Skip to main content
Dryad

Biodiversity across the Greater Cape Floristic Region

Data files

May 04, 2021 version files 271.13 KB

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 endeavor. One remote sensing approach in 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 centered in southwestern and western South Africa.

Time Period: All data were collected between 19782014.

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 ten-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.