NEWS & VIEWS
A M E R I C A N J O U R N A L O F B O TA N Y
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New Ideas and Directions in Botany
Harnessing plant spectra to integrate the biodiversity
sciences across biological and spatial scales1
Jeannine Cavender-Bares2,7, John A. Gamon3,4, Sarah E. Hobbie2, Michael D. Madritch5, José Eduardo Meireles2, Anna K. Schweiger2,
and Philip A. Townsend6
Plants provide the productive basis for all other life, and their diversity
is critical for the Earth’s life support systems. Many plant species are
at risk for extinction due to global change factors, including drought
stress, exotic species invasions, pathogens, land-use change combined
with altered disturbance regimes (e.g., fire), application of chemicals,
and overexploitation. One in five species within the Plant Kingdom is
thought to be threatened with extinction (Kew Royal Botanic Gardens,
2016). Given the multifaceted consequences of plant biodiversity for
providing the ecosystem services on which humans depend, including
the food we grow, the regulating services that maintain our fresh water
supply and provision the multitude of organisms we care about, plant
biodiversity is important to understand and to monitor across scales
from genetic variation at local scales to the entire plant tree of life.
Here we argue that deeper understanding and wider application of
plant electromagnetic spectra—the patterns of light absorbed, transmitted, and reflected at different wavelengths from plants—can integrate previously disparate sectors of biodiversity science and the
remote sensing community at multiple biological and spatial scales.
WHAT ARE SPECTRA?
Plants synthesize a wide variety of chemical and structural compounds to support physiological functions for survival and growth.
Leaf reflectance spectra are aggregate indicators of plant chemistry,
1
Manuscript received 14 February 2017; revision accepted 23 May 2017.
Department of Ecology, Evolution and Behavior, University of Minnesota, 1479 Gortner
Avenue, Saint Paul, Minnesota 55108 USA;
3
Center for Advanced Land Management Information Technologies (CALMIT), School of
Natural Resources, University of Nebraska-Lincoln, 3310 Holdrege Street, Lincoln,
Nebraska 68583 USA;
4
Departments of Earth & Atmospheric Sciences and Biological Sciences, 1-26 Earth
Sciences Building, University of Alberta, Edmonton, Alberta, Canada, T6G 2E3;
5
Department of Biology. Appalachian State University, 572 Rivers Street, Boone, North
Carolina 28608 USA; and
6
Department of Forest and Wildlife Ecology, University of Wisconsin-Madison, 1630
Linden Drive, Madison, Wisconsin 53706 USA
7
Author for correspondence (cavender@umn.edu)
https://doi.org/10.3732/ajb.1700061
2
physiology, water content, and both internal and external structure
(Fig. 1A). Since foliar properties influence how leaves interact with
light, many attributes of plants can be detected using spectral reflectance from leaves, plant canopies, and ecosystems. In the visible range
(VIS, 400–700 nm), light is strongly absorbed by pigments, including
chlorophyll, carotenoids, and anthocyanins. In the near-infrared
range (NIR, 700–1100 nm), energy is scattered by leaf surface characteristics, tissue components, and anatomical structures including
intercellular spaces inside the leaf. The short-wave infrared (SWIR,
1100–2500 nm) spectral region also shows relatively high reflectance,
but shows distinct absorption features for water and specific plant
biochemicals, such as lignin, cellulose, phenolics, and is influenced
by anatomical and morphological attributes of plants (Ustin et al.,
2009). These SWIR regions of plant spectra tend to be most phylogenetically conserved (McManus et al., 2016). Thermal infrared
(TIR) spectra (5–10 μm) are influenced by leaf surface temperature
and also include features associated with physiological processes.
As the spatial scale of spectral observations shifts from the leaf to
canopies, landscapes, and larger scales (Fig. 1B) using imaging spectroscopy via airborne or satellite platforms, influences of the atmosphere, sun angle, and terrain must be addressed. Leaf and canopy
spectra are generally responsive to similar fundamental properties,
given that a large proportion of what is captured in remotely sensed
vegetation data are foliar features. However, atmospheric effects, solar illumination, and the three-dimensional structure of the vegetation
introduce additional variation, as do reproductive and other nonfoliar structures, as well as canopy gaps and soils. These all add “features” to spectral measurements that confound properties of interest
that are measured at the leaf level, although in some cases they may
actually help in the assessment of biodiversity. These issues highlight
the importance of in-situ field measurements to independently validate image corrections and properly interpret remote spectra.
