Use este identificador para citar ou linkar para este item: https://repositorio.inpa.gov.br/handle/1/15739
Título: Convergence in relationships between leaf traits, spectra and age across diverse canopy environments and two contrasting tropical forests
Autor: Wu, Jin
Chavana-Bryant, Cecilia
Prohaska, Neill
Serbin, Shawn P.
Guan, Kaiyu
Albert, Loren P.
Yang, Xi
Van Leeuwen, Willem Jan Dirk
Garnello, Anthony John
Martins, Giordane Augusto
Malhi, Yadvinder Singh
Gerard, France F.
Oliviera, Raimundo Cosme
Saleska, Scott Reid
Palavras-chave: Canopy Reflectance
Convergence
Leaf
Least Squares Method
Life History Trait
Phenology
Tropical Forest
Understory
Vegetation Index
Water Content
Peru
Anatomy And Histology
Forest
Geography
Growth, Development And Aging
Light
Peru
Physiology
Plant Leaf
Quantitative Trait
Regression Analysis
Theoretical Model
Tree
Tropic Climate
Forests
Geography
Light
Models, Theoretical
Peru
Plant Leaves
Quantitative Trait, Heritable
Regression Analysis
Trees
Tropical Climate
Data do documento: 2017
Revista: New Phytologist
É parte de: Volume 214, Número 3, Pags. 1033-1048
Abstract: 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. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust
DOI: 10.1111/nph.14051
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