licenses/by/
dc.subject.entropical forest
dc.subject.endrought
dc.subject.enrecovery
dc.subject.enforest structure
dc.title.enClimatic and biotic factors influencing regional declines and recovery of tropical forest biomass from the 2015/16 El Niño
dc.typeArticle de revue
dc.identifier.doi10.1073/pnas.2101388119
dc.subject.halSciences de l'environnement/Milieux et Changements globaux
dc.subject.halStatistiques [stat]/Machine Learning [stat.ML]
bordeaux.journalProceedings of the National Academy of Sciences of the United States of America
bordeaux.page108301
bordeaux.volume119
bordeaux.hal.laboratoriesInteractions Soil Plant Atmosphere (ISPA) - UMR 1391*
bordeaux.issue26
bordeaux.institutionBordeaux Sciences Agro
bordeaux.institutionINRAE
bordeaux.peerReviewedoui
hal.identifierhal-03702327
hal.version1
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-03702327v1
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