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

Journal Article · · Remote Sensing
DOI:https://doi.org/10.3390/rs8030221· OSTI ID:1260157
 [1];  [1];  [2];  [1];  [2];  [2];  [3];  [4];  [5];  [5];  [2]
  1. Univ. of Minnesota, Minneapolis, MN (United States)
  2. Univ. of Wisconsin, Madison, WI (United States)
  3. Univ. of Wisconsin, Madison, WI (United States); Brookhaven National Lab. (BNL), Upton, NY (United States)
  4. Univ. of Minnesota, Minneapolis, MN (United States); Saint Olaf College, Northfield, MN (United States)
  5. Univ. of Zamorano (Honduras)

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. 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. Furthermore, we 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.

Research Organization:
Brookhaven National Laboratory (BNL), Upton, NY (United States)
Sponsoring Organization:
USDOE Office of Science (SC), Basic Energy Sciences (BES)
Grant/Contract Number:
SC00112704
OSTI ID:
1260157
Report Number(s):
BNL-112303-2016-JA; R&D Project: 21087; YN0100000
Journal Information:
Remote Sensing, Vol. 8, Issue 3; ISSN 2072-4292
Publisher:
MDPICopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 89 works
Citation information provided by
Web of Science

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Plant spectral diversity integrates functional and phylogenetic components of biodiversity and predicts ecosystem function journal May 2018
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Consequences of biodiversity shift across phylogenetic scales for aspen and willow growth, survival, and herbivory journal March 2019
Diversification, adaptation, and community assembly of the American oaks ( Quercus ), a model clade for integrating ecology and evolution journal September 2018
Demystifying dominant species journal May 2019
Leaf Canopy Layers Affect Spectral Reflectance in Silver Birch journal December 2019
Hyperspectral Measurements Enable Pre-Symptomatic Detection and Differentiation of Contrasting Physiological Effects of Late Blight and Early Blight in Potato journal January 2020
The Effect of Leaf Stacking on Leaf Reflectance and Vegetation Indices Measured by Contact Probe during the Season journal May 2017
The CCB-ID approach to tree species mapping with airborne imaging spectroscopy journal January 2018
The CCB-ID approach to tree species mapping with airborne imaging spectroscopy posted_content June 2018
Partitioning plant spectral diversity into alpha and beta components text January 2020
Plant spectral diversity integrates functional and phylogenetic components of biodiversity and predicts ecosystem function text January 2018
Intraspecific drought tolerance of Betula pendula genotypes: an evaluation using leaf turgor loss in a botanical collection journal November 2020
Spatial functional data modeling of plant reflectances journal September 2022