4.5 Article

Variation in Leaf Reflectance Spectra Across the California Flora Partitioned by Evolutionary History, Geographic Origin, and Deep Time

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AMER GEOPHYSICAL UNION
DOI: 10.1029/2022JG007160

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hyperspectral; surface biology and geology; leaf reflectance; phylogenetic conservatism; evolution

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Evolutionary relatedness plays a key role in determining functional diversity patterns in the natural world. Hyperspectral remote sensing can detect these patterns in plants based on inherited leaf reflectance spectra. Our study on California flora revealed that the variation in reflectance spectra is more influenced by phylogenetic relatedness than geographic origin. The combination of ecotypic and convergent evolution accounted for a small but statistically significant portion (3%-7%) of the spectral variation. However, at a genus level, no unique variation was linked to geographic origin, and a considerable proportion (up to 18%) of spectral variation was shared between phylogeny and intraspecific ecotypic differences.
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.

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