Functional and biological diversity of foliar spectra in tree canopies throughout the Andes to Amazon region
Version of Record online: 18 JUN 2014
© 2014 The Authors. New Phytologist © 2014 New Phytologist Trust
Volume 204, Issue 1, pages 127–139, October 2014
How to Cite
Asner, G. P., Martin, R. E., Carranza-Jiménez, L., Sinca, F., Tupayachi, R., Anderson, C. B. and Martinez, P. (2014), Functional and biological diversity of foliar spectra in tree canopies throughout the Andes to Amazon region. New Phytologist, 204: 127–139. doi: 10.1111/nph.12895
- Issue online: 26 AUG 2014
- Version of Record online: 18 JUN 2014
- Manuscript Accepted: 11 MAY 2014
- Manuscript Received: 28 FEB 2014
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Fig. S1 Intra-specific and inter-specific variation in leaf reflectance and transmittance spectra in the 400–800-nm wavelength range.
Fig. S2 Ratio of intra-specific to inter-specific variation in leaf reflectance and transmittance spectra of forest sites.
Fig. S3 Standardized weighting coefficients for partial least squares regression (PLSR) for leaf chemical traits and LMA using foliar reflectance spectra.
Fig. S4 Standardized weighting coefficients for partial least squares regression (PLSR) for leaf chemical traits and LMA using foliar transmittance spectra.
Fig. S5 Effects of elevation and soil fertility on site-averaged chemical traits and LMA derived from leaf transmittance spectroscopy.
Fig. S6 Partitioning of the variance for spectranomic traits derived from leaf transmittance spectroscopy.
Table S1 Taxonomic arrangement of samples collected throughout the Andes-to-Amazon region
Table S2 List of canopy tree taxa measured in the study
Table S3 Mean and standard deviation of tree foliar chemical traits at each study site
Table S4 Analysis of variance tests comparing higher and lower fertility soils
Table S5 Relationships between modeled chemical traits and LMA (‘spectranomic traits’) and elevation for higher fertility sites
Table S6 The cumulative effect of combining leaf spectranomic traits based on transmittance in the prediction of tree canopy species using linear discriminant analysis (LDA)