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

Jeannine Cavender-Bares,Aditya Singh,Matthew Kaproth,Esau Zuniga,Philip Townsend,Jose Meireles,Alyson Center,John Couture,Shawn Serbin,George Pilz,Clayton Kingdon

doi:10.3390/rs8030221

Abstract

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.

Highlights

Biodiversity loss is a major threat to our planetary life support systems [1,2,3]
In the first experimental system, we show that the four populations of Q. oleoides, which exhibit differentiation based on molecular data (Figure 2A), demonstrate considerable variation across the major spectral regions (Figure 2B–F)
The partial least squares discriminant analysis (PLS-DA) approaches used in this study show great potential to distinguish populations, species and clades within a single genus

Summary

Introduction

Biodiversity loss is a major threat to our planetary life support systems [1,2,3]. Gaps in documenting and monitoring biodiversity are largest in areas where biodiversity is greatest and where existing biodiversity may be most threatened [4], highlighting the need for globally consistent and continuous approaches for assessing changes in biodiversity [5]. Recent and proposed airborne and satellite platforms equipped with hyperspectral imaging technology [5,9] increase the urgency to understand how we can use these tools effectively to monitor biological variation globally across spatial, temporal and biological scales. Recent and proposed airborne and satellite platforms equipped with consequences for their spectral properties, giventhethat the chemical, morphological, physiological hyperspectral imaging technology [5,9] increase urgency to understand how we can use these and structural properties of leaves influence theglobally way electromagnetic energy is reflected, tools effectively to monitor biological variation across spatial, temporal and biological scales.transmitted speciesAand lineages have evolved traits different functional mechanisms to acquire, harness and absorbedPlant [14,15,16,17,18,19]

Methods

Results

Discussion

Conclusion