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Description: These datasets include U.S. West Coast regions and gridded areas designed to aid in the prioritization of future seafloor mapping. Also included are data layers depicting general priority areas for seafloor mapping and deep-sea coral and sponge visual surveys, using remotely operated vehicles (ROV) and autonomous underwater vehicles (AUV), that were suggested and voted on by deep-sea coral and mapping experts at the 2018 DSCRTP WCDSCI science priority scoping workshop.

Copyright Text: National Oceanic and Atmospheric Administration (NOAA)

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Layer: Prioritization Grid (101)

Parent Layer: Prioritization

Sub Layers:
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• Washington State Existing Prioritization Grid
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Description: These datasets include five West Coast regions and gridded areas designed to aid in the prioritization of future seafloor mapping. Also included is a grid which was used to assist the State of Washington in prioritizing seafloor mapping data needs along Washington's Pacific coast.

Copyright Text: National Oceanic and Atmospheric Administration (NOAA)

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Layer: West Coast Proposed Subregions (102)

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Description: Five subregions of the Pacific West Coast US developed by NOAA's National Centers for Coastal Ocean Science (NCCOS) to aid in the prioritization of areas for future seafloor mapping and deep sea surveys.

Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science

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Description: This 10 x 10 minute grid was developed by NOAA's National Centers for Coastal Ocean Science (NCCOS) to aid in the prioritization of areas for future seafloor mapping and deep sea surveys.

Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Description: This grid was used to assist the State of Washington in prioritizing seafloor mapping data needs along Washington's Pacific coast as part of their marine spatial planning process.

Copyright Text: State of Washington, National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Layer: Washington State Existing Prioritization Combined Hotspot Model (1041)

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Description: This model shows the cumulative hot spots of the Washington State Prioritization project responses combined with neighborhood analysis.

Copyright Text: NOAA/NOS/NCCOS

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Layer: DSCRTP WCI Workshop Priorities (105)

Parent Layer: Prioritization

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Description: These data layers depict general priority areas for seafloor mapping and deep-sea coral and sponge visual surveys, using remotely operated vehicles (ROV) and autonomous underwater vehicles (AUV), that were suggested and voted on by deep-sea coral and mapping experts at the 2018 DSCRTP WCDSCI science priority scoping workshop.

Copyright Text: Deep-Sea Coral Research and Technology Program (DSCRTP); National Oceanic and Atmospheric Administration (NOAA); Channel Islands National Marine Sanctuary (CINMS)

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Spatial Reference: 102100  (3857)



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Layer: Priority Mapping Areas (106)

Parent Layer: DSCRTP WCI Workshop Priorities

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Description: This data layer depicts general priority areas for seafloor mapping that were suggested and ranked by West Coast deep-sea coral and mapping experts at the 2018 DSCRTP WCDSCI science priority scoping workshop.

Copyright Text: Deep-Sea Coral Research and Technology Program (DSCRTP); Channel Islands National Marine Sanctuary (CINMS); National Oceanic and Atmospheric Administration (NOAA)

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Description: This data layer depicts priority areas for coral surveys using remotely operated vehicles (ROV) that were decided upon during the DSCRTP WCI Workshop.

Copyright Text: Deep-Sea Coral Research and Technology Program (DSCRTP); Channel Islands National Marine Sanctuary (CINMS); National Oceanic and Atmospheric Administration (NOAA)

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Layer: Administrative (200)

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Description: These datasets include a variety of marine managed areas along the U.S. West Coast, which include various state managed areas, Essential Fish Habitat (EFH) designations, Habitat Areas of Particular Concern (HAPC), National Marine Sanctuaries (NMS), and BOEM leasing data.

Copyright Text: National Oceanic and Atmospheric Administration (NOAA), Bureau of Ocean Energy Management (BOEM)

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Copyright Text: U.S. Census Bureau

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Description: Maritime limits for the United States are measured from the U.S. baseline, recognized as the low-water line along the coast as marked on NOAA's nautical charts in accordance with the articles of the Law of the Sea. The baseline and related maritime limits are reviewed and approved by the interagency U.S. Baseline Committee. The primary purpose of this dataset is to update the official depiction of these maritime limits and boundaries on NOAA's nautical charts. The Office of Coast Survey depicts on its nautical charts the territorial sea (12 nautical miles), contiguous zone (24nm), and exclusive economic zone (200nm, plus maritime boundaries with adjacent/opposite countries). U.S. maritime limits are ambulatory and subject to revision based on accretion or erosion of the charted low water line. To ensure you are up-to-date and for more information about U.S. Maritime Limits and Boundaries, see http://www.nauticalcharts.noaa.gov/csdl/mbound.htm.For the full FGDC metadata record, see http://www.ncddc.noaa.gov/approved_recs/nos_de/ocs/ocs/ocs/MB_ParentDataset.html.Coordinates for the US/Canada international boundary, on land and through the Great Lakes, are managed by the International Boundary Commission. These boundaries are included with this dataset for continuity.

Copyright Text: National Oceanic and Atmospheric Administration (NOAA), National Ocean Service (NOS), Office of Coast Survey (OCS)

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Description: Essential Fish Habitat are those areas that have been identified and described by species and lifestage. Fish require healthy surroundings to survive and reproduce. Essential fish haitat includes all types of aquatic habitat - wetlands, coral reefs, sea-grasses, rivers - where fish spawn, breed, feed, or growh to maturity. EFH Mapper Data is a combination of three existing data layers: Essential Fish Habitat (EFH), Habitat Areas of Particular Concern (HAPC) and EFH Areas Protected from Fishing (EFHA).

Copyright Text: NOAA Fisheries / Office of Habitat Conservation / Habitat Protection Division

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Copyright Text: NOAA Fisheries / Office of Habitat Conservation / Habitat Protection Division

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Copyright Text: Bureau of Ocean Energy Management (BOEM)

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Description: This data set contains BOEM Planning Area outlines in ESRI Arc/Info export and Arc/View shape file formats for the BOEM Pacific Region. The use of Planning Areas makes it easier to refer to Official Protraction Diagrams (OPD) and individual blocks within a region. The digital Planning Area outlines were constructed from the block coverage by using Arc/Info s dissolve command. Because GIS projection and topology functions can change or generalize coordinates, these GIS files are NOT an OFFICIAL record for the exact Planning Area boundaries.

Copyright Text: Bureau of Ocean Energy Management (BOEM)

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Layer: BOEM Wind Energy Call Areas (223)

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Name: BOEM Wind Energy Call Areas

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Description: The Bureau of Ocean Energy Management (BOEM) published a Call for Information and Nominations (Call) on October 19, 2018 to obtain nominations from companies interested in commercial wind energy leases within the proposed areas off central and northern California. In addition to nominations, BOEM will seek public input on the potential for wind energy development in the Call Areas. This includes site conditions, resources, and multiple uses in close proximity to, or within, the Call Areas that would be relevant to BOEM’s review of any nominations submitted, as well as BOEM’s subsequent decision whether to offer all or part of the Call Areas for commercial wind leasing.

Copyright Text: Bureau of Ocean Energy Management (BOEM)

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Layer: Infrastructure (300)

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Description: These datasets include the locations of oil platforms, submarine cables, and shipping lanes along the U.S. West Coast.

Copyright Text: National Oceanic and Atmospheric Administration (NOAA), Bureau of Ocean Energy Management (BOEM)

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Layer: Oil Platforms (301)

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Description: Bureau of Ocean Energy Management Pacific OCS Platforms as of August 24, 2010

Copyright Text: BOEM Pacific OCS Region, Office of Production, Development, and Resource Evaluation

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Layer: Submarine Cables (302)

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Description: These data depict the occurrence of submarine cables in and around U.S. navigable waters. The purpose of this data product is to support coastal planning at the regional and national scale. Source geometry and attributes were derived from 2010 NOAA Electronic Navigation Charts and 2009 NOAA Raster Nautical Charts. Polyline features explicitly defined as cables were compiled from the original sources, exclusive of those features noted as 'cable areas'. The scale of the source material was highly variable and discontinuities between multiple sources were resolved with least possible spatial adjustments. The original S-57 data model was modified for readability and performance.

Copyright Text: National Oceanic and Atmospheric Administration (NOAA)

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Layer: Shipping Lanes (303)

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Description: Various shipping zones delineate activities and regulations for marine vessel traffic. Traffic lanes define specific traffic flow, while traffic separation zones assist opposing streams of marine traffic. Precautionary areas represent areas where ships must navigate with caution, and shipping safety fairways designate where artificial structures are prohibited. Recommended Routes are predetermined routes for shipping adopted for reasons of safety. Along certain zones of the East Coast of the United States, ships are required to reduce speeds to 10 knots or less over ground during seasonal periods within designated endangered species areas, such as the North Atlantic Right Whales. Particularly Sensitive Sea Areas need special protection because of their vulnerability to damage by international maritime activities. Areas to be avoided are within defined limits where navigation is particularly hazardous or it is exceptionally important to avoid casualties and should be avoided by all ships or certain classes of ships.

Copyright Text: National Oceanic and Atmospheric Administration (NOAA) Office of Coast Survey

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Layer: In Situ (400)

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Description: These datasets include the locations of deep sea corals and sponges along the U.S. West Coast along with all known visual surveys employing remotely operated vehicles (ROV) or autonomous underwater vehicles (AUV) conducted.

