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dc.contributor.authorAlves, Eliane Gomes-
dc.contributor.authorTóta, Júlio-
dc.contributor.authorTurnipseed, Andrew A.-
dc.contributor.authorGuenther, Alex B.-
dc.contributor.authorVega Bustillos, José Oscar W.-
dc.contributor.authorSantana, Raoni Aquino Silva de-
dc.contributor.authorCirino, Glauber G.-
dc.contributor.authorTavares, Julia Valentim-
dc.contributor.authorLopes, Aline Pontes-
dc.contributor.authorNelson, Bruce Walker-
dc.contributor.authorSouza, Rodrigo Augusto Ferreira de-
dc.contributor.authorGu, Dasa-
dc.contributor.authorStavrakou, Trissevgeni-
dc.contributor.authorAdams, David K.-
dc.contributor.authorWu, Jin-
dc.contributor.authorSaleska, Scott Reid-
dc.contributor.authorManzi, Antônio Ocimar-
dc.date.accessioned2020-05-07T13:47:18Z-
dc.date.available2020-05-07T13:47:18Z-
dc.date.issued2018-
dc.identifier.urihttps://repositorio.inpa.gov.br/handle/1/14903-
dc.description.abstractIsoprene fluxes vary seasonally with changes in environmental factors (e.g., solar radiation and temperature) and biological factors (e.g., leaf phenology). However, our understanding of the seasonal patterns of isoprene fluxes and the associated mechanistic controls is still limited, especially in Amazonian evergreen forests. In this paper, we aim to connect intensive, field-based measurements of canopy isoprene flux over a central Amazonian evergreen forest site with meteorological observations and with tower-mounted camera leaf phenology to improve our understanding of patterns and causes of isoprene flux seasonality. Our results demonstrate that the highest isoprene emissions are observed during the dry and dry-to-wet transition seasons, whereas the lowest emissions were found during the wet-to-dry transition season. Our results also indicate that light and temperature cannot totally explain isoprene flux seasonality. Instead, the camera-derived leaf area index (LAI) of recently mature leaf age class (e.g., leaf ages of 3-5 months) exhibits the highest correlation with observed isoprene flux seasonality (R2 = 0.59, p < 0.05). Attempting to better represent leaf phenology in the Model of Emissions of Gases and Aerosols from Nature (MEGAN 2.1), we improved the leaf age algorithm by utilizing results from the camera-derived leaf phenology that provided LAI categorized into three different leaf ages. The model results show that the observations of age-dependent isoprene emission capacity, in conjunction with camera-derived leaf age demography, significantly improved simulations in terms of seasonal variations in isoprene fluxes (R2 = 0.52, p < 0.05). This study highlights the importance of accounting for differences in isoprene emission capacity across canopy leaf age classes and identifying forest adaptive mechanisms that underlie seasonal variation in isoprene emissions in Amazonia. © 2018 Author(s).en
dc.language.isoenpt_BR
dc.relation.ispartofVolume 15, Número 13, Pags. 4019-4032pt_BR
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Brazil*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/br/*
dc.subjectAge Classen
dc.subjectAlgorithmen
dc.subjectEmissionen
dc.subjectEnvironmental Factoren
dc.subjectEvergreen Foresten
dc.subjectFlux Measurementen
dc.subjectForest Canopyen
dc.subjectIsopreneen
dc.subjectLeafen
dc.subjectLeaf Area Indexen
dc.subjectPhenologyen
dc.subjectSeasonal Variationen
dc.subjectSeasonalityen
dc.subjectAmazoniaen
dc.titleLeaf phenology as one important driver of seasonal changes in isoprene emissions in central Amazoniaen
dc.typeArtigopt_BR
dc.identifier.doi10.5194/bg-15-4019-2018-
dc.publisher.journalBiogeosciencespt_BR
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