The National Deep-Sea Coral and Sponge Database: A Comprehensive Resource for United States Deep-Sea Coral and Sponge Records

Abstract:

Research on deep-sea corals has expanded rapidly over the last two decades, as scientists began to realize their value as long-lived structural components of high biodiversity habitats and archives of environmental information. The NOAA Deep Sea Coral Research and Technology Program’s National Database for Deep-Sea Corals and Sponges is a comprehensive resource for georeferenced data on these organisms in U.S. waters. The National Database currently includes more than 220,000 deep-sea coral records representing approximately 880 unique species. Database records from museum archives, commercial and scientific bycatch, and from journal publications provide baseline information with relatively coarse spatial resolution dating back as far as 1842. These data are complemented by modern, in-situ submersible observations with high spatial resolution, from surveys conducted by NOAA and NOAA partners.

Management of high volumes of modern high-resolution observational data can be challenging. NOAA is working with our data partners to incorporate this occurrence data into the National Database, along with images and associated information related to geoposition, time, biology, taxonomy, environment, provenance, and accuracy. NOAA is also working to link associated datasets collected by our program’s research, to properly archive them to the NOAA National Data Centers, to build a robust metadata record, and to establish a standard protocol to simplify the process.

Access to the National Database is provided through an online mapping portal. The map displays point based records from the database. Records can be refined by taxon, region, time, and depth. The queries and extent used to view the map can also be used to download subsets of the database. The database, map, and website is already in use by NOAA, regional fishery management councils, and regional ocean planning bodies, but we envision it as a model that can expand to accommodate data on a global scale.