“Big Data” Squared: GIS, Hydrological, and Remote Sensing Data Coupled with Gene Flow and Species Distributions

Eco-hydrology and landscape genetics are bourgeoning fields of research that attempt to document effects of landscape-scale disturbances like urbanization, agriculture, and water impoundments on the sustainability and connectivity of native populations.  Unprecedented availability of GIS and remote sensing data provides exciting new research opportunities, but also new challenges in the collection and analysis of spatial data.  To overcome the workflow bottleneck associated with acquiring and extracting GIS data at appropriate spatial scales, a centralized national geodatabase and automated data collector—Geodata Crawler—is being developed to rapidly tabulate customized multi-scale landscape data (i.e. from watersheds, riparian zones, or stream paths).  Multi-model comparison and machine learning will be discussed as analytical solutions to accommodate potentially unwieldy datasets.  Three ongoing or planned projects provide examples: (1) Multi-scale habitat associations of the endangered American burying beetle and a satellite-based monitoring tool; (2) Mapping natural flow regimes and hydrologic alteration in the Ozark-Ouachita Interior Highlands; and (3) Identifying barriers to gene flow among populations of Bluehead Sucker, a sensitive fish in the Colorado River basin.  The potential for automated multi-scale data collection to foster interdisciplinary research in eco-hydrology, landscape genetics, and species distributions will be emphasized.