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Registro Completo |
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Biblioteca(s): |
Embrapa Amazônia Oriental. |
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Data corrente: |
06/10/2017 |
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Data da última atualização: |
20/05/2022 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
WU, J.; CHAVANA-BRYANT, C.; PROHASKA, N.; SERBIN, S. P.; GUAN, K.; ALBERT, L. P.; YANG, X.; LEEUWEN, W. J. D. van; GARNELLO, A. J.; MARTINS, G.; MALHI, Y.; GERARD, F.; OLIVEIRA JUNIOR, R. C. de; SALESKA, S. R. |
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Afiliação: |
Jin Wu, University of Arizona / Brookhaven National Lab; Cecilia Chavana-Bryant, University of Oxford; Neill Prohaska, University of Arizona; Shawn P. Serbin, Brookhaven National Lab; Kaiyu Guan, University of Illinois at Urbana Champaign; Loren P. Albert, University of Arizona; Xi Yang, Brown University; Willem J. D. van Leeuwen, University of Arizona; Anthony John Garnello, University of Arizona; Giordane Martins, INPA; Yadvinder Malhi, University of Oxford; France Gerard, Centre for Ecology and Hydrology (CEH); RAIMUNDO COSME DE OLIVEIRA JUNIOR, CPATU; Scott R. Saleska, University of Arizona. |
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Título: |
Convergence in relationships between leaf traits, spectra and age across diverse canopy environments and two contrasting tropical forests. |
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Ano de publicação: |
2017 |
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Fonte/Imprenta: |
New Phytologist, v. 214, n. 3, p. 1033-1048, May 2017. |
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DOI: |
10.1111/nph.14051 |
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Idioma: |
Inglês |
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Conteúdo: |
Leaf 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. |
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Palavras-Chave: |
Espectroscopia; Índices de vegetação; Massa foliar por área; Perfis de copa vertical; Teor de água. |
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Thesagro: |
Folha. |
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Categoria do assunto: |
F Plantas e Produtos de Origem Vegetal |
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Marc: |
LEADER 02559naa a2200361 a 4500
001 2076792
005 2022-05-20
008 2017 bl uuuu u00u1 u #d
024 7 $a10.1111/nph.14051$2DOI
100 1 $aWU, J.
245 $aConvergence in relationships between leaf traits, spectra and age across diverse canopy environments and two contrasting tropical forests.$h[electronic resource]
260 $c2017
520 $aLeaf 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.
650 $aFolha
653 $aEspectroscopia
653 $aÍndices de vegetação
653 $aMassa foliar por área
653 $aPerfis de copa vertical
653 $aTeor de água
700 1 $aCHAVANA-BRYANT, C.
700 1 $aPROHASKA, N.
700 1 $aSERBIN, S. P.
700 1 $aGUAN, K.
700 1 $aALBERT, L. P.
700 1 $aYANG, X.
700 1 $aLEEUWEN, W. J. D. van
700 1 $aGARNELLO, A. J.
700 1 $aMARTINS, G.
700 1 $aMALHI, Y.
700 1 $aGERARD, F.
700 1 $aOLIVEIRA JUNIOR, R. C. de
700 1 $aSALESKA, S. R.
773 $tNew Phytologist$gv. 214, n. 3, p. 1033-1048, May 2017.
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