OOS 23-5 - Scaling from leaf optical properties to canopies: How does optical diversity predict biodiversity?

Wednesday, August 10, 2016: 2:30 PM
Grand Floridian Blrm F, Ft Lauderdale Convention Center
Anna K. Schweiger1, Jeannine Cavender-Bares1, Ran Wang2, Philip A. Townsend3 and John A. Gamon2, (1)Department of Ecology, Evolution, and Behavior, University of Minnesota, Saint Paul, MN, (2)Department of Earth and Atmospheric Sciences, University of Alberta, Edmonton, AB, Canada, (3)Department of Forest and Wildlife Ecology, University of Wisconsin-Madison, Madison, WI

Developing consistent methods to assess biodiversity using remote sensing techniques requires a thorough understanding of the relationship between leaf optical properties and the spectral signals detected at the canopy scale. Indices that capture optical diversity, such as the coefficient of variation, have shown promise in detecting biodiversity in our study system. Building upon these results, we investigated the extent to which canopy structure contributes to the correlations between optical diversity and different diversity metrics, including measures of species, functional and phylogenetic diversity. We used leaf level spectroscopic data and spectroscopic data collected at the canopy scale using an automated tram system in the prairie biodiversity experiment (BioDIV) at Cedar Creek in Central Minnesota. Simulated canopy images were created using species specific leaf spectra, randomly drawn from the distribution of the species spectra measured in plots with varying diversity levels. Comparing observed and simulated images allowed us to disentangle the effect of canopy structure on the relationship between optical diversity and different diversity metrics. Spectroscopic data from individually marked leaves measured simultaneously at the leaf and the canopy level were used to relate our results to biochemical plant traits estimated at both spatial scales.


Simulated canopy data showed lower optical diversity than the original canopy data, with consistent patterns across plot diversity levels, regardless of the diversity metric used. Likewise, the correlations between optical diversity and any of the diversity metrics decreased in the simulated dataset. However, the decline depended on the diversity metric and was less pronounced for phylogenetic diversity. Moreover, biochemical plant trait diversity estimated at the plot level was more closely related to phylogenetic diversity than any other diversity metric. Our results indicate that structural canopy effects contribute substantially to optical diversity, but their influences on the relationship between optical diversity and different diversity metrics vary. It appears that the detectability of phylogenetic diversity in our study system depends less on canopy structure than species or functional diversity, possibly due to its stronger link to leaf chemistry.