Remote sensing of belowground variation in trembling aspen forests
The chemical traits of forest canopies that are important to soil microbial communities are increasingly measurable via remote sensing platforms. For instance, imaging spectroscopy can provide detailed chemical information about forest canopies by measuring reflectance across a wide range of the electromagnetic spectrum at fine spectral and spatial resolutions. Recent advances in remote sensing indicate that imaging spectroscopy can be used as proxies for important aboveground ecological traits. Here, we demonstrate that imaging spectroscopy can also be used as a proxy for belowground systems. We employed NASA’s airborne imaging spectrometer, AVIRIS, to measure both above- and belowground variation in trembling aspen (Populus tremuloides) forests. We employed trembling aspen as a model system due to its widespread ecological and economic importance, and well-characterized variation in leaf chemistry. We sampled sites across the continental US for both canopy and soil samples. The functional response of soil communities was estimated by measuring extracellular enzyme activity potentials, and belowground microbial diversity was estimated by next generation sequencing techniques.
While one of our primary goals was to measure variation in aboveground chemistry and aspen genotype, our work also demonstrates that remote sensing can provide information regarding belowground systems. Variation in AVIRIS imagery was well correlated with variation in belowground enzyme activities, C, N, and extractable NH4+ and NO3-. In addition to serving as a proxy for microbial functional responses, AVIRIS imagery can also provide taxonomic information as suggested by next generation sequence analysis of soil bacterial and fungal communities. While we cannot correlate specific taxa with specific AVIRIS spectra at this point, imaging spectroscopy is related to simple belowground diversity indexes generated from Illumina MiSeq runs. These results suggest that remote sensing technologies can be used to describe the fine-scale variation in belowground systems across large spatial scales that is otherwise not feasible via traditional field collection methods