Journal
NEW PHYTOLOGIST
Volume 214, Issue 3, Pages 1049-1063Publisher
WILEY
DOI: 10.1111/nph.13853
Keywords
canopy trees; leaf age; leaf lifecycle; leaf spectral properties; leaf traits; phenology; tropical forests; vegetation indices (VIs)
Categories
Funding
- NERC TROBIT project [NE/D005469/1]
- Centre for Ecology & Hydrology (CEH)
- Jackson Foundation
- ERC Advanced Investigator Grant GEM-TRAIT [321131]
- NERC [ceh020009, NE/J023418/1, ceh020001, NE/D01185X/1, NE/D005469/1] Funding Source: UKRI
- Natural Environment Research Council [ceh020009, NE/D005469/1, ceh020001, NE/J023418/1, NE/D01185X/1] Funding Source: researchfish
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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 (P-mass) contents and an increase in leaf mass per unit area (LMA) with age across trees; leaf nitrogen (N-mass) and carbon (C-mass) 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 (R-2 = 0.86; percent root mean square error (% RMSE) = 33) compared with trait-based models using single (R-2 = 0.07-0.73; % RMSE = 7-38) and multiple (R-2 = 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.
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