Literature DB >> 31245836

Leaf reflectance spectroscopy captures variation in carboxylation capacity across species, canopy environment and leaf age in lowland moist tropical forests.

Jin Wu1, Alistair Rogers1, Loren P Albert2,3, Kim Ely1, Neill Prohaska3, Brett T Wolfe4, Raimundo Cosme Oliveira5, Scott R Saleska3, Shawn P Serbin1.   

Abstract

Understanding the pronounced seasonal and spatial variation in leaf carboxylation capacity (Vc,max ) is critical for determining terrestrial carbon cycling in tropical forests. However, an efficient and scalable approach for predicting Vc,max is still lacking. Here the ability of leaf spectroscopy for rapid estimation of Vc,max was tested. Vc,max was estimated using traditional gas exchange methods, and measured reflectance spectra and leaf age in leaves sampled from tropical forests in Panama and Brazil. These data were used to build a model to predict Vc,max from leaf spectra. The results demonstrated that leaf spectroscopy accurately predicts Vc,max of mature leaves in Panamanian tropical forests (R2  = 0.90). However, this single-age model required recalibration when applied to broader leaf demographic classes (i.e. immature leaves). Combined use of spectroscopy models for Vc,max and leaf age enabled construction of the Vc,max -age relationship solely from leaf spectra, which agreed with field observations. This suggests that the spectroscopy technique can capture the seasonal variability in Vc,max , assuming sufficient sampling across diverse species, leaf ages and canopy environments. This finding will aid development of remote sensing approaches that can be used to characterize Vc,max in moist tropical forests and enable an efficient means to parameterize and evaluate terrestrial biosphere models.
© 2019 The Authors. New Phytologist © 2019 New Phytologist Trust.

Entities:  

Keywords:  Earth system models; gas exchange; plant functional traits; seasonality; vegetation spectroscopy

Mesh:

Year:  2019        PMID: 31245836     DOI: 10.1111/nph.16029

Source DB:  PubMed          Journal:  New Phytol        ISSN: 0028-646X            Impact factor:   10.151


  5 in total

Review 1.  Advances in field-based high-throughput photosynthetic phenotyping.

Authors:  Peng Fu; Christopher M Montes; Matthew H Siebers; Nuria Gomez-Casanovas; Justin M McGrath; Elizabeth A Ainsworth; Carl J Bernacchi
Journal:  J Exp Bot       Date:  2022-05-23       Impact factor: 7.298

2.  Seawater exposure causes hydraulic damage in dying Sitka-spruce trees.

Authors:  Hongxia Zhang; Xinrong Li; Wenzhi Wang; Alexandria L Pivovaroff; Weibin Li; Peipei Zhang; Nicholas D Ward; Allison Myers-Pigg; Henry D Adams; Riley Leff; Anzhi Wang; Fenghui Yuan; Jiabing Wu; Steve Yabusaki; Scott Waichler; Vanessa L Bailey; Dexin Guan; Nate G McDowell
Journal:  Plant Physiol       Date:  2021-10-05       Impact factor: 8.005

3.  Automated hyperspectral vegetation index derivation using a hyperparameter optimisation framework for high-throughput plant phenotyping.

Authors:  Joshua C O Koh; Bikram P Banerjee; German Spangenberg; Surya Kant
Journal:  New Phytol       Date:  2022-01-20       Impact factor: 10.323

Review 4.  The Spectral Species Concept in Living Color.

Authors:  Duccio Rocchini; Maria J Santos; Susan L Ustin; Jean-Baptiste Féret; Gregory P Asner; Carl Beierkuhnlein; Michele Dalponte; Hannes Feilhauer; Giles M Foody; Gary N Geller; Thomas W Gillespie; Kate S He; David Kleijn; Pedro J Leitão; Marco Malavasi; Vítězslav Moudrý; Jana Müllerová; Harini Nagendra; Signe Normand; Carlo Ricotta; Michael E Schaepman; Sebastian Schmidtlein; Andrew K Skidmore; Petra Šímová; Michele Torresani; Philip A Townsend; Woody Turner; Petteri Vihervaara; Martin Wegmann; Jonathan Lenoir
Journal:  J Geophys Res Biogeosci       Date:  2022-09-02       Impact factor: 4.432

Review 5.  Hyperspectral reflectance-based phenotyping for quantitative genetics in crops: Progress and challenges.

Authors:  Marcin Grzybowski; Nuwan K Wijewardane; Abbas Atefi; Yufeng Ge; James C Schnable
Journal:  Plant Commun       Date:  2021-05-27
  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.