title: Spectral diversity area relationships for assessing biodiversity in a wildland-agriculture matrix.
abstract: Species-area relationships have long been used to assess patterns of species diversity across scales. Here, this concept is extended to spectral diversity using hyperspectral data collected by NASA's Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) over western Michigan. This mixture of mesic forest and agricultural lands offers two end-points on the local-scale diversity continuum; one set of well-mixed forest patches and one set of highly homogeneous agricultural patches. Using the sum of the first three principal component values and the principal components' convex hull volume, spectral diversity was compared within and among these plots and to null expectations for perfectly random and perfectly patchy landscapes. Overall, the spectral diversity-area relationship confirms the patterns that would be expected for this landscape, but this application suggests that this approach could be extended to less well-understood landscapes and could reveal key insights about the relative importance of different drivers of community assembly, even in the absence of additional data about plant functional traits or species' identities.
authors.affiliation: Department of Geography, Environment, and Spatial Sciences and Program in Ecology, Evolutionary Biology, and Behavior,  Michigan State University, Geography Building, 673 Auditorium Road, East Lansing, Michigan, 48824, USA.
authors.forename: Kyla Marie
authors.initials: KM
authors.lastname: Dahlin
mesh_terms: D000383:Agriculture; D044822:Biodiversity; D065928:Forests; D008824:Michigan; D010944:Plants
keywords: Airborne Visible/Infrared Imaging Spectrometer; Michigan; biodiversity; community assembly; hyperspectral remote sensing; imaging spectroscopy; spectral diversity-area relationship