Plant Spectral Diversity As A Surrogate For Species, Functional And Phylogenetic Diversity Across A Hyper-Diverse Biogeographic Region

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.