Variation in Leaf Reflectance Spectra Across the California Flora Partitioned by Evolutionary History, Geographic Origin, and Deep Time. Issue 2 (13th February 2023) - Griffith, Daniel M.; Byrd, Kristin B.; Taylor, Niky; Allan, Elijah; Bittner, Liz; O'Brien, Bart; Parker, V. Thomas; Vasey, Michael C.; Pavlick, Ryan; Nemani, Ramakrishna R.
Abstract: Evolutionary relatedness underlies patterns of functional diversity in the natural world. Hyperspectral remote sensing has the potential to detect these patterns in plants through inherited patterns of leaf reflectance spectra. We collected leaf reflectance data across the California flora from plants grown in a common garden. Regions of the reflectance spectra vary in the depth and strength of phylogenetic signal. We also show that these differences are much greater than variation due to the geographic origin of the plant. At the phylogenetic extent of the California flora, spectral variation explained by the combination of ecotypic variation (divergent evolution) and convergent evolution of disparate lineages was minimal (3%–7%) but statistically significant. Interestingly, at the extent of a single genus ( Arctostaphylos ) no unique variation could be attributed to geographic origin. However, up to 18% of the spectral variation among Arctostaphylos individuals was shared between phylogeny and intraspecific variation stemming from ecotypic differences (i.e., geographic origin). Future studies could conduct more structured experiments (e.g., transplants or observations along environmental gradients) to disentangle these sources of variation and include other intraspecific variation (e.g., plasticity). We constrain broad‐scale spectral variability due to ecotypic sources, providing further support for the idea that phylogenetic clusters of species might be detectable through remote sensing. Phylogenetic clusters could represent a valuable dimension of biodiversity monitoring and detection. Plain Language Summary: Related plant species often share inherited features, and we show that this is the case for the way the plant leaves reflect certain wavelengths of light. We collected leaf reflectance data from plants in a common garden where plants from across California are grown. Evolution explained more of the reflectance qualities of leaves than geographic origin of the plant species. These results provide support for the idea that remote sensing could help monitor biodiversity change by detecting groups of related plants. Key Points: We collected leaf reflectance data from across the California flora from plants grown in a common garden Different parts of the spectra capture deeper evolutionary differences among plants and are more important than geographic origin This provides support for the idea that phylogenetic clusters of species might be detectable through remote sensing