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dc.contributor.authorWu, Jin-
dc.contributor.authorChavana-Bryant, Cecilia-
dc.contributor.authorProhaska, Neill-
dc.contributor.authorSerbin, Shawn P.-
dc.contributor.authorGuan, Kaiyu-
dc.contributor.authorAlbert, Loren P.-
dc.contributor.authorYang, Xi-
dc.contributor.authorVan Leeuwen, Willem Jan Dirk-
dc.contributor.authorGarnello, Anthony John-
dc.contributor.authorMartins, Giordane Augusto-
dc.contributor.authorMalhi, Yadvinder Singh-
dc.contributor.authorGerard, France F.-
dc.contributor.authorOliviera, Raimundo Cosme-
dc.contributor.authorSaleska, Scott Reid-
dc.date.accessioned2020-05-18T18:29:14Z-
dc.date.available2020-05-18T18:29:14Z-
dc.date.issued2017-
dc.identifier.urihttps://repositorio.inpa.gov.br/handle/1/15739-
dc.description.abstractLeaf age structures the phenology and development of plants, as well as the evolution of leaf traits over life histories. However, a general method for efficiently estimating leaf age across forests and canopy environments is lacking. Here, we explored the potential for a statistical model, previously developed for Peruvian sunlit leaves, to consistently predict leaf ages from leaf reflectance spectra across two contrasting forests in Peru and Brazil and across diverse canopy environments. The model performed well for independent Brazilian sunlit and shade canopy leaves (R2 = 0.75–0.78), suggesting that canopy leaves (and their associated spectra) follow constrained developmental trajectories even in contrasting forests. The model did not perform as well for mid-canopy and understory leaves (R2 = 0.27–0.29), because leaves in different environments have distinct traits and trait developmental trajectories. When we accounted for distinct environment–trait linkages – either by explicitly including traits and environments in the model, or, even better, by re-parameterizing the spectra-only model to implicitly capture distinct trait-trajectories in different environments – we achieved a more general model that well-predicted leaf age across forests and environments (R2 = 0.79). Fundamental rules, linked to leaf environments, constrain the development of leaf traits and allow for general prediction of leaf age from spectra across species, sites and canopy environments. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trusten
dc.language.isoenpt_BR
dc.relation.ispartofVolume 214, Número 3, Pags. 1033-1048pt_BR
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Brazil*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/br/*
dc.subjectCanopy Reflectanceen
dc.subjectConvergenceen
dc.subjectLeafen
dc.subjectLeast Squares Methoden
dc.subjectLife History Traiten
dc.subjectPhenologyen
dc.subjectTropical Foresten
dc.subjectUnderstoryen
dc.subjectVegetation Indexen
dc.subjectWater Contenten
dc.subjectPeruen
dc.subjectAnatomy And Histologyen
dc.subjectForesten
dc.subjectGeographyen
dc.subjectGrowth, Development And Agingen
dc.subjectLighten
dc.subjectPeruen
dc.subjectPhysiologyen
dc.subjectPlant Leafen
dc.subjectQuantitative Traiten
dc.subjectRegression Analysisen
dc.subjectTheoretical Modelen
dc.subjectTreeen
dc.subjectTropic Climateen
dc.subjectForestsen
dc.subjectGeographyen
dc.subjectLighten
dc.subjectModels, Theoreticalen
dc.subjectPeruen
dc.subjectPlant Leavesen
dc.subjectQuantitative Trait, Heritableen
dc.subjectRegression Analysisen
dc.subjectTreesen
dc.subjectTropical Climateen
dc.titleConvergence in relationships between leaf traits, spectra and age across diverse canopy environments and two contrasting tropical forestsen
dc.typeArtigopt_BR
dc.identifier.doi10.1111/nph.14051-
dc.publisher.journalNew Phytologistpt_BR
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