Mapping functional diversity of canopy physiological traits using UAS imaging spectroscopy

Plant functional diversity (FD) is a component of biodiversity linking plant functional traits to ecosystem processes (e.g., photosynthesis) and services (e.g., gross primary production). Development of remote sensing capabilities to monitor forest FD across various spatio-temporal scales is critical, especially in view of increasing global climate and anthropogenic pressures. Here, we focus on investigating the capability of unoccupied aerial systems (UAS), acquiring imaging spectroscopy data of high spatial (pixel size <= 0.1 m) and spectral (band-width < 5 nm between 400 and 1000 nm) resolutions, to map two trait-based FD metrics, namely, richness and divergence, of two open sclerophyll forests at the plot-scale (<0.2 km(2)). An emerging scalable kernel-based trait probability density (TPD) approach was implemented to compute spatially explicit metrics of FD at different areal extents and pixel sizes through spatially resampled products. Narrow-band spectral indices were utilized as proxies of selected plant functional traits, including photoprotective zeaxanthin-to-antheraxanthin transformation ratio (VAZ), and foliar pigments of chlorophylls and anthocyanins (C-ab and C-ant). The combination of high-resolution imagery and TPDs presents a suitable alternative to the traditional need for taxonomic information and alleviates pixel-based spectral mixing issues known to affect pixel-based FD metrics. A moving kernel (6 x 6 m) applied to UAS data, allowed to capture fine and medium-scale drivers of functional richness and divergence, including within-crown and complex branching variance, topography, sun aspect, and speciation. For the same kernel size, functional richness computed from coarsened pseudo-airborne products (pixel size of 2 m) was found to be 57-68% of that derived from UAS products. Functional divergence did not portray substantial differences across scales and resolutions, even though this metric further emphasized the complexity of the surveyed open-forest sclerophyll sites. UAS have the potential to become an efficient tool for monitoring FD linked with ecosystem processes at key monitoring sites, and for the validation and support of large-scale but less detailed airborne and satellite products. Finally, this study highlights the sensitivity of FD metrics to variations in scale, resolution, and TPD parametrization suggesting that more research is needed to standardize remote sensing protocols for the quantification of FD across spatial and temporal scales.