Leaf aging of Amazonian canopy trees as revealed by spectral and physiochemical measurements

Chavana-Bryant, Cecilia; Malhi, Yadvinder; Wu, Jin; Asner, Gregory P.; Anastasiou, Athanasios; Enquist, Brian J.; Cosio Caravasi, Eric G.; Doughty, Christopher E.; Saleska, Scott R.; Martin, Roberta E.; Gerard, France F.. 2017 Leaf aging of Amazonian canopy trees as revealed by spectral and physiochemical measurements [in special issue: Featured papers on ‘Tropical plants and ecosystem function’] New Phytologist, 214 (3). 1049-1063. https://doi.org/10.1111/nph.13853

Full text not available from this repository.

Abstract/Summary

• Leaf aging is a fundamental driver of changes in leaf traits, thereby regulating ecosystem processes and remotely sensed canopy dynamics. • We explore leaf reflectance as a tool to monitor leaf age and develop a spectra-based partial least squares regression (PLSR) model to predict age using data from a phenological study of 1099 leaves from 12 lowland Amazonian canopy trees in southern Peru. • Results demonstrated monotonic decreases in leaf water (LWC) and phosphorus (Pmass) contents and an increase in leaf mass per unit area (LMA) with age across trees; leaf nitrogen (Nmass) and carbon (Cmass) contents showed monotonic but tree-specific age responses. We observed large age-related variation in leaf spectra across trees. A spectra-based model was more accurate in predicting leaf age (R2 = 0.86; percent root mean square error (%RMSE) = 33) compared with trait-based models using single (R2 = 0.07–0.73; %RMSE = 7–38) and multiple (R2 = 0.76; %RMSE = 28) predictors. Spectra- and trait-based models established a physiochemical basis for the spectral age model. Vegetation indices (VIs) including the normalized difference vegetation index (NDVI), enhanced vegetation index 2 (EVI2), normalized difference water index (NDWI) and photosynthetic reflectance index (PRI) were all age-dependent. • This study highlights the importance of leaf age as a mediator of leaf traits, provides evidence of age-related leaf reflectance changes that have important impacts on VIs used to monitor canopy dynamics and productivity and proposes a new approach to predicting and monitoring leaf age with important implications for remote sensing.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.1111/nph.13853
UKCEH and CEH Sections/Science Areas:	Reynard
ISSN:	0028-646X
Additional Keywords:	canopy trees, hyperspectral reflectance, leaf age, leaf traits, leaf lifecycle, leaf morphological traits, PLSR, tropical forests, vegetation indices, leaf spectral properties, phenology
NORA Subject Terms:	Earth Sciences Ecology and Environment
Date made live:	15 Feb 2016 13:01 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/511213

Actions (login required)

View Item

Document Downloads

More statistics for this item...