SPATIAL FUNCTIONAL DATA MODELING OF PLANT REFLECTANCES

Plant reflectance spectra, the profile of light reflected by leaves across different wavelengths, supply the spectral signature for a species at a spatial location to enable estimation of functional and taxonomic diversity for plants. We consider leaf spectra as “responses” to be explained spatially. These re-flectance spectra are also functions over wavelength that respond to the envi-ronment. Our motivating data are gathered for several plant families from the Greater Cape Floristic Region (GCFR) in South Africa and lead us to develop rich novel spatial models that can explain spectra for genera within families. Wavelength responses for an individual leaf are viewed as a function of wave-length, leading to functional data modeling. Local environmental features be-come covariates. We introduce a wavelength, covariate interaction, since the response to environmental regressors may vary with wavelength, as may vari-ance. Formal spatial modeling enables prediction of reflectances for genera at unobserved locations with known environmental features. We incorporate spatial dependence, wavelength dependence, and space–wavelength interaction (in the spirit of space–time interaction). We implement out-of-sample validation for model selection, finding that the model features above are in-formative for the functional data analysis. We supply ecological interpretation of the results under the selected model.

Duke Scholars

Author Alan E. Gelfand Statistical Science