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.

Leaf reflectance spectra have been increasingly used to assess plant diversity. However, we do not yet understand how spectra vary across the tree of life or how the evolution of leaf traits affects the differentiation of spectra among species and lineages. Here we describe a framework that integrates spectra with phylogenies and apply it to a global dataset of over 16 000 leaf-level spectra (400-2400 nm) for 544 seed plant species. We test for phylogenetic signal in spectra, evaluate their ability to classify lineages, and characterize their evolutionary dynamics. We show that phylogenetic signal is present in leaf spectra but that the spectral regions most strongly associated with the phylogeny vary among lineages. Despite among-lineage heterogeneity, broad plant groups, orders, and families can be identified from reflectance spectra. Evolutionary models also reveal that different spectral regions evolve at different rates and under different constraint levels, mirroring the evolution of their underlying traits. Leaf spectra capture the phylogenetic history of seed plants and the evolutionary dynamics of leaf chemistry and structure. Consequently, spectra have the potential to provide breakthrough assessments of leaf evolution and plant phylogenetic diversity at global scales.

Author ContributionsENS is the lead writer for the manuscript, DS lead discussions and helped articulate the key points of discussion for the manuscript, RP provided HISUI and OCO3 information and subfigures associated with Figure 2 as well as with edits for the manuscript, SS helped edit the general text, developed Figure 2 and provided text for terrestrial biosphere models section, AS helped edit the general text and provided text for terrestrial biosphere models sections, LD provided the GEDI sub-figure in Figure 2 and text describing GEDI, JBF helped with general editing and provided the ECOSTRESS sub-figure in Figure 2, FF helped with general editing, SU helped develop the original manuscript outline, RD, AS and PW were key in contributing ideas for the manuscript.

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