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Mapping the Atlantic Seabed: Status, Drivers, and Future Opportunities

This article highlights the current drivers, approaches, activities, and priorities in the mapping of the Atlantic seabed. It also explores future opportunities, challenges, and aspirations in the field. The focus is on efficient data collection, biotope characterization, and the development of common systems for describing ecosystems.

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Mapping the Atlantic Seabed: Status, Drivers, and Future Opportunities

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  1. Atlantic Seabed Mapping – Status & Direction Towards a CAN-EU-US Atlantic strategic seabed mapping pilot initiative: highlighting current drivers, approaches, activities, and priorities, and future opportunities, challenges and aspirations Pål Buhl-Mortensen Institute of Marine Research Galway Statement Implementation – Atlantic Seabed Mapping Workshop Dublin Castle, Dublin, 1st – 2nd December 2014

  2. Bathymetry – terrain descriptors at relevant scales • The North Atlantic • ~20 mill km2 • Meandepth ~ 3900m • Greatestdepth 8380m • Example: MAREANO mappingprogramme • Started 2006 • Total area coveredwith MBE: 131 000 km2 • € 6.5 mill/yr • € 0.4 mill/1000 km2 • N Atlantic: • € 6.5 billion • € 130 mill/yr – 50 yr • Realistic approaches • Focus on priority areas • Instrumentation of commercial vessels • AUV etc • Representative areas/transects

  3. Spatial information for decision support Biological values (Biodiversity, vulnerability, productivity, etc) 3. Sampling Biological/geological sampling of a selection of video locations 2. Video surveys Visual documentation of ~0.1‰ of the MBE- mapped seabed 1. Multibeam mapping VIII. Selection of sampling locations Biotope distribution VII. Predictive modeling of biotopes VI. Faunal classification V. Video analyses Sediments, Marine landscapes & Oceanography Mapping activities Environmental variables IV. Selection of video survey locations III. Oceanographic modeling Environmental proxies II. Unsupervised classification I. Terrain analyses

  4. Gaps and challenges • Efficient use of existing data • Efficient collection of new data • Multibeam surveying • Biotope characterisation • analyses of imagery • Collection of bottom samples • Use of classifications • Communities and environment • Unified systems (CMECS, EUNIS, NiN etc) • Ecosystem functions/monitoring (selection of locations) • Suggestions and solutions • Data repositories (PANGEA EMODNET) – Digitization of historic data • Instrumentation of commercial vessels, Autonomous vehicles • Semi-automatic image analyses/annotation tools • Sampling designs supervised by spatial info on environmental/habitat variation • Develop common systems for describing ecosystems/biotopes • Develop functional definitions that enable comarisons between areas • Selection of locations/biotopes/ indicators guided by spatial information on pressures, vulnerability and environmental relationships

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