Hyperspectral remote sensing: Unlocking process in a marine foundation species

Examining patterns at a variety of scales is essential for identifying and elucidating ecological processes. High-resolution, spatially explicit remotely sensed data have revolutionized the study of how pattern and variability change across the scale of description. Here we use a time series of hyperspectral aerial imagery to examine the regional and local scale dynamics of a globally distributed coastal foundation species, giant kelp. By linking these regional and local scale dynamics and developing a conceptual model on how giant kelp forests emerge, grow, and senesce we can better understand the spatial and temporal dynamics of the diverse kelp-associated ecosystem.