Abstract
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.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 976-982 |
| Number of pages | 7 |
| Journal | Nature Ecology and Evolution |
| Volume | 2 |
| Issue number | 6 |
| DOIs | |
| State | Published - Jun 1 2018 |
Bibliographical note
Publisher Copyright:© 2018 The Author(s).
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Dive into the research topics of 'Plant spectral diversity integrates functional and phylogenetic components of biodiversity and predicts ecosystem function'. Together they form a unique fingerprint.Datasets
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Leaf carbon fraction data from tree and grassland species collected at the Cedar Creek Ecosystem Science Reserve in 2015 and 2016
Schweiger, A. K., Lapadat, C., Kothari, S. A. & Cavender-Bares, J. M., Data Repository for the University of Minnesota, 2020
DOI: 10.13020/d74j-wd55, http://hdl.handle.net/11299/214935
Dataset
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Leaf carbon and nitrogen content of tree and grassland species collected at the Cedar Creek Ecosystem Science Reserve in 2015 and 2016
Schweiger, A. K., Lapadat, C. & Cavender-Bares, J. M., Data Repository for the University of Minnesota, 2020
DOI: 10.13020/0476-9m60, http://hdl.handle.net/11299/215291
Dataset
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Content of leaf pigments of tree and grassland species collected at the Cedar Creek Ecosystem Science Reserve in 2015 and 2016
Schweiger, A. K., Fredericksen, B., Lapadat, C. & Cavender-Bares, J. M., Data Repository for the University of Minnesota, 2020
DOI: 10.13020/j7fw-2g91, http://hdl.handle.net/11299/215290
Dataset
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