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Article: Convergence in relationships between leaf traits, spectra and age across diverse canopy environments and two contrasting tropical forests

TitleConvergence in relationships between leaf traits, spectra and age across diverse canopy environments and two contrasting tropical forests
Authors
Keywordsspectroscopy
leaf mass per area (LMA)
leaf water content (LWC)
partial least-squares regression (PLSR)
understory
vegetation indices
vertical canopy profiles
Issue Date2017
Citation
New Phytologist, 2017, v. 214, n. 3, p. 1033-1048 How to Cite?
Abstract© 2016 The Authors. New Phytologist © 2016 New Phytologist Trust 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.
Persistent Identifierhttp://hdl.handle.net/10722/267047
ISSN
2023 Impact Factor: 8.3
2023 SCImago Journal Rankings: 3.007
ISI Accession Number ID

 

DC FieldValueLanguage
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 J.D.-
dc.contributor.authorGarnello, Anthony John-
dc.contributor.authorMartins, Giordane-
dc.contributor.authorMalhi, Yadvinder-
dc.contributor.authorGerard, France-
dc.contributor.authorOliviera, Raimundo Cosme-
dc.contributor.authorSaleska, Scott R.-
dc.date.accessioned2019-01-31T07:20:21Z-
dc.date.available2019-01-31T07:20:21Z-
dc.date.issued2017-
dc.identifier.citationNew Phytologist, 2017, v. 214, n. 3, p. 1033-1048-
dc.identifier.issn0028-646X-
dc.identifier.urihttp://hdl.handle.net/10722/267047-
dc.description.abstract© 2016 The Authors. New Phytologist © 2016 New Phytologist Trust 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.-
dc.languageeng-
dc.relation.ispartofNew Phytologist-
dc.subjectspectroscopy-
dc.subjectleaf mass per area (LMA)-
dc.subjectleaf water content (LWC)-
dc.subjectpartial least-squares regression (PLSR)-
dc.subjectunderstory-
dc.subjectvegetation indices-
dc.subjectvertical canopy profiles-
dc.titleConvergence in relationships between leaf traits, spectra and age across diverse canopy environments and two contrasting tropical forests-
dc.typeArticle-
dc.description.naturelink_to_OA_fulltext-
dc.identifier.doi10.1111/nph.14051-
dc.identifier.pmid27381054-
dc.identifier.scopuseid_2-s2.0-84978972818-
dc.identifier.volume214-
dc.identifier.issue3-
dc.identifier.spage1033-
dc.identifier.epage1048-
dc.identifier.eissn1469-8137-
dc.identifier.isiWOS:000402403900015-
dc.identifier.issnl0028-646X-

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