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Leafing patterns and drivers across seasonally dry tropical communities

dc.contributor.authorAlberton, Bruna [UNESP]
dc.contributor.authorTorres, Ricardo da Silva
dc.contributor.authorSilva, Thiago Sanna Freire
dc.contributor.authorda Rocha, Humberto R.
dc.contributor.authorMoura, Magna S.B.
dc.contributor.authorMorellato, Leonor Patrícia Cerdeira [UNESP]
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.contributor.institutionUniversidade Estadual de Campinas (UNICAMP)
dc.contributor.institutionUniversity of Stirling
dc.contributor.institutionUniversidade de S'o Paulo
dc.contributor.institutionEmpresa Brasileira de Pesquisa Agropecuária (EMBRAPA)
dc.date.accessioned2020-12-12T02:27:25Z
dc.date.available2020-12-12T02:27:25Z
dc.date.issued2019-10-01
dc.description.abstractInvestigating the timing of key phenological events across environments with variable seasonality is crucial to understand the drivers of ecosystem dynamics. Leaf production in the tropics is mainly constrained by water and light availability. Identifying the factors regulating leaf phenology patterns allows efficiently forecasting of climate change impacts. We conducted a novel phenological monitoring study across four Neotropical vegetation sites using leaf phenology time series obtained from digital repeated photographs (phenocameras). Seasonality differed among sites, from very seasonally dry climate in the caatinga dry scrubland with an eight-month long dry season to the less restrictive Cerrado vegetation with a six-month dry season. To unravel the main drivers of leaf phenology and understand how they influence seasonal dynamics (represented by the green color channel (Gcc) vegetation index), we applied Generalized Additive Mixed Models (GAMMs) to estimate the growing seasons, using water deficit and day length as covariates. Our results indicated that plant-water relationships are more important in the caatinga, while light (measured as day-length) was more relevant in explaining leafing patterns in Cerrado communities. Leafing behaviors and predictor-response relationships (distinct smooth functions) were more variable at the less seasonal Cerrado sites, suggesting that different life-forms (grasses, herbs, shrubs, and trees) are capable of overcoming drought through specific phenological strategies and associated functional traits, such as deep root systems in trees.en
dc.description.affiliationLaborat'rio de Fenologia Instituto de Bioci'ncias Universidade Estadual Paulista (Unesp)
dc.description.affiliationInstitute of Computing University of Campinas
dc.description.affiliationBiological and Environmental Sciences University of Stirling
dc.description.affiliationInstituto de Astronomia Geof'sica e Ci'ncias Atmosf'ricas Universidade de S'o Paulo
dc.description.affiliationEmpresa Brasileira de Pesquisa Agropecu'ria Embrapa Semi'rido
dc.description.affiliationUnespLaborat'rio de Fenologia Instituto de Bioci'ncias Universidade Estadual Paulista (Unesp)
dc.identifierhttp://dx.doi.org/10.3390/rs11192267
dc.identifier.citationRemote Sensing, v. 11, n. 19, 2019.
dc.identifier.doi10.3390/rs11192267
dc.identifier.issn2072-4292
dc.identifier.scopus2-s2.0-85073408575
dc.identifier.urihttp://hdl.handle.net/11449/201233
dc.language.isoeng
dc.relation.ispartofRemote Sensing
dc.sourceScopus
dc.subjectCaatinga
dc.subjectCerrado
dc.subjectClimate drivers
dc.subjectDeciduousness
dc.subjectGreenness
dc.subjectNear-surface remote phenology
dc.subjectSavanna
dc.subjectSeasonality
dc.subjectTime series
dc.subjectVegetative phenology
dc.titleLeafing patterns and drivers across seasonally dry tropical communitiesen
dc.typeArtigopt
dspace.entity.typePublication
unesp.author.orcid0000-0003-4835-8389[1]
unesp.author.orcid0000-0001-9772-263X[2]
unesp.author.orcid0000-0001-8174-0489[3]
unesp.author.orcid0000-0001-5265-8988[6]
unesp.campusUniversidade Estadual Paulista (UNESP), Instituto de Biociências, Rio Claropt
unesp.departmentBotânica - IBpt

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