Detecting prairie biodiversity with airborne remote sensing

This study assessed the application of airborne imaging spectroscopy to monitor alpha-diversity in restored grassland plots. The study site was located within the Central Platte River ecosystem, south of Wood River in Central Nebraska, USA, and consisted of two sets of plots (young and old). Exotic species had recently invaded the old plots, confounding the original study design, while the young plots did not have significant invasion by weeds, reflecting the original study design. We used spectral variation (i.e. spectral diversity, expressed as the coefficient of variation) as a proxy for alpha-diversity (expressed as species richness and Shannon index). Airborne data collected at two flight altitudes and two flight directions tested the validity of spectral diversity-alpha-diversity relationship at different sampling scales and flight directions. Our results showed a strong relationship between spectral diversity and alpha-diversity in young, non-invaded plots exhibiting strong differences in alpha-diversity. However, in the old, invaded plots, the spectral diversity-alpha-diversity relationship was non-significant. Factors likely contributing to this failure in the old plots included the spatial mismatch between airborne and field-based sampling, the convergence in diversity levels over time, and the unique reflectance signatures of the invasive species related to their different structural and phenological properties. Unlike previous airborne studies in manipulated experimental prairie plots, but similar to results in more natural settings, the strong spectral diversity-alpha-diversity relationship in the young plots remained even at the spatial resolution of 1 m, demonstrating the potential of airborne remote sensing to assess diversity patterns in prairie grasslands. These findings demonstrate the importance of experimental remote sensing in evaluating spectral diversity, and provide insight for the development of operational airborne methods to assess biodiversity.