skip to main content


Title: Plant spectral diversity as a surrogate for species, functional and phylogenetic diversity across a hyper‐diverse biogeographic region
Abstract Aim

With plant biodiversity under global threat, there is an urgent need to monitor the spatial distribution of multiple axes of biodiversity. Remote sensing is a critical tool in this endeavour. One remote sensing approach for detecting biodiversity is based on the hypothesis that the spectral diversity of plant communities is a surrogate of multiple dimensions of biodiversity. We investigated the generality of this ‘surrogacy’ for spectral, species, functional and phylogenetic diversity across 1,267 plots in the Greater Cape Floristic Region (GCFR), a hyper‐diverse region comprising several biomes and two adjacent global biodiversity hotspots.

Location

The GCFR centred in south‐western and western South Africa.

Time period

All data were collected between 1978–2014.

Major taxa studied

Vascular plants within the GCFR.

Methods

Spectral diversity was calculated using leaf reflectance spectra (450–950 nm) and was related to other dimensions of biodiversity via linear models. The accuracy of different spectral diversity metrics was compared using 10‐fold cross‐validation.

Results

We found that a distance‐based spectral diversity metric was a robust predictor of species, functional and phylogenetic biodiversity. This result serves as a proof‐of‐concept that spectral diversity is a potential surrogate of biodiversity across a hyper‐diverse biogeographic region. While our results support the generality of spectral diversity as a biodiversity surrogate, we also find that relationships vary between different geographic subregions and biomes, suggesting that differences in broad‐scale community composition can affect these relationships.

Main conclusions

Spectral diversity was shown to be a robust surrogate of multiple dimensions of biodiversity across biomes and a widely varying biogeographic region. We also extend these surrogacy relationships to ecological redundancy to demonstrate the potential for additional insights into community structure based on spectral reflectance.

 
more » « less
NSF-PAR ID:
10374842
Author(s) / Creator(s):
 ;  ;  ;  ;  ;  ;  ;  ;  ;  ;
Publisher / Repository:
Wiley-Blackwell
Date Published:
Journal Name:
Global Ecology and Biogeography
Volume:
30
Issue:
7
ISSN:
1466-822X
Page Range / eLocation ID:
p. 1403-1417
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. Abstract Aim

    Mountains provide uniquely informative systems for examining how biodiversity is distributed and identifying the causes of those patterns. Elevational patterns of species richness are well‐documented for many taxa but comparatively few studies have investigated patterns in multiple dimensions of biodiversity along mountainsides, which can reveal the underlying processes at play. Here, we use trait‐based diversity patterns to determine the role of abiotic filters and competition in the assembly of communities of small mammals across elevation and evaluate the surrogacy of taxonomic, functional, and phylogenetic dimensions of diversity.

    Location

    Great Basin ecoregion, western North America.

    Taxon

    Rodents and shrews.

    Methods

    The elevational distributions of 34 species were determined from comprehensive field surveys conducted in three arid, temperate mountain ranges. Elevation–diversity relationships and community assembly processes were inferred from phylogenetic (PD) and functional diversity (FD) patterns of mean pairwise and mean nearest‐neighbor distances while accounting for differences in species richness. FD indices were calculated separately for traits related to either abiotic filtering (β‐niche traits) or biotic interactions (α‐niche traits) to test explicit predictions of the role of each across elevation.

    Results

    Trait‐based tests of processes indicated that abiotic filtering tied to a strong aridity gradient drives the assembly of both low‐ and high‐elevation communities. Support for competition was not consistent with theoretical expectations under the stress‐dominance hypothesis, species interactions‐abiotic stress hypothesis, or guild assembly rule. Mid‐elevation peaks in species richness contrasted with overall FD and PD, which generally increased with elevation. PD and total FD were correlated on two of three mountains.

    Main conclusions

    The functional diversity of small mammal communities in these arid, temperate mountains is most consistent with abiotic filters, whereas support for competition is weak. Decomposing FD into traits related to separate assembly processes and examining ecoregional variation in diversity were critical for uncovering the generality of mechanisms. Divergent patterns among dimensions revealed species richness to be a poor surrogate for PD and FD across elevation and reflect the effect of biogeographic and evolutionary history. This first analysis of elevational multidimensional diversity gradients for temperate mammals provides a versatile framework for future comparative studies.

     
    more » « less
  2. Abstract Aim

    Rapid global change is impacting the diversity of tree species and essential ecosystem functions and services of forests. It is therefore critical to understand and predict how the diversity of tree species is spatially distributed within and among forest biomes. Satellite remote sensing platforms have been used for decades to map forest structure and function but are limited in their capacity to monitor change by their relatively coarse spatial resolution and the complexity of scales at which different dimensions of biodiversity are observed in the field. Recently, airborne remote sensing platforms making use of passive high spectral resolution (i.e., hyperspectral) and active lidar data have been operationalized, providing an opportunity to disentangle how biodiversity patterns vary across space and time from field observations to larger scales. Most studies to date have focused on single sites and/or one sensor type; here we ask how multiple sensor types from the National Ecological Observatory Network’s Airborne Observation Platform (NEON AOP) perform across multiple sites in a single biome at the NEON field plot scale (i.e., 40 m × 40 m).