Copyright Text: National Oceanic and Atmospheric Administration (NOAA), Deep Sea Coral Research and Technology Program (DSCRTP), Channel Islands National Marine Sanctuary (CINMS)

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Layer: Presences - Deep Sea Coral and Sponges (401)

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Name: Presences - Deep Sea Coral and Sponges

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Description: These datasets include the locations of various deep-sea coral and sponge taxa along the U.S. West Coast as documented within NOAA’s Deep-Sea Coral Research and Technology Program (DSCRTP) national geodatabase.

Copyright Text: National Oceanic and Atmospheric Administration (NOAA), Deep-Sea Coral Research and Technology Program

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Layer: All taxa (402)

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Description: This data layer depicts point (samples, observations) data from NOAA’s Deep-Sea Coral Research and Technology Program (DSCRTP) national geodatabase of the known locations of deep-sea corals and sponges in U.S. territorial waters and beyond. The structure of the database is tailored to occurrence records of all the azooxanthellate corals, a subset of all corals, and all sponge species. Records shallower than 50 m are generally excluded in order to focus on predominantly deep-water species the mandate of the DSCRTP. The intention is to limit the overlap with light-dependent (and mostly shallow-water) corals.

Copyright Text: Deep-Sea Coral Research and Technology Program (DSCRTP)

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Copyright Text: Bishop Museum Invertebrate Zoology Collection, Bureau of Ocean Energy Management, California Academy of Sciences, Dauphin Island Sea Lab, Giamonna et al. 1978, Hall-Spencer, J., Harbor Branch Oceanographic Institute, Hawaii Undersea Research Laboratory, Hexacorallians of the World, Monterey Bay Aquarium Research Institute, National Undersea Research Center, National Oceanographic and Atmospheric Administration, NOAA Alaska Fisheries Science Center, NOAA Center for Coastal Environmental Health and Biomolecular Research, NOAA Channel Islands National Marine Sanctuary, NOAA Cordell Bank National Marine Sanctuary, NOAA Flower Garden Banks National Marine Sanctuary, NOAA Gulf of Farallones National Marine Sanctuary, NOAA Northeast Fisheries Science Center, NOAA Northwest Fisheries Science Center, NOAA Office of Exploration and Research, NOAA Office of Response and Restoration, NOAA Olympic Coast National Marine Sanctuary, NOAA Southeast Fisheries Science Center, NOAA Southwest Fisheries Science Center, Ocean Biogeographic Information System USA, Oceana, A. Quattrini, Santa Barbara Museum of Natural History, Schmidt Ocean Institute, SeamountsOnline, Smithsonian Institution National Museum of Natural History, Texas A+M University, United States Geological Survey, Washington State University, Yale University Peabody Museum

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Parent Layer: Presences - Deep Sea Coral and Sponges

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Copyright Text: Deep-Sea Coral Research and Technology Program (DSCRTP)

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Copyright Text: Deep-Sea Coral Research and Technology Program (DSCRTP)

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Layer: Anthomastus (406)

Parent Layer: Presences - Deep Sea Coral and Sponges

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Copyright Text: Deep-Sea Coral Research and Technology Program (DSCRTP)

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Parent Layer: Presences - Deep Sea Coral and Sponges

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Copyright Text: Deep-Sea Coral Research and Technology Program (DSCRTP)

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Parent Layer: Presences - Deep Sea Coral and Sponges

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Copyright Text: Deep-Sea Coral Research and Technology Program (DSCRTP)

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Copyright Text: Deep-Sea Coral Research and Technology Program (DSCRTP)

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Parent Layer: Presences - Deep Sea Coral and Sponges

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Copyright Text: Deep-Sea Coral Research and Technology Program (DSCRTP)

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Parent Layer: Presences - Deep Sea Coral and Sponges

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Copyright Text: Deep-Sea Coral Research and Technology Program (DSCRTP)

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Parent Layer: Presences - Deep Sea Coral and Sponges

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Copyright Text: Deep-Sea Coral Research and Technology Program (DSCRTP)

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Parent Layer: Presences - Deep Sea Coral and Sponges

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Parent Layer: Presences - Deep Sea Coral and Sponges

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Copyright Text: Deep-Sea Coral Research and Technology Program (DSCRTP)

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Copyright Text: Deep-Sea Coral Research and Technology Program (DSCRTP)

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Copyright Text: Deep-Sea Coral Research and Technology Program (DSCRTP)

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Copyright Text: Deep-Sea Coral Research and Technology Program (DSCRTP)

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Parent Layer: Presences - Deep Sea Coral and Sponges

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Copyright Text: Deep-Sea Coral Research and Technology Program (DSCRTP)

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Parent Layer: Presences - Deep Sea Coral and Sponges

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Parent Layer: Presences - Deep Sea Coral and Sponges

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Copyright Text: Deep-Sea Coral Research and Technology Program (DSCRTP)

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Layer: Paracyathus (443)

Parent Layer: Presences - Deep Sea Coral and Sponges

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Copyright Text: Deep-Sea Coral Research and Technology Program (DSCRTP)

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Parent Layer: Presences - Deep Sea Coral and Sponges

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Copyright Text: Deep-Sea Coral Research and Technology Program (DSCRTP)

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Layer: Parastenella (445)

Parent Layer: Presences - Deep Sea Coral and Sponges

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Copyright Text: Deep-Sea Coral Research and Technology Program (DSCRTP)

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Parent Layer: Presences - Deep Sea Coral and Sponges

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Copyright Text: Deep-Sea Coral Research and Technology Program (DSCRTP)

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Parent Layer: Presences - Deep Sea Coral and Sponges

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Parent Layer: Presences - Deep Sea Coral and Sponges

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Copyright Text: Deep-Sea Coral Research and Technology Program (DSCRTP)

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Parent Layer: Presences - Deep Sea Coral and Sponges

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Copyright Text: Deep-Sea Coral Research and Technology Program (DSCRTP)

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Parent Layer: Presences - Deep Sea Coral and Sponges

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Copyright Text: Deep-Sea Coral Research and Technology Program (DSCRTP)

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Layer: Ptilosarcus (451)

Parent Layer: Presences - Deep Sea Coral and Sponges

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Copyright Text: Deep-Sea Coral Research and Technology Program (DSCRTP)

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Parent Layer: Presences - Deep Sea Coral and Sponges

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Copyright Text: Deep-Sea Coral Research and Technology Program (DSCRTP)

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Parent Layer: Presences - Deep Sea Coral and Sponges

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Copyright Text: Deep-Sea Coral Research and Technology Program (DSCRTP)

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Parent Layer: Presences - Deep Sea Coral and Sponges

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Copyright Text: Deep-Sea Coral Research and Technology Program (DSCRTP)

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Layer: Umbellapathes (458)

Parent Layer: Presences - Deep Sea Coral and Sponges

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Copyright Text: Deep-Sea Coral Research and Technology Program (DSCRTP)

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Parent Layer: Presences - Deep Sea Coral and Sponges

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Copyright Text: Deep-Sea Coral Research and Technology Program (DSCRTP)

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Layer: Virgularia (460)

Parent Layer: Presences - Deep Sea Coral and Sponges

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Description: This data layer depicts point (samples, observations) data from NOAA’s Deep-Sea Coral Research and Technology Program (DSCRTP) national geodatabase of the known locations of deep-sea corals and sponges in U.S. territorial waters and beyond. The structure of the database is tailored to occurrence records of all the azooxanthellate corals, a subset of all corals, and all sponge species. Records shallower than 50 m are generally excluded in order to focus on predominantly deep-water species the mandate of the DSCRTP. The intention is to limit the overlap with light-dependent (and mostly shallow-water) corals.

Copyright Text: Deep-Sea Coral Research and Technology Program (DSCRTP)

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Layer: Visual Surveys (470)

Parent Layer: In Situ

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Description: This data layer depicts all known visual surveys employing remotely operated vehicles (ROV) or autonomous underwater vehicles (AUV) conducted along the U.S. West Coast.

Copyright Text: National Oceanic and Atmospheric Administration (NOAA), NOAA Office for Ocean Exploration and Research (OER), Channel Islands National Marine Sanctuary (CINMS), Oregon Department of Fish and Wildlife (ODFW) Marine Resources Program, United States Geological Survey (USGS)

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Layer: Shipboard Visual Video Observations (471)

Parent Layer: Visual Surveys

Name: Shipboard Visual Video Observations

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Description: This feature layer contains point features representing individual video drop-camera observation locations conducted by the USGS Western Region Coastal and Marine Geology Program and the Oregon Department of Fish and Wildlife (ODFW). The USGS data represents shipboard visual video observations of benthic habitat from cruises C0111SC, C0212SC, C109NC, C210NC, F208NC, F307NC, L908NC, S1C08SC, S2210MB, SW109SC, Z107SC, and Z206SC in California. The vector data files are accessible from http://pubs.usgs.gov/ds/781/video_observations/data_catalog_video_observations.html. The ODFW surveys were conducted by three separate research groups within ODFW between 2009 and 2017. Their purpose included assessment of fish communities and habitats in Marine Reserves and comparison areas, assessment of nearshore rockfish abundance, evaluation of yelloweye rockfish abundance and habitat selection, and other research topics.

