4.5 Article

Plant spectral diversity integrates functional and phylogenetic components of biodiversity and predicts ecosystem function

Journal

NATURE ECOLOGY & EVOLUTION
Volume 2, Issue 6, Pages 976-+

Publisher

NATURE PORTFOLIO
DOI: 10.1038/s41559-018-0551-1

Keywords

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Funding

  1. National Science Foundation
  2. National Aeronautics and Space Administration through Dimensions of Biodiversity programme [DEB-1342872, DEB-1342778, DEB-1342827, DEB-1342823]
  3. Cedar Creek National Science Foundation Long-Term Ecological Research programme [DEB-1234162]
  4. iCORE/AITF [G224150012, 200700172]
  5. NSERC [RGPIN-2015-05129]
  6. CFI [26793]
  7. China Scholarship Council
  8. Direct For Biological Sciences
  9. Division Of Environmental Biology [1342778] Funding Source: National Science Foundation

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Biodiversity promotes ecosystem function as a consequence of functional differences among organisms that enable resource partitioning and facilitation. As the need for biodiversity assessments increases in the face of accelerated global change, novel approaches that are rapid, repeatable and scalable are critical, especially in ecosystems for which information about species identity and the number of species is difficult to acquire. Here, we present 'spectral diversity'-a spectroscopic index of the variability of electromagnetic radiation reflected from plants measured in the visible, near-infrared and short-wave infrared regions (400-2,400 nm). Using data collected from the Cedar Creek biodiversity experiment (Minnesota, USA), we provide evidence that the dissimilarity of species' leaf spectra increases with functional dissimilarity and evolutionary divergence time. Spectral diversity at the leaf level explains 51% of total variation in productivity-a proportion comparable to taxonomic (47%), functional (51%) or phylogenetic diversity (48%)-and performs similarly when calculated from high-resolution canopy image spectra. Spectral diversity is an emerging dimension of plant biodiversity that integrates trait variation within and across species even in the absence of taxonomic, functional, phylogenetic or abundance information, and has the potential to transform biodiversity assessment because of its scalability to remote sensing.

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