NEW PARADIGM
Plant spectra can be sampled at different spatial scales providing a
means to link an array of biological disciplines at different scales.
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FIGURE 1 (A) Leaves have evolved different chemical properties and structures, which influence how leaves interact with light and result in different
spectral signatures. These spectra can be used to estimate chemical and structural traits of a leaf as well as locate a species or lineage in the tree of life
to estimate biodiversity. (B) Detecting spectral diversity in plant assemblages. Images of individual and landscape level experimental plots are from
the BioDIV experiment at Cedar Creek Ecosystem Science Reserve (top left and bottom left, respectively). Heterogeneity in vegetation within assemblages can be detected with imaging spectroscopy shown schematically for the pixels of a single plot (top middle) and for a landscape of plots (bottom middle). Differences in spectra among pixels within an assemblage can be used to calculate alpha (α) spectral diversity, and among assemblages
for beta (β) spectral diversity, similar to metrics of α and β diversity for species or for phylogenetic distances between species.
Leaf reflectance itself integrates within- and between-species differences in morphology, foliar chemistry, life history strategies, and
responses to environmental variation. As a consequence, spectra
can be used to address basic questions in physiology, ecology, and
evolution as well as applied questions in agriculture and forestry.
For instance, scientists focusing on the origins and consequences of
plant biodiversity, as well as both the regulating and provisioning
services they render, can use spectral patterns to understand physiology, community assembly, and nonvisual phenotypic variation
linked to genetic and phylogenetic variation. The multiscale nature
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of spectral data reveals a growing suite of information about leaves,
whole plants, communities, and ecosystems offering new insights
into plant function and potential for integration across disciplines.
Spectral diversity is thus emerging as an important component
of biodiversity, alongside functional and genetic or phylogenetic
diversity.
PHYSIOLOGICAL AND FUNCTIONAL INSIGHTS FROM LEAF
LEVEL AND CANOPY SPECTRA
Spectral measurements have allowed rapid and nondestructive detection of foliar traits for research in areas such as physiology, crop
breeding, and plant health. A broad suite of functional traits, including many leaf economic spectrum (LES) traits associated with
plant life history strategies, can be detected and accurately predicted using spectral data (Serbin et al., 2014). Spectral variation is
thus becoming increasingly used in quantitative genetics for highthroughput plant phenotyping and in functional ecology to gain
information on the life history strategies and stress tolerance of
plants (Fig. 1A). At the whole plant or canopy scale, the chemical
and structural composition of plants influences reflectance spectra
(Fig. 1B). Spectra can be obtained by high-fidelity imaging spectrometers at various distances from the ground, which alters the
size of the measurement unit (pixel). Vegetation traits can be estimated for each pixel in an image by scaling leaf level trait data by
species to the pixel level using allometric approaches (Singh et al.,
2015) or through direct estimation of canopy traits (Dahlin et al.,
2013; Chadwick and Asner, 2016). While many of the basic features
of plant spectra are well understood, considerable challenges remain in analyzing and interpreting the subtle dynamics of these
features in time and space, as well as in processing and storing large
data volumes.
GENETIC AND PHYLOGENETIC DIVERSITY FROM SPECTRA
Plant genotypes, species, and phylogenetic lineages differ in their
morphology, anatomy, and how they acquire and allocate resources.
These differences result from their evolutionary histories and genetic backgrounds and are further influenced by environmental
conditions. Spectra are increasingly used to detect different levels of
diversity, from intraspecific phenotypic and genetic variation to
phylogenetic lineages, despite environmentally caused variation.
For instance, genotypes of Populus tremuloides have been distinguished using imaging spectroscopy (Madritch et al., 2014), and
populations of tropical live oaks (Quercus oleoides) have been distinguished based on leaf-level spectra (Cavender-Bares et al., 2016).
Tools that leverage spectral data can facilitate rapid selection in
plant breeding based on suites of important traits, including anatomical or chemical attributes that influence reflectance at wavelengths outside the range of visible light (400–700 nm), and hence
are not visually observable; these nonvisible spectral traits can be
statistically associated with yield (or other remotely sensed fitness
proxies, such as biomass) (Babar et al., 2006).
Estimating the placement of an unknown spectral sample in the
tree of life (Fig. 1A) may now be within reach, given that spectra
appear to follow evolutionary models (Cavender-Bares et al., 2016),
and large regions of spectra are highly phylogenetically conserved
(McManus et al., 2016). Combined with species distribution models
A M E R I C A N J O U R N A L O F B OTA N Y
that provide information on which species are or are not likely to
occur in a geographic region, spectral approaches that locate plants
within the tree of life have potential to estimate levels of plant diversity, including phylogenetic diversity, at a range of spatial scales
(Jetz et al., 2016).
INSIGHTS FROM SPECTRA FOR COMMUNITIES, ECOSYSTEMS,
AND LANDSCAPES
Quantifying community responses to global changes and biotic invasions across landscapes is an emerging ecological application of
spectral measurements. Turnover in plant species composition
across landscapes has been detected and related to productivity in
prairie landscapes (Wang et al., 2016) and to biochemical composition in tropical forests (Feret and Asner, 2014). A major decline in
healthy hemlock (Tsuga canadensis) stands in the northeastern
United States due to invasion of the exotic woolly adelgid (Adelges
tsugae) was documented from NASA AVIRIS imagery (Hanavan
et al., 2015). Forest canopy water loss across California ecosystems
in response to prolonged drought has allowed identification of regions most at risk for widespread tree mortality (Asner et al., 2016).
Each of these studies illustrates the effective use of plant spectral
patterns to assess changing ecosystem function, with implications
for biodiversity.
While there is high potential to leverage spectra for community
ecology, very little has been done to include linkages of plants to
other trophic levels and to analyze co-occurrence patterns that
might reveal insights into coexistence mechanisms and community
assembly processes. Carbon-based defense traits (Couture et al.,
2016) are well retrieved from spectral information, facilitating integration of information on host-specific herbivores and pathogens
with leaf chemical composition and abundance.
We can expect spectral variation to represent variation in biomass and leaf chemistry that is linked to the chemistry of belowground root exudation. Aboveground plant functional diversity
may influence the diversity of substrates available as food for soil
organisms and have concomitant effects on the activity of enzymes
secreted by soil microorganisms, decomposition, and nutrient cycling.
Live and dead plant parts may include a diversity of organic molecules such as cellulose, hemicellulose, lignin, and tannins, among
others. For example, foliar spectral variation in aspen correlates
well with variation in canopy chemistry, including condensed tannin, lignin, and nitrogen concentrations, which is in turn linked to
variation in belowground processes (Madritch et al., 2014).
GLOBAL BIODIVERSITY MONITORING FOR MANAGING PLANET
EARTH
Given its high potential for monitoring global biodiversity, there is
growing emphasis on satellite missions that support imaging spectroscopy capabilities (Turner, 2014; Schimel et al., 2015; Jetz et al.,
2016). To the extent that the botanical community advances understanding and application of plant spectra from a multitude of perspectives on the ground, in the field, in the laboratory, from aerial
and airborne platforms, and from space, such missions stand to
revolutionize biodiversity science. The transformation will come
both from the technological capability to detect changes in plant
functional composition and diversity (Asner et al., 2017) through
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time across the globe (Jetz et al., 2016) and from our ability to identify hotspots of change that may inform management decisions.
However, major advances will require intentional integration
across biological and spatial scales and a deeper understanding and
wider application of spectra. We will also need to establish a common language and body of knowledge across the biodiversity sciences and develop mechanisms for reconciling and sharing data
across instruments and users. Currently, we lack a clear understanding of the scale-dependence of the spectral–biodiversity relationship, and this is likely to vary for different ecosystems (Wang
et al., in press). The temporal dynamics of spectra also deserve further study. Going forward, we will need to integrate field studies,
airborne studies, and satellite monitoring and develop new informatics approaches. The reward will be a new understanding of
plant ecology and a highly powerful set of tools for monitoring and
understanding changes in biodiversity across the globe, a requirement for sustainable management of planet Earth.
ACKNOWLEDGEMENTS
The authors thank three anonymous reviewers and Editor-in-Chief
P. Diggle for improving the manuscript. Funding was provided by the
National Science Foundation (NSF) and the National Aeronautics
and Space Administration (NASA) through the Dimensions of
Biodiversity program (DEB-1342872) and the Cedar Creek NSF
Long-Term Ecological Research program (DEB-1234162).
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