Copyright Text: Oregon Department of Fish and Wildlife (ODFW) Marine Resources Program; United States Geological Survey (USGS) Western Region Coastal and Marine Geology Program

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Layer: Visual Survey Transects (472)

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Description: This data layer depicts all known visual surveys employing remotely operated vehicles (ROV) or autonomous underwater vehicles (AUV) conducted by the NOAA Office for Ocean Exploration and Research (OER) and Oregon Department of Fish and Wildlife (2003 and 2017). The purpose of the surveys varied, including groundtruthing previous seafloor geologic habitat classifications and assessing fish and invertebrate communities and associated habitat features.

Copyright Text: National Oceanic and Atmospheric Administration (NOAA), NOAA Office for Ocean National Oceanic and Atmospheric Administration (NOAA), NOAA Office for Ocean Exploration and Research (OER), Channel Islands National Marine Sanctuary (CINMS), Oregon Department of Fish and Wildlife (ODFW) Marine Resources Program

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Layer: Ship Tracklines - E/V Nautilus (699)

Parent Layer: In Situ

Name: Ship Tracklines - E/V Nautilus

Display Field: CruiseName

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Description: This data layer depicts E/V Nautilus ship tracklines.

Copyright Text: National Oceanic and Atmospheric Administration (NOAA), NOAA Office for Ocean Exploration and Research (OER), Channel Islands National Marine Sanctuary (CINMS)

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Description: These datasets include multibeam survey footprints as well as depth contours and a mosaic bathymetry grid created from the same set of multibeam survey products.

Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS); Channel Islands National Marine Sanctuary (CINMS); Oregon Department of Fish and Wildlife (ODFW) Marine Resources Program

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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Layer: Depth - Bathymetry Grid (512)

Parent Layer: Seafloor - Depth

Name: Depth - Bathymetry Grid

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Description: This bathymetry grid was developed from a compilation of various multibeam datasets. All individual datasets were resampled and projected to a 25 x 25 meter grid before building the mosaic dataset. In areas with overlapping coverage, newer and finer resolution datasets were prioritized. The Coastal Relief Model was used in places where multibeam data sources were not available.

Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Layer: Seafloor - Habitats (600)

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Description: These data layers contain the draft outputs of habitat suitability models for deep-sea corals and sponges offshore California, Oregon, and Washington and data layers representing abiotic habitat characteristics such as substrate type and mean grain size.

Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Layer: Abiotic (601)

Parent Layer: Seafloor - Habitats

Sub Layers:
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• CMECS Ecological Marine Units
Name: Abiotic

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Description: These datasets include abiotic habitat characteristics such as mean grain size and substrate type (hard or soft).

Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS), National Oceanic and Atmospheric Administration (NOAA) National Marine Fisheries Service (NMFS) Southwest Fisheries Science Center (SWFSC)

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Layer: Substrate - Mean Grain Size (603)

Parent Layer: Abiotic

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Description: This is an interpolated surface of mean grain size point data created by Bayesian kriiging in ArcPro. Input data sources included US Seabed database (USGS), Oregon State University (OSU), and Southern California Coastal Water Research Project (SCCWRP).

Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Layer: CMECS Ecological Marine Units (703)

Parent Layer: Abiotic

Name: CMECS Ecological Marine Units

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Description: This data set delineates geological seafloor characteristics of the continental margin of the United States West Coast adjacent to Washington, Oregon, and Northern California; see Description for source data (V4_OR_WA_CMECS_Edits_111815) for a complete description.

Copyright Text: Please credit the Oregon State University, Active Tectonics & Seafloor Mapping Lab (AT&SML), NOAA Fisheries Northwest Fisheries Science Center, and the Bureau of Ocean Energy Management when using this dataset. Additional contributions provided by: the Oregon Department of Fish and Wildlife, NOAA Biogeography Branch, The Nature Conservancy, and NatureServe. Additional map product inputs were provided by: the Seafloor Mapping Lab of California State University Monterey Bay, the Center for Habitat Studies at Moss Landing Marine Labs, the Olympic Coast National Marine Sanctuary, and NOAA Fisheries Northwest Fisheries Science Center. Larger Work Citation: Goldfinger C, Henkel, SK, et al. 2014. Benthic Habitat Characterization: Volume 1 Evaluation of Continental Shelf Geology Offshore the Pacific Northwest. US Dept. of the Interior, Bureau of Ocean Energy Management, Pacific OCS Region. OCS Study BOEM 2014-662. 161 pp.

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Layer: Deep Sea Corals and Sponges (604)

Parent Layer: Seafloor - Habitats

Sub Layers:
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Name: Deep Sea Corals and Sponges

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Description: This data package contains the draft outputs of habitat suitability models for deep-sea corals and sponges offshore California, Oregon, and Washington. NCCOS obtained the April 5, 2018 version of the NOAA Deep Sea Coral Research and Technology Program national database of deep-sea corals and sponges and extracted presence locations of deep-sea corals and sponges offshore California, Oregon, and Washington and shallower than the 1200m depth contour. The project science team identified 44 taxa of deep-sea coral and sponges with sufficient presence locations to develop habitat suitability models. For each taxon, the R package ‘maxnet’ was used to fit models of habitat suitability using the values of the environmental covariates at locations of deep-sea coral or sponge occurrence. A stepwise model selection procedure was performed to select a final model for each taxon that balanced model predictive performance with model complexity. The set of environmental covariates in the final model was used to fit models to ten bootstrap samples to generate spatially explicit predictions of the relative likelihood of habitat suitability. Outputs from these predictions include the mean prediction across the models fit to the ten bootstrap samples, the coefficient of variation across the predictions, a classified prediction created by reclassifying the mean prediction into classes of increasing likelihood of habitat suitability, and a “robust” very high likelihood prediction that indicates grid cells for which all the models fit to the bootstrap samples were classified as having a very high likelihood of containing suitable habitat.

Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Layer: Robust Very High Likelihood Predictions (605)

Parent Layer: Deep Sea Corals and Sponges

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• Acanthoptilum - Robust Very High Likelihood
• Adelogorgia phyllosclera - Robust Very High Likelihood
• Anthoptilum - Robust Very High Likelihood
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• Aphrocallistes vastus - Robust Very High Likelihood
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• Balanophyllia - Robust Very High Likelihood
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• Clavularia - Robust Very High Likelihood
• Coenocyathus bowersi - Robust Very High Likelihood
• Demospongiae - Robust Very High Likelihood
• Desmophyllum - Robust Very High Likelihood
• Distichoptilum - Robust Very High Likelihood
• Eugorgia - Robust Very High Likelihood
• Farrea occa - Robust Very High Likelihood
• Funiculina - Robust Very High Likelihood
• Halipteris californica - Robust Very High Likelihood
• Halipteris - Robust Very High Likelihood
• Heterochone calyx - Robust Very High Likelihood
• Heteropolypus ritteri - Robust Very High Likelihood
• Hexactinellida - Robust Very High Likelihood
• Hyalonema - Robust Very High Likelihood
• Isidella - Robust Very High Likelihood
• Leptogorgia - Robust Very High Likelihood
• Lophelia pertusa - Robust Very High Likelihood
• Paracyathus - Robust Very High Likelihood
• Paragorgia - Robust Very High Likelihood
• Parastenella - Robust Very High Likelihood
• Pennatula - Robust Very High Likelihood
• Plumarella - Robust Very High Likelihood
• Polymastia - Robust Very High Likelihood
• Psammogorgia - Robust Very High Likelihood
• Ptilosarcus - Robust Very High Likelihood
• Stylaster californicus - Robust Very High Likelihood
• Stylaster - Robust Very High Likelihood
• Stylatula - Robust Very High Likelihood
• Swiftia kofoidi - Robust Very High Likelihood
• Swiftia pacifica - Robust Very High Likelihood
• Swiftia simplex - Robust Very High Likelihood
• Umbellula - Robust Very High Likelihood
• Virgularia - Robust Very High Likelihood
Name: Robust Very High Likelihood Predictions

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Description: These data layers include the draft outputs of habitat suitability models for deep-sea corals and sponges offshore California, Oregon, and Washington. Depicted are the “robust” very high likelihood predictions for each taxon that indicates grid cells for which all the models fit to the bootstrap samples were classified as having a very high likelihood of containing suitable habitat.

Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Layer: Acanthogorgia - Robust Very High Likelihood Prediction (700)

Parent Layer: Robust Very High Likelihood Predictions

Name: Acanthogorgia - Robust Very High Likelihood Prediction

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Description: This data layer contains the draft output of the habitat suitability models for the taxon group Acanthogorgia offshore California, Oregon, and Washington. Depicted is a “robust” very high likelihood prediction that indicates grid cells for which all the models fit to the bootstrap samples were classified as having a very high likelihood of containing suitable habitat.

Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Layer: Acanthoptilum - Robust Very High Likelihood (241)

Parent Layer: Robust Very High Likelihood Predictions

Name: Acanthoptilum - Robust Very High Likelihood

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Description: This data layer contains the draft output of the habitat suitability models for the taxon group Acanthoptilum offshore California, Oregon, and Washington. Depicted is a “robust” very high likelihood prediction that indicates grid cells for which all the models fit to the bootstrap samples were classified as having a very high likelihood of containing suitable habitat. NCCOS obtained the April 5, 2018 version of the NOAA Deep Sea Coral Research and Technology Program national database of deep-sea corals and sponges and extracted presence locations of deep-sea corals and sponges offshore California, Oregon, and Washington and shallower than the 1200m depth contour. The project science team identified 44 taxa of deep-sea coral and sponges with sufficient presence locations to develop habitat suitability models. For each taxon, the R package ‘maxnet’ was used to fit models of habitat suitability using the values of the environmental covariates at locations of deep-sea coral or sponge occurrence. A stepwise model selection procedure was performed to select a final model for each taxon that balanced model predictive performance with model complexity. The set of environmental covariates in the final model was used to fit models to ten bootstrap samples to generate spatially explicit predictions of the relative likelihood of habitat suitability. Outputs from these predictions include the mean prediction across the models fit to the ten bootstrap samples, the coefficient of variation across the predictions, a classified prediction created by reclassifying the mean prediction into classes of increasing likelihood of habitat suitability, and a “robust” very high likelihood prediction that indicates grid cells for which all the models fit to the bootstrap samples were classified as having a very high likelihood of containing suitable habitat.

Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Layer: Adelogorgia phyllosclera - Robust Very High Likelihood (608)

Parent Layer: Robust Very High Likelihood Predictions

Name: Adelogorgia phyllosclera - Robust Very High Likelihood

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Description: This data layer contains the draft output of the habitat suitability models for the taxon group Adelogorgia phyllosclera offshore California, Oregon, and Washington. Depicted is a “robust” very high likelihood prediction that indicates grid cells for which all the models fit to the bootstrap samples were classified as having a very high likelihood of containing suitable habitat. NCCOS obtained the April 5, 2018 version of the NOAA Deep Sea Coral Research and Technology Program national database of deep-sea corals and sponges and extracted presence locations of deep-sea corals and sponges offshore California, Oregon, and Washington and shallower than the 1200m depth contour. The project science team identified 44 taxa of deep-sea coral and sponges with sufficient presence locations to develop habitat suitability models. For each taxon, the R package ‘maxnet’ was used to fit models of habitat suitability using the values of the environmental covariates at locations of deep-sea coral or sponge occurrence. A stepwise model selection procedure was performed to select a final model for each taxon that balanced model predictive performance with model complexity. The set of environmental covariates in the final model was used to fit models to ten bootstrap samples to generate spatially explicit predictions of the relative likelihood of habitat suitability. Outputs from these predictions include the mean prediction across the models fit to the ten bootstrap samples, the coefficient of variation across the predictions, a classified prediction created by reclassifying the mean prediction into classes of increasing likelihood of habitat suitability, and a “robust” very high likelihood prediction that indicates grid cells for which all the models fit to the bootstrap samples were classified as having a very high likelihood of containing suitable habitat.

Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Layer: Anthoptilum - Robust Very High Likelihood (609)

Parent Layer: Robust Very High Likelihood Predictions

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Description: This data layer contains the draft output of the habitat suitability models for the taxon group Anthoptilum offshore California, Oregon, and Washington. Depicted is a “robust” very high likelihood prediction that indicates grid cells for which all the models fit to the bootstrap samples were classified as having a very high likelihood of containing suitable habitat. NCCOS obtained the April 5, 2018 version of the NOAA Deep Sea Coral Research and Technology Program national database of deep-sea corals and sponges and extracted presence locations of deep-sea corals and sponges offshore California, Oregon, and Washington and shallower than the 1200m depth contour. The project science team identified 44 taxa of deep-sea coral and sponges with sufficient presence locations to develop habitat suitability models. For each taxon, the R package ‘maxnet’ was used to fit models of habitat suitability using the values of the environmental covariates at locations of deep-sea coral or sponge occurrence. A stepwise model selection procedure was performed to select a final model for each taxon that balanced model predictive performance with model complexity. The set of environmental covariates in the final model was used to fit models to ten bootstrap samples to generate spatially explicit predictions of the relative likelihood of habitat suitability. Outputs from these predictions include the mean prediction across the models fit to the ten bootstrap samples, the coefficient of variation across the predictions, a classified prediction created by reclassifying the mean prediction into classes of increasing likelihood of habitat suitability, and a “robust” very high likelihood prediction that indicates grid cells for which all the models fit to the bootstrap samples were classified as having a very high likelihood of containing suitable habitat.

Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Layer: Antipathes dendrochristos - Robust Very High Likelihood (610)

Parent Layer: Robust Very High Likelihood Predictions

Name: Antipathes dendrochristos - Robust Very High Likelihood

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Description: This data layer contains the draft output of the habitat suitability models for the taxon group Antipathes dendrochristos offshore California, Oregon, and Washington. Depicted is a “robust” very high likelihood prediction that indicates grid cells for which all the models fit to the bootstrap samples were classified as having a very high likelihood of containing suitable habitat. NCCOS obtained the April 5, 2018 version of the NOAA Deep Sea Coral Research and Technology Program national database of deep-sea corals and sponges and extracted presence locations of deep-sea corals and sponges offshore California, Oregon, and Washington and shallower than the 1200m depth contour. The project science team identified 44 taxa of deep-sea coral and sponges with sufficient presence locations to develop habitat suitability models. For each taxon, the R package ‘maxnet’ was used to fit models of habitat suitability using the values of the environmental covariates at locations of deep-sea coral or sponge occurrence. A stepwise model selection procedure was performed to select a final model for each taxon that balanced model predictive performance with model complexity. The set of environmental covariates in the final model was used to fit models to ten bootstrap samples to generate spatially explicit predictions of the relative likelihood of habitat suitability. Outputs from these predictions include the mean prediction across the models fit to the ten bootstrap samples, the coefficient of variation across the predictions, a classified prediction created by reclassifying the mean prediction into classes of increasing likelihood of habitat suitability, and a “robust” very high likelihood prediction that indicates grid cells for which all the models fit to the bootstrap samples were classified as having a very high likelihood of containing suitable habitat.

Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Description: This data layer contains the draft output of the habitat suitability models for the taxon group Distichoptilum offshore California, Oregon, and Washington. Depicted is a “robust” very high likelihood prediction that indicates grid cells for which all the models fit to the bootstrap samples were classified as having a very high likelihood of containing suitable habitat. NCCOS obtained the April 5, 2018 version of the NOAA Deep Sea Coral Research and Technology Program national database of deep-sea corals and sponges and extracted presence locations of deep-sea corals and sponges offshore California, Oregon, and Washington and shallower than the 1200m depth contour. The project science team identified 44 taxa of deep-sea coral and sponges with sufficient presence locations to develop habitat suitability models. For each taxon, the R package ‘maxnet’ was used to fit models of habitat suitability using the values of the environmental covariates at locations of deep-sea coral or sponge occurrence. A stepwise model selection procedure was performed to select a final model for each taxon that balanced model predictive performance with model complexity. The set of environmental covariates in the final model was used to fit models to ten bootstrap samples to generate spatially explicit predictions of the relative likelihood of habitat suitability. Outputs from these predictions include the mean prediction across the models fit to the ten bootstrap samples, the coefficient of variation across the predictions, a classified prediction created by reclassifying the mean prediction into classes of increasing likelihood of habitat suitability, and a “robust” very high likelihood prediction that indicates grid cells for which all the models fit to the bootstrap samples were classified as having a very high likelihood of containing suitable habitat.

Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Description: This data layer contains the draft output of the habitat suitability models for the taxon group Eugorgia offshore California, Oregon, and Washington. Depicted is a “robust” very high likelihood prediction that indicates grid cells for which all the models fit to the bootstrap samples were classified as having a very high likelihood of containing suitable habitat. NCCOS obtained the April 5, 2018 version of the NOAA Deep Sea Coral Research and Technology Program national database of deep-sea corals and sponges and extracted presence locations of deep-sea corals and sponges offshore California, Oregon, and Washington and shallower than the 1200m depth contour. The project science team identified 44 taxa of deep-sea coral and sponges with sufficient presence locations to develop habitat suitability models. For each taxon, the R package ‘maxnet’ was used to fit models of habitat suitability using the values of the environmental covariates at locations of deep-sea coral or sponge occurrence. A stepwise model selection procedure was performed to select a final model for each taxon that balanced model predictive performance with model complexity. The set of environmental covariates in the final model was used to fit models to ten bootstrap samples to generate spatially explicit predictions of the relative likelihood of habitat suitability. Outputs from these predictions include the mean prediction across the models fit to the ten bootstrap samples, the coefficient of variation across the predictions, a classified prediction created by reclassifying the mean prediction into classes of increasing likelihood of habitat suitability, and a “robust” very high likelihood prediction that indicates grid cells for which all the models fit to the bootstrap samples were classified as having a very high likelihood of containing suitable habitat.

Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Description: This data layer contains the draft output of the habitat suitability models for the taxon group Farrea occa offshore California, Oregon, and Washington. Depicted is a “robust” very high likelihood prediction that indicates grid cells for which all the models fit to the bootstrap samples were classified as having a very high likelihood of containing suitable habitat. NCCOS obtained the April 5, 2018 version of the NOAA Deep Sea Coral Research and Technology Program national database of deep-sea corals and sponges and extracted presence locations of deep-sea corals and sponges offshore California, Oregon, and Washington and shallower than the 1200m depth contour. The project science team identified 44 taxa of deep-sea coral and sponges with sufficient presence locations to develop habitat suitability models. For each taxon, the R package ‘maxnet’ was used to fit models of habitat suitability using the values of the environmental covariates at locations of deep-sea coral or sponge occurrence. A stepwise model selection procedure was performed to select a final model for each taxon that balanced model predictive performance with model complexity. The set of environmental covariates in the final model was used to fit models to ten bootstrap samples to generate spatially explicit predictions of the relative likelihood of habitat suitability. Outputs from these predictions include the mean prediction across the models fit to the ten bootstrap samples, the coefficient of variation across the predictions, a classified prediction created by reclassifying the mean prediction into classes of increasing likelihood of habitat suitability, and a “robust” very high likelihood prediction that indicates grid cells for which all the models fit to the bootstrap samples were classified as having a very high likelihood of containing suitable habitat.

Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Description: This data layer contains the draft output of the habitat suitability models for the taxon group Halipteris californica offshore California, Oregon, and Washington. Depicted is a “robust” very high likelihood prediction that indicates grid cells for which all the models fit to the bootstrap samples were classified as having a very high likelihood of containing suitable habitat. NCCOS obtained the April 5, 2018 version of the NOAA Deep Sea Coral Research and Technology Program national database of deep-sea corals and sponges and extracted presence locations of deep-sea corals and sponges offshore California, Oregon, and Washington and shallower than the 1200m depth contour. The project science team identified 44 taxa of deep-sea coral and sponges with sufficient presence locations to develop habitat suitability models. For each taxon, the R package ‘maxnet’ was used to fit models of habitat suitability using the values of the environmental covariates at locations of deep-sea coral or sponge occurrence. A stepwise model selection procedure was performed to select a final model for each taxon that balanced model predictive performance with model complexity. The set of environmental covariates in the final model was used to fit models to ten bootstrap samples to generate spatially explicit predictions of the relative likelihood of habitat suitability. Outputs from these predictions include the mean prediction across the models fit to the ten bootstrap samples, the coefficient of variation across the predictions, a classified prediction created by reclassifying the mean prediction into classes of increasing likelihood of habitat suitability, and a “robust” very high likelihood prediction that indicates grid cells for which all the models fit to the bootstrap samples were classified as having a very high likelihood of containing suitable habitat.

Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Description: This data layer contains the draft output of the habitat suitability models for the taxon group Halipteris offshore California, Oregon, and Washington. Depicted is a “robust” very high likelihood prediction that indicates grid cells for which all the models fit to the bootstrap samples were classified as having a very high likelihood of containing suitable habitat. NCCOS obtained the April 5, 2018 version of the NOAA Deep Sea Coral Research and Technology Program national database of deep-sea corals and sponges and extracted presence locations of deep-sea corals and sponges offshore California, Oregon, and Washington and shallower than the 1200m depth contour. The project science team identified 44 taxa of deep-sea coral and sponges with sufficient presence locations to develop habitat suitability models. For each taxon, the R package ‘maxnet’ was used to fit models of habitat suitability using the values of the environmental covariates at locations of deep-sea coral or sponge occurrence. A stepwise model selection procedure was performed to select a final model for each taxon that balanced model predictive performance with model complexity. The set of environmental covariates in the final model was used to fit models to ten bootstrap samples to generate spatially explicit predictions of the relative likelihood of habitat suitability. Outputs from these predictions include the mean prediction across the models fit to the ten bootstrap samples, the coefficient of variation across the predictions, a classified prediction created by reclassifying the mean prediction into classes of increasing likelihood of habitat suitability, and a “robust” very high likelihood prediction that indicates grid cells for which all the models fit to the bootstrap samples were classified as having a very high likelihood of containing suitable habitat.

Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Layer: Heterochone calyx - Robust Very High Likelihood (628)

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Description: This data layer contains the draft output of the habitat suitability models for the taxon group Heterochone calyx offshore California, Oregon, and Washington. Depicted is a “robust” very high likelihood prediction that indicates grid cells for which all the models fit to the bootstrap samples were classified as having a very high likelihood of containing suitable habitat. NCCOS obtained the April 5, 2018 version of the NOAA Deep Sea Coral Research and Technology Program national database of deep-sea corals and sponges and extracted presence locations of deep-sea corals and sponges offshore California, Oregon, and Washington and shallower than the 1200m depth contour. The project science team identified 44 taxa of deep-sea coral and sponges with sufficient presence locations to develop habitat suitability models. For each taxon, the R package ‘maxnet’ was used to fit models of habitat suitability using the values of the environmental covariates at locations of deep-sea coral or sponge occurrence. A stepwise model selection procedure was performed to select a final model for each taxon that balanced model predictive performance with model complexity. The set of environmental covariates in the final model was used to fit models to ten bootstrap samples to generate spatially explicit predictions of the relative likelihood of habitat suitability. Outputs from these predictions include the mean prediction across the models fit to the ten bootstrap samples, the coefficient of variation across the predictions, a classified prediction created by reclassifying the mean prediction into classes of increasing likelihood of habitat suitability, and a “robust” very high likelihood prediction that indicates grid cells for which all the models fit to the bootstrap samples were classified as having a very high likelihood of containing suitable habitat.

Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Layer: Heteropolypus ritteri - Robust Very High Likelihood (629)

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Description: This data layer contains the draft output of the habitat suitability models for the taxon group Heteropolypus ritteri offshore California, Oregon, and Washington. Depicted is a “robust” very high likelihood prediction that indicates grid cells for which all the models fit to the bootstrap samples were classified as having a very high likelihood of containing suitable habitat. NCCOS obtained the April 5, 2018 version of the NOAA Deep Sea Coral Research and Technology Program national database of deep-sea corals and sponges and extracted presence locations of deep-sea corals and sponges offshore California, Oregon, and Washington and shallower than the 1200m depth contour. The project science team identified 44 taxa of deep-sea coral and sponges with sufficient presence locations to develop habitat suitability models. For each taxon, the R package ‘maxnet’ was used to fit models of habitat suitability using the values of the environmental covariates at locations of deep-sea coral or sponge occurrence. A stepwise model selection procedure was performed to select a final model for each taxon that balanced model predictive performance with model complexity. The set of environmental covariates in the final model was used to fit models to ten bootstrap samples to generate spatially explicit predictions of the relative likelihood of habitat suitability. Outputs from these predictions include the mean prediction across the models fit to the ten bootstrap samples, the coefficient of variation across the predictions, a classified prediction created by reclassifying the mean prediction into classes of increasing likelihood of habitat suitability, and a “robust” very high likelihood prediction that indicates grid cells for which all the models fit to the bootstrap samples were classified as having a very high likelihood of containing suitable habitat.

Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Description: This data layer contains the draft output of the habitat suitability models for the taxon group Hexactinellida offshore California, Oregon, and Washington. Depicted is a “robust” very high likelihood prediction that indicates grid cells for which all the models fit to the bootstrap samples were classified as having a very high likelihood of containing suitable habitat. NCCOS obtained the April 5, 2018 version of the NOAA Deep Sea Coral Research and Technology Program national database of deep-sea corals and sponges and extracted presence locations of deep-sea corals and sponges offshore California, Oregon, and Washington and shallower than the 1200m depth contour. The project science team identified 44 taxa of deep-sea coral and sponges with sufficient presence locations to develop habitat suitability models. For each taxon, the R package ‘maxnet’ was used to fit models of habitat suitability using the values of the environmental covariates at locations of deep-sea coral or sponge occurrence. A stepwise model selection procedure was performed to select a final model for each taxon that balanced model predictive performance with model complexity. The set of environmental covariates in the final model was used to fit models to ten bootstrap samples to generate spatially explicit predictions of the relative likelihood of habitat suitability. Outputs from these predictions include the mean prediction across the models fit to the ten bootstrap samples, the coefficient of variation across the predictions, a classified prediction created by reclassifying the mean prediction into classes of increasing likelihood of habitat suitability, and a “robust” very high likelihood prediction that indicates grid cells for which all the models fit to the bootstrap samples were classified as having a very high likelihood of containing suitable habitat.

Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Description: This data layer contains the draft output of the habitat suitability models for the taxon group Isidella offshore California, Oregon, and Washington. Depicted is a “robust” very high likelihood prediction that indicates grid cells for which all the models fit to the bootstrap samples were classified as having a very high likelihood of containing suitable habitat. NCCOS obtained the April 5, 2018 version of the NOAA Deep Sea Coral Research and Technology Program national database of deep-sea corals and sponges and extracted presence locations of deep-sea corals and sponges offshore California, Oregon, and Washington and shallower than the 1200m depth contour. The project science team identified 44 taxa of deep-sea coral and sponges with sufficient presence locations to develop habitat suitability models. For each taxon, the R package ‘maxnet’ was used to fit models of habitat suitability using the values of the environmental covariates at locations of deep-sea coral or sponge occurrence. A stepwise model selection procedure was performed to select a final model for each taxon that balanced model predictive performance with model complexity. The set of environmental covariates in the final model was used to fit models to ten bootstrap samples to generate spatially explicit predictions of the relative likelihood of habitat suitability. Outputs from these predictions include the mean prediction across the models fit to the ten bootstrap samples, the coefficient of variation across the predictions, a classified prediction created by reclassifying the mean prediction into classes of increasing likelihood of habitat suitability, and a “robust” very high likelihood prediction that indicates grid cells for which all the models fit to the bootstrap samples were classified as having a very high likelihood of containing suitable habitat.

Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Description: This data layer contains the draft output of the habitat suitability models for the taxon group Leptogorgia offshore California, Oregon, and Washington. Depicted is a “robust” very high likelihood prediction that indicates grid cells for which all the models fit to the bootstrap samples were classified as having a very high likelihood of containing suitable habitat. NCCOS obtained the April 5, 2018 version of the NOAA Deep Sea Coral Research and Technology Program national database of deep-sea corals and sponges and extracted presence locations of deep-sea corals and sponges offshore California, Oregon, and Washington and shallower than the 1200m depth contour. The project science team identified 44 taxa of deep-sea coral and sponges with sufficient presence locations to develop habitat suitability models. For each taxon, the R package ‘maxnet’ was used to fit models of habitat suitability using the values of the environmental covariates at locations of deep-sea coral or sponge occurrence. A stepwise model selection procedure was performed to select a final model for each taxon that balanced model predictive performance with model complexity. The set of environmental covariates in the final model was used to fit models to ten bootstrap samples to generate spatially explicit predictions of the relative likelihood of habitat suitability. Outputs from these predictions include the mean prediction across the models fit to the ten bootstrap samples, the coefficient of variation across the predictions, a classified prediction created by reclassifying the mean prediction into classes of increasing likelihood of habitat suitability, and a “robust” very high likelihood prediction that indicates grid cells for which all the models fit to the bootstrap samples were classified as having a very high likelihood of containing suitable habitat.

Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Description: This data layer contains the draft output of the habitat suitability models for the taxon group Lophelia pertusa offshore California, Oregon, and Washington. Depicted is a “robust” very high likelihood prediction that indicates grid cells for which all the models fit to the bootstrap samples were classified as having a very high likelihood of containing suitable habitat. NCCOS obtained the April 5, 2018 version of the NOAA Deep Sea Coral Research and Technology Program national database of deep-sea corals and sponges and extracted presence locations of deep-sea corals and sponges offshore California, Oregon, and Washington and shallower than the 1200m depth contour. The project science team identified 44 taxa of deep-sea coral and sponges with sufficient presence locations to develop habitat suitability models. For each taxon, the R package ‘maxnet’ was used to fit models of habitat suitability using the values of the environmental covariates at locations of deep-sea coral or sponge occurrence. A stepwise model selection procedure was performed to select a final model for each taxon that balanced model predictive performance with model complexity. The set of environmental covariates in the final model was used to fit models to ten bootstrap samples to generate spatially explicit predictions of the relative likelihood of habitat suitability. Outputs from these predictions include the mean prediction across the models fit to the ten bootstrap samples, the coefficient of variation across the predictions, a classified prediction created by reclassifying the mean prediction into classes of increasing likelihood of habitat suitability, and a “robust” very high likelihood prediction that indicates grid cells for which all the models fit to the bootstrap samples were classified as having a very high likelihood of containing suitable habitat.

Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Description: This data layer contains the draft output of the habitat suitability models for the taxon group Paracyathus offshore California, Oregon, and Washington. Depicted is a “robust” very high likelihood prediction that indicates grid cells for which all the models fit to the bootstrap samples were classified as having a very high likelihood of containing suitable habitat. NCCOS obtained the April 5, 2018 version of the NOAA Deep Sea Coral Research and Technology Program national database of deep-sea corals and sponges and extracted presence locations of deep-sea corals and sponges offshore California, Oregon, and Washington and shallower than the 1200m depth contour. The project science team identified 44 taxa of deep-sea coral and sponges with sufficient presence locations to develop habitat suitability models. For each taxon, the R package ‘maxnet’ was used to fit models of habitat suitability using the values of the environmental covariates at locations of deep-sea coral or sponge occurrence. A stepwise model selection procedure was performed to select a final model for each taxon that balanced model predictive performance with model complexity. The set of environmental covariates in the final model was used to fit models to ten bootstrap samples to generate spatially explicit predictions of the relative likelihood of habitat suitability. Outputs from these predictions include the mean prediction across the models fit to the ten bootstrap samples, the coefficient of variation across the predictions, a classified prediction created by reclassifying the mean prediction into classes of increasing likelihood of habitat suitability, and a “robust” very high likelihood prediction that indicates grid cells for which all the models fit to the bootstrap samples were classified as having a very high likelihood of containing suitable habitat.

Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Description: This data layer contains the draft output of the habitat suitability models for the taxon group Paragorgia offshore California, Oregon, and Washington. Depicted is a “robust” very high likelihood prediction that indicates grid cells for which all the models fit to the bootstrap samples were classified as having a very high likelihood of containing suitable habitat. NCCOS obtained the April 5, 2018 version of the NOAA Deep Sea Coral Research and Technology Program national database of deep-sea corals and sponges and extracted presence locations of deep-sea corals and sponges offshore California, Oregon, and Washington and shallower than the 1200m depth contour. The project science team identified 44 taxa of deep-sea coral and sponges with sufficient presence locations to develop habitat suitability models. For each taxon, the R package ‘maxnet’ was used to fit models of habitat suitability using the values of the environmental covariates at locations of deep-sea coral or sponge occurrence. A stepwise model selection procedure was performed to select a final model for each taxon that balanced model predictive performance with model complexity. The set of environmental covariates in the final model was used to fit models to ten bootstrap samples to generate spatially explicit predictions of the relative likelihood of habitat suitability. Outputs from these predictions include the mean prediction across the models fit to the ten bootstrap samples, the coefficient of variation across the predictions, a classified prediction created by reclassifying the mean prediction into classes of increasing likelihood of habitat suitability, and a “robust” very high likelihood prediction that indicates grid cells for which all the models fit to the bootstrap samples were classified as having a very high likelihood of containing suitable habitat.

Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Description: This data layer contains the draft output of the habitat suitability models for the taxon group Parastenella offshore California, Oregon, and Washington. Depicted is a “robust” very high likelihood prediction that indicates grid cells for which all the models fit to the bootstrap samples were classified as having a very high likelihood of containing suitable habitat. NCCOS obtained the April 5, 2018 version of the NOAA Deep Sea Coral Research and Technology Program national database of deep-sea corals and sponges and extracted presence locations of deep-sea corals and sponges offshore California, Oregon, and Washington and shallower than the 1200m depth contour. The project science team identified 44 taxa of deep-sea coral and sponges with sufficient presence locations to develop habitat suitability models. For each taxon, the R package ‘maxnet’ was used to fit models of habitat suitability using the values of the environmental covariates at locations of deep-sea coral or sponge occurrence. A stepwise model selection procedure was performed to select a final model for each taxon that balanced model predictive performance with model complexity. The set of environmental covariates in the final model was used to fit models to ten bootstrap samples to generate spatially explicit predictions of the relative likelihood of habitat suitability. Outputs from these predictions include the mean prediction across the models fit to the ten bootstrap samples, the coefficient of variation across the predictions, a classified prediction created by reclassifying the mean prediction into classes of increasing likelihood of habitat suitability, and a “robust” very high likelihood prediction that indicates grid cells for which all the models fit to the bootstrap samples were classified as having a very high likelihood of containing suitable habitat.

Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Description: This data layer contains the draft output of the habitat suitability models for the taxon group Pennatula offshore California, Oregon, and Washington. Depicted is a “robust” very high likelihood prediction that indicates grid cells for which all the models fit to the bootstrap samples were classified as having a very high likelihood of containing suitable habitat. NCCOS obtained the April 5, 2018 version of the NOAA Deep Sea Coral Research and Technology Program national database of deep-sea corals and sponges and extracted presence locations of deep-sea corals and sponges offshore California, Oregon, and Washington and shallower than the 1200m depth contour. The project science team identified 44 taxa of deep-sea coral and sponges with sufficient presence locations to develop habitat suitability models. For each taxon, the R package ‘maxnet’ was used to fit models of habitat suitability using the values of the environmental covariates at locations of deep-sea coral or sponge occurrence. A stepwise model selection procedure was performed to select a final model for each taxon that balanced model predictive performance with model complexity. The set of environmental covariates in the final model was used to fit models to ten bootstrap samples to generate spatially explicit predictions of the relative likelihood of habitat suitability. Outputs from these predictions include the mean prediction across the models fit to the ten bootstrap samples, the coefficient of variation across the predictions, a classified prediction created by reclassifying the mean prediction into classes of increasing likelihood of habitat suitability, and a “robust” very high likelihood prediction that indicates grid cells for which all the models fit to the bootstrap samples were classified as having a very high likelihood of containing suitable habitat.

Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Layer: Plumarella - Robust Very High Likelihood (639)

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Description: This data layer contains the draft output of the habitat suitability models for the taxon group Plumarella offshore California, Oregon, and Washington. Depicted is a “robust” very high likelihood prediction that indicates grid cells for which all the models fit to the bootstrap samples were classified as having a very high likelihood of containing suitable habitat. NCCOS obtained the April 5, 2018 version of the NOAA Deep Sea Coral Research and Technology Program national database of deep-sea corals and sponges and extracted presence locations of deep-sea corals and sponges offshore California, Oregon, and Washington and shallower than the 1200m depth contour. The project science team identified 44 taxa of deep-sea coral and sponges with sufficient presence locations to develop habitat suitability models. For each taxon, the R package ‘maxnet’ was used to fit models of habitat suitability using the values of the environmental covariates at locations of deep-sea coral or sponge occurrence. A stepwise model selection procedure was performed to select a final model for each taxon that balanced model predictive performance with model complexity. The set of environmental covariates in the final model was used to fit models to ten bootstrap samples to generate spatially explicit predictions of the relative likelihood of habitat suitability. Outputs from these predictions include the mean prediction across the models fit to the ten bootstrap samples, the coefficient of variation across the predictions, a classified prediction created by reclassifying the mean prediction into classes of increasing likelihood of habitat suitability, and a “robust” very high likelihood prediction that indicates grid cells for which all the models fit to the bootstrap samples were classified as having a very high likelihood of containing suitable habitat.

Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Description: This data layer contains the draft output of the habitat suitability models for the taxon group Polymastia offshore California, Oregon, and Washington. Depicted is a “robust” very high likelihood prediction that indicates grid cells for which all the models fit to the bootstrap samples were classified as having a very high likelihood of containing suitable habitat. NCCOS obtained the April 5, 2018 version of the NOAA Deep Sea Coral Research and Technology Program national database of deep-sea corals and sponges and extracted presence locations of deep-sea corals and sponges offshore California, Oregon, and Washington and shallower than the 1200m depth contour. The project science team identified 44 taxa of deep-sea coral and sponges with sufficient presence locations to develop habitat suitability models. For each taxon, the R package ‘maxnet’ was used to fit models of habitat suitability using the values of the environmental covariates at locations of deep-sea coral or sponge occurrence. A stepwise model selection procedure was performed to select a final model for each taxon that balanced model predictive performance with model complexity. The set of environmental covariates in the final model was used to fit models to ten bootstrap samples to generate spatially explicit predictions of the relative likelihood of habitat suitability. Outputs from these predictions include the mean prediction across the models fit to the ten bootstrap samples, the coefficient of variation across the predictions, a classified prediction created by reclassifying the mean prediction into classes of increasing likelihood of habitat suitability, and a “robust” very high likelihood prediction that indicates grid cells for which all the models fit to the bootstrap samples were classified as having a very high likelihood of containing suitable habitat.

Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Description: This data layer contains the draft output of the habitat suitability models for the taxon group Ptilosarcus offshore California, Oregon, and Washington. Depicted is a “robust” very high likelihood prediction that indicates grid cells for which all the models fit to the bootstrap samples were classified as having a very high likelihood of containing suitable habitat. NCCOS obtained the April 5, 2018 version of the NOAA Deep Sea Coral Research and Technology Program national database of deep-sea corals and sponges and extracted presence locations of deep-sea corals and sponges offshore California, Oregon, and Washington and shallower than the 1200m depth contour. The project science team identified 44 taxa of deep-sea coral and sponges with sufficient presence locations to develop habitat suitability models. For each taxon, the R package ‘maxnet’ was used to fit models of habitat suitability using the values of the environmental covariates at locations of deep-sea coral or sponge occurrence. A stepwise model selection procedure was performed to select a final model for each taxon that balanced model predictive performance with model complexity. The set of environmental covariates in the final model was used to fit models to ten bootstrap samples to generate spatially explicit predictions of the relative likelihood of habitat suitability. Outputs from these predictions include the mean prediction across the models fit to the ten bootstrap samples, the coefficient of variation across the predictions, a classified prediction created by reclassifying the mean prediction into classes of increasing likelihood of habitat suitability, and a “robust” very high likelihood prediction that indicates grid cells for which all the models fit to the bootstrap samples were classified as having a very high likelihood of containing suitable habitat.

Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Description: This data layer contains the draft output of the habitat suitability models for the taxon group Stylaster californicus offshore California, Oregon, and Washington. Depicted is a “robust” very high likelihood prediction that indicates grid cells for which all the models fit to the bootstrap samples were classified as having a very high likelihood of containing suitable habitat. NCCOS obtained the April 5, 2018 version of the NOAA Deep Sea Coral Research and Technology Program national database of deep-sea corals and sponges and extracted presence locations of deep-sea corals and sponges offshore California, Oregon, and Washington and shallower than the 1200m depth contour. The project science team identified 44 taxa of deep-sea coral and sponges with sufficient presence locations to develop habitat suitability models. For each taxon, the R package ‘maxnet’ was used to fit models of habitat suitability using the values of the environmental covariates at locations of deep-sea coral or sponge occurrence. A stepwise model selection procedure was performed to select a final model for each taxon that balanced model predictive performance with model complexity. The set of environmental covariates in the final model was used to fit models to ten bootstrap samples to generate spatially explicit predictions of the relative likelihood of habitat suitability. Outputs from these predictions include the mean prediction across the models fit to the ten bootstrap samples, the coefficient of variation across the predictions, a classified prediction created by reclassifying the mean prediction into classes of increasing likelihood of habitat suitability, and a “robust” very high likelihood prediction that indicates grid cells for which all the models fit to the bootstrap samples were classified as having a very high likelihood of containing suitable habitat.

Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Description: This data layer contains the draft output of the habitat suitability models for the taxon group Swiftia kofoidi offshore California, Oregon, and Washington. Depicted is a “robust” very high likelihood prediction that indicates grid cells for which all the models fit to the bootstrap samples were classified as having a very high likelihood of containing suitable habitat. NCCOS obtained the April 5, 2018 version of the NOAA Deep Sea Coral Research and Technology Program national database of deep-sea corals and sponges and extracted presence locations of deep-sea corals and sponges offshore California, Oregon, and Washington and shallower than the 1200m depth contour. The project science team identified 44 taxa of deep-sea coral and sponges with sufficient presence locations to develop habitat suitability models. For each taxon, the R package ‘maxnet’ was used to fit models of habitat suitability using the values of the environmental covariates at locations of deep-sea coral or sponge occurrence. A stepwise model selection procedure was performed to select a final model for each taxon that balanced model predictive performance with model complexity. The set of environmental covariates in the final model was used to fit models to ten bootstrap samples to generate spatially explicit predictions of the relative likelihood of habitat suitability. Outputs from these predictions include the mean prediction across the models fit to the ten bootstrap samples, the coefficient of variation across the predictions, a classified prediction created by reclassifying the mean prediction into classes of increasing likelihood of habitat suitability, and a “robust” very high likelihood prediction that indicates grid cells for which all the models fit to the bootstrap samples were classified as having a very high likelihood of containing suitable habitat.

Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Layer: Umbellula - Robust Very High Likelihood (649)

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Description: This data layer contains the draft output of the habitat suitability models for the taxon group Umbellula offshore California, Oregon, and Washington. Depicted is a “robust” very high likelihood prediction that indicates grid cells for which all the models fit to the bootstrap samples were classified as having a very high likelihood of containing suitable habitat. NCCOS obtained the April 5, 2018 version of the NOAA Deep Sea Coral Research and Technology Program national database of deep-sea corals and sponges and extracted presence locations of deep-sea corals and sponges offshore California, Oregon, and Washington and shallower than the 1200m depth contour. The project science team identified 44 taxa of deep-sea coral and sponges with sufficient presence locations to develop habitat suitability models. For each taxon, the R package ‘maxnet’ was used to fit models of habitat suitability using the values of the environmental covariates at locations of deep-sea coral or sponge occurrence. A stepwise model selection procedure was performed to select a final model for each taxon that balanced model predictive performance with model complexity. The set of environmental covariates in the final model was used to fit models to ten bootstrap samples to generate spatially explicit predictions of the relative likelihood of habitat suitability. Outputs from these predictions include the mean prediction across the models fit to the ten bootstrap samples, the coefficient of variation across the predictions, a classified prediction created by reclassifying the mean prediction into classes of increasing likelihood of habitat suitability, and a “robust” very high likelihood prediction that indicates grid cells for which all the models fit to the bootstrap samples were classified as having a very high likelihood of containing suitable habitat.

Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Layer: Thresholded Mean Predictions (651)

Parent Layer: Deep Sea Corals and Sponges

Sub Layers:
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• Acanthoptilum - Thresholded Mean
• Adelogorgia phyllosclera - Thresholded Mean
• Anthoptilum - Thresholded Mean
• Antipathes dendrochristos - Thresholded Mean
• Aphrocallistes vastus - Thresholded Mean
• Asbestopluma - Thresholded Mean
• Balanophyllia - Thresholded Mean
• Bathypathes - Thresholded Mean
• Calcigorgia - Thresholded Mean
• Chromoplexaura - Thresholded Mean
• Chrysopathes - Thresholded Mean
• Clavularia - Thresholded Mean
• Coenocyathus bowersi - Thresholded Mean
• Demospongiae - Thresholded Mean
• Desmophyllum - Thresholded Mean
• Distichoptilum - Thresholded Mean
• Eugorgia - Thresholded Mean
• Farrea occa - Thresholded Mean
• Funiculina - Thresholded Mean
• Halipteris californica - Thresholded Mean
• Halipteris - Thresholded Mean
• Heterochone calyx - Thresholded Mean
• Heteropolypus ritteri - Thresholded Mean
• Hexactinellida - Thresholded Mean
• Hyalonema - Thresholded Mean
• Isidella - Thresholded Mean
• Leptogorgia - Thresholded Mean
• Lophelia pertusa - Thresholded Mean
• Paracyathus - Thresholded Mean
• Paragorgia - Thresholded Mean
• Parastenella - Thresholded Mean
• Pennatula - Thresholded Mean
• Plumarella - Thresholded Mean
• Polymastia - Thresholded Mean
• Psammogorgia - Thresholded Mean
• Ptilosarcus - Thresholded Mean
• Stylaster californicus - Thresholded Mean
• Stylaster - Thresholded Mean
• Stylatula - Thresholded Mean
• Swiftia kofoidi - Thresholded Mean
• Swiftia pacifica - Thresholded Mean
• Swiftia simplex - Thresholded Mean
• Umbellula - Thresholded Mean
• Virgularia - Thresholded Mean
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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Layer: Adelogorgia phyllosclera - Thresholded Mean (654)

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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Layer: Anthoptilum - Thresholded Mean (655)

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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Layer: Antipathes dendrochristos - Thresholded Mean (656)

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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Layer: Aphrocallistes vastus - Thresholded Mean (657)

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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Layer: Asbestopluma - Thresholded Mean (658)

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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Description: This data layer contains the draft output of the habitat suitability models for the taxon group Hyalonema offshore California, Oregon, and Washington. Depicted is a classified prediction created by reclassifying the mean prediction into classes of increasing likelihood of habitat suitability. NCCOS obtained the April 5, 2018 version of the NOAA Deep Sea Coral Research and Technology Program national database of deep-sea corals and sponges and extracted presence locations of deep-sea corals and sponges offshore California, Oregon, and Washington and shallower than the 1200m depth contour. The project science team identified 44 taxa of deep-sea coral and sponges with sufficient presence locations to develop habitat suitability models. For each taxon, the R package ‘maxnet’ was used to fit models of habitat suitability using the values of the environmental covariates at locations of deep-sea coral or sponge occurrence. A stepwise model selection procedure was performed to select a final model for each taxon that balanced model predictive performance with model complexity. The set of environmental covariates in the final model was used to fit models to ten bootstrap samples to generate spatially explicit predictions of the relative likelihood of habitat suitability. Outputs from these predictions include the mean prediction across the models fit to the ten bootstrap samples, the coefficient of variation across the predictions, a classified prediction created by reclassifying the mean prediction into classes of increasing likelihood of habitat suitability, and a “robust” very high likelihood prediction that indicates grid cells for which all the models fit to the bootstrap samples were classified as having a very high likelihood of containing suitable habitat.

Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Description: This data layer contains the draft output of the habitat suitability models for the taxon group Isidella offshore California, Oregon, and Washington. Depicted is a classified prediction created by reclassifying the mean prediction into classes of increasing likelihood of habitat suitability. NCCOS obtained the April 5, 2018 version of the NOAA Deep Sea Coral Research and Technology Program national database of deep-sea corals and sponges and extracted presence locations of deep-sea corals and sponges offshore California, Oregon, and Washington and shallower than the 1200m depth contour. The project science team identified 44 taxa of deep-sea coral and sponges with sufficient presence locations to develop habitat suitability models. For each taxon, the R package ‘maxnet’ was used to fit models of habitat suitability using the values of the environmental covariates at locations of deep-sea coral or sponge occurrence. A stepwise model selection procedure was performed to select a final model for each taxon that balanced model predictive performance with model complexity. The set of environmental covariates in the final model was used to fit models to ten bootstrap samples to generate spatially explicit predictions of the relative likelihood of habitat suitability. Outputs from these predictions include the mean prediction across the models fit to the ten bootstrap samples, the coefficient of variation across the predictions, a classified prediction created by reclassifying the mean prediction into classes of increasing likelihood of habitat suitability, and a “robust” very high likelihood prediction that indicates grid cells for which all the models fit to the bootstrap samples were classified as having a very high likelihood of containing suitable habitat.

Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Description: This data layer contains the draft output of the habitat suitability models for the taxon group Leptogorgia offshore California, Oregon, and Washington. Depicted is a classified prediction created by reclassifying the mean prediction into classes of increasing likelihood of habitat suitability. NCCOS obtained the April 5, 2018 version of the NOAA Deep Sea Coral Research and Technology Program national database of deep-sea corals and sponges and extracted presence locations of deep-sea corals and sponges offshore California, Oregon, and Washington and shallower than the 1200m depth contour. The project science team identified 44 taxa of deep-sea coral and sponges with sufficient presence locations to develop habitat suitability models. For each taxon, the R package ‘maxnet’ was used to fit models of habitat suitability using the values of the environmental covariates at locations of deep-sea coral or sponge occurrence. A stepwise model selection procedure was performed to select a final model for each taxon that balanced model predictive performance with model complexity. The set of environmental covariates in the final model was used to fit models to ten bootstrap samples to generate spatially explicit predictions of the relative likelihood of habitat suitability. Outputs from these predictions include the mean prediction across the models fit to the ten bootstrap samples, the coefficient of variation across the predictions, a classified prediction created by reclassifying the mean prediction into classes of increasing likelihood of habitat suitability, and a “robust” very high likelihood prediction that indicates grid cells for which all the models fit to the bootstrap samples were classified as having a very high likelihood of containing suitable habitat.

Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Description: This data layer contains the draft output of the habitat suitability models for the taxon group Lophelia pertusa offshore California, Oregon, and Washington. Depicted is a classified prediction created by reclassifying the mean prediction into classes of increasing likelihood of habitat suitability. NCCOS obtained the April 5, 2018 version of the NOAA Deep Sea Coral Research and Technology Program national database of deep-sea corals and sponges and extracted presence locations of deep-sea corals and sponges offshore California, Oregon, and Washington and shallower than the 1200m depth contour. The project science team identified 44 taxa of deep-sea coral and sponges with sufficient presence locations to develop habitat suitability models. For each taxon, the R package ‘maxnet’ was used to fit models of habitat suitability using the values of the environmental covariates at locations of deep-sea coral or sponge occurrence. A stepwise model selection procedure was performed to select a final model for each taxon that balanced model predictive performance with model complexity. The set of environmental covariates in the final model was used to fit models to ten bootstrap samples to generate spatially explicit predictions of the relative likelihood of habitat suitability. Outputs from these predictions include the mean prediction across the models fit to the ten bootstrap samples, the coefficient of variation across the predictions, a classified prediction created by reclassifying the mean prediction into classes of increasing likelihood of habitat suitability, and a “robust” very high likelihood prediction that indicates grid cells for which all the models fit to the bootstrap samples were classified as having a very high likelihood of containing suitable habitat.

Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Layer: Swiftia simplex - Thresholded Mean (694)

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Description: This data layer contains the draft output of the habitat suitability models for the taxon group Swiftia simplex offshore California, Oregon, and Washington. Depicted is a classified prediction created by reclassifying the mean prediction into classes of increasing likelihood of habitat suitability. NCCOS obtained the April 5, 2018 version of the NOAA Deep Sea Coral Research and Technology Program national database of deep-sea corals and sponges and extracted presence locations of deep-sea corals and sponges offshore California, Oregon, and Washington and shallower than the 1200m depth contour. The project science team identified 44 taxa of deep-sea coral and sponges with sufficient presence locations to develop habitat suitability models. For each taxon, the R package ‘maxnet’ was used to fit models of habitat suitability using the values of the environmental covariates at locations of deep-sea coral or sponge occurrence. A stepwise model selection procedure was performed to select a final model for each taxon that balanced model predictive performance with model complexity. The set of environmental covariates in the final model was used to fit models to ten bootstrap samples to generate spatially explicit predictions of the relative likelihood of habitat suitability. Outputs from these predictions include the mean prediction across the models fit to the ten bootstrap samples, the coefficient of variation across the predictions, a classified prediction created by reclassifying the mean prediction into classes of increasing likelihood of habitat suitability, and a “robust” very high likelihood prediction that indicates grid cells for which all the models fit to the bootstrap samples were classified as having a very high likelihood of containing suitable habitat.

Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Layer: Umbellula - Thresholded Mean (695)

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Description: This data layer contains the draft output of the habitat suitability models for the taxon group Umbellula offshore California, Oregon, and Washington. Depicted is a classified prediction created by reclassifying the mean prediction into classes of increasing likelihood of habitat suitability. NCCOS obtained the April 5, 2018 version of the NOAA Deep Sea Coral Research and Technology Program national database of deep-sea corals and sponges and extracted presence locations of deep-sea corals and sponges offshore California, Oregon, and Washington and shallower than the 1200m depth contour. The project science team identified 44 taxa of deep-sea coral and sponges with sufficient presence locations to develop habitat suitability models. For each taxon, the R package ‘maxnet’ was used to fit models of habitat suitability using the values of the environmental covariates at locations of deep-sea coral or sponge occurrence. A stepwise model selection procedure was performed to select a final model for each taxon that balanced model predictive performance with model complexity. The set of environmental covariates in the final model was used to fit models to ten bootstrap samples to generate spatially explicit predictions of the relative likelihood of habitat suitability. Outputs from these predictions include the mean prediction across the models fit to the ten bootstrap samples, the coefficient of variation across the predictions, a classified prediction created by reclassifying the mean prediction into classes of increasing likelihood of habitat suitability, