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Erratum published on 16 June 2016, see Remote Sens. 2016, 8(6), 475.
Open AccessArticle

Associations of Leaf Spectra with Genetic and Phylogenetic Variation in Oaks: Prospects for Remote Detection of Biodiversity

1
Department of Ecology, Evolution and Behavior, University of Minnesota, Saint Paul, MN 55108, USA
2
Department of Forest and Wildlife Ecology, University of Wisconsin, Madison, WI 53706, USA
3
Environmental & Climate Sciences Department, Brookhaven National Laboratory, Upton, NY 11973, USA
4
Department of Biology, Saint Olaf College, Northfield, MN 55057, USA
5
Departamento de Ingenieria en Ambiente y Desarrollo, University of Zamorano, Zamorano, Honduras
*
Authors to whom correspondence should be addressed.
Academic Editors: Susan L. Ustin, Parth Sarathi Roy and Prasad S. Thenkabail
Remote Sens. 2016, 8(3), 221; https://doi.org/10.3390/rs8030221
Received: 13 November 2015 / Revised: 1 February 2016 / Accepted: 22 February 2016 / Published: 9 March 2016
(This article belongs to the Special Issue Remote Sensing of Biodiversity)
Species and phylogenetic lineages have evolved to differ in the way that they acquire and deploy resources, with consequences for their physiological, chemical and structural attributes, many of which can be detected using spectral reflectance form leaves. Recent technological advances for assessing optical properties of plants offer opportunities to detect functional traits of organisms and differentiate levels of biological organization across the tree of life. Here, we connect leaf-level full range spectral data (400–2400 nm) of leaves to the hierarchical organization of plant diversity within the oak genus (Quercus) using field and greenhouse experiments in which environmental factors and plant age are controlled. We show that spectral data significantly differentiate populations within a species and that spectral similarity is significantly associated with phylogenetic similarity among species. We further show that hyperspectral information allows more accurate classification of taxa than spectrally-derived traits, which by definition are of lower dimensionality. Finally, model accuracy increases at higher levels in the hierarchical organization of plant diversity, such that we are able to better distinguish clades than species or populations. This pattern supports an evolutionary explanation for the degree of optical differentiation among plants and demonstrates potential for remote detection of genetic and phylogenetic diversity. View Full-Text
Keywords: hyperspectral data; leaf functional traits; hierarchical organization of plant diversity; evolution; tree of life; populations; genetic variation; PLS-DA; phylogenetic signal; optical classification hyperspectral data; leaf functional traits; hierarchical organization of plant diversity; evolution; tree of life; populations; genetic variation; PLS-DA; phylogenetic signal; optical classification
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MDPI and ACS Style

Cavender-Bares, J.; Meireles, J.E.; Couture, J.J.; Kaproth, M.A; Kingdon, C.C.; Singh, A.; Serbin, S.P.; Center, A.; Zuniga, E.; Pilz, G.; Townsend, P.A. Associations of Leaf Spectra with Genetic and Phylogenetic Variation in Oaks: Prospects for Remote Detection of Biodiversity. Remote Sens. 2016, 8, 221. https://doi.org/10.3390/rs8030221

AMA Style

Cavender-Bares J, Meireles JE, Couture JJ, Kaproth MA, Kingdon CC, Singh A, Serbin SP, Center A, Zuniga E, Pilz G, Townsend PA. Associations of Leaf Spectra with Genetic and Phylogenetic Variation in Oaks: Prospects for Remote Detection of Biodiversity. Remote Sensing. 2016; 8(3):221. https://doi.org/10.3390/rs8030221

Chicago/Turabian Style

Cavender-Bares, Jeannine; Meireles, Jose E.; Couture, John J.; Kaproth, Matthew A; Kingdon, Clayton C.; Singh, Aditya; Serbin, Shawn P.; Center, Alyson; Zuniga, Esau; Pilz, George; Townsend, Philip A. 2016. "Associations of Leaf Spectra with Genetic and Phylogenetic Variation in Oaks: Prospects for Remote Detection of Biodiversity" Remote Sens. 8, no. 3: 221. https://doi.org/10.3390/rs8030221

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