    Location

    Eastern USA.

    Time period

    2017–2018.

    Taxa studied

    Trees.

    Methods

    With a fusion of hyperspectral and lidar data from the NEON AOP, we assess the ability of high resolution remotely sensed metrics to measure biodiversity variation across eastern US temperate forests. We examine how taxonomic, functional, and phylogenetic measures of alpha diversity vary spatially and assess to what degree remotely sensed metrics correlate with in situ biodiversity metrics.

    Results

    Models using estimates of forest function, canopy structure, and topographic diversity performed better than models containing each category alone. Our results show that canopy structural diversity, and not just spectral reflectance, is critical to predicting biodiversity.

    Main conclusions

    We found that an approach that jointly leverages spectral properties related to leaf and canopy functional traits and forest health, lidar derived estimates of forest structure, fine‐resolution topographic diversity, and careful consideration of biogeographical differences within and among biomes is needed to accurately map biodiversity variation from above.

     
    more » « less
  3. Abstract

    Hyperspectral remote sensing has the potential to map numerous attributes of the Earth’s surface, including spatial patterns of biological diversity. Grasslands are one of the largest biomes on Earth. Accurate mapping of grassland biodiversity relies on spectral discrimination of endmembers of species or plant functional types. We focused on spectral separation of grass lineages that dominate global grassy biomes: Andropogoneae (C4), Chloridoideae (C4), and Pooideae (C3). We examined leaf reflectance spectra (350–2,500 nm) from 43 grass species representing these grass lineages from four representative grassland sites in the Great Plains region of North America. We assessed the utility of leaf reflectance data for classification of grass species into three major lineages and by collection site. Classifications had very high accuracy (94%) that were robust to site differences in species and environment. We also show an information loss using multispectral sensors, that is, classification accuracy of grass lineages using spectral bands provided by current multispectral satellites is much lower (accuracy of 85.2% and 61.3% using Sentinel 2 and Landsat 8 bands, respectively). Our results suggest that hyperspectral data have an exciting potential for mapping grass functional types as informed by phylogeny. Leaf‐level hyperspectral separability of grass lineages is consistent with the potential increase in biodiversity and functional information content from the next generation of satellite‐based spectrometers.

     
    more » « less
  4. Abstract

    A rich body of evidence from local-scale experiments and observational studies has revealed stabilizing effects of biodiversity on ecosystem functioning. However, whether these effects emerge across entire regions and continents remains largely overlooked. Here we combine data on the distribution of more than 57,500 plant species and remote-sensing observations throughout the entire Western Hemisphere to investigate the role of multiple facets of plant diversity (species richness, phylogenetic diversity, and functional diversity) in mediating the sensitivity of ecosystems to climate variability at the regional-scale over the past 20 years. We show that, across multiple biomes, regions of greater plant diversity exhibit lower sensitivity (more stable over time) to temperature variability at the interannual and seasonal-scales. While these areas can display lower sensitivity to interannual variability in precipitation, they emerge as highly sensitive to precipitation seasonality. Conserving landscapes of greater diversity may help stabilize ecosystem functioning under climate change, possibly securing the continuous provisions of productivity-related ecosystem service to people.

     
    more » « less
  5. Abstract

    Evolutionary relatedness underlies patterns of functional diversity in the natural world. Hyperspectral remote sensing has the potential to detect these patterns in plants through inherited patterns of leaf reflectance spectra. We collected leaf reflectance data across the California flora from plants grown in a common garden. Regions of the reflectance spectra vary in the depth and strength of phylogenetic signal. We also show that these differences are much greater than variation due to the geographic origin of the plant. At the phylogenetic extent of the California flora, spectral variation explained by the combination of ecotypic variation (divergent evolution) and convergent evolution of disparate lineages was minimal (3%–7%) but statistically significant. Interestingly, at the extent of a single genus (Arctostaphylos) no unique variation could be attributed to geographic origin. However, up to 18% of the spectral variation amongArctostaphylosindividuals was shared between phylogeny and intraspecific variation stemming from ecotypic differences (i.e., geographic origin). Future studies could conduct more structured experiments (e.g., transplants or observations along environmental gradients) to disentangle these sources of variation and include other intraspecific variation (e.g., plasticity). We constrain broad‐scale spectral variability due to ecotypic sources, providing further support for the idea that phylogenetic clusters of species might be detectable through remote sensing. Phylogenetic clusters could represent a valuable dimension of biodiversity monitoring and detection.

     
    more » « less