Can Leaf Spectroscopy Predict Leaf and Forest Traits Along a Peruvian Tropical Forest Elevation Gradient?

SANTOS-ANDRADE, P. E.; DÍAZ, S.; DOUGHTY, CHRISTOPHER E.; GOLDSMITH, G. R.

Journal of Geophysical Research: Biogeosciences

Agu.Publications

Año: 2017 vol. 122 p. 2952 - 2965

Abstract High-resolution spectroscopy can be used to measure leaf chemical and structural traits. Suchleaf traits are often highly correlated to other traits, such as photosynthesis, through the leaf economicsspectrum. We measured VNIR (visible-near infrared) leaf reflectance (400?1,075 nm) of sunlit and shadedleaves in ~150 dominant species across ten, 1 ha plots along a 3,300 m elevation gradient in Peru (on 4,284individual leaves). We used partial least squares (PLS) regression to compare leaf reflectance to chemicaltraits, such as nitrogen and phosphorus, structural traits, including leaf mass per area (LMA), branch wooddensity and leaf venation, and ?higher-level? traits such as leaf photosynthetic capacity, leaf water repellency,and woody growth rates. Empirical models using leaf reflectance predicted leaf N and LMA (r2 > 30% and%RMSE < 30%), weakly predicted leaf venation, photosynthesis, and branch density (r2 between 10 and 35%and %RMSE between 10% and 65%), and did not predict leaf water repellency or woody growth rates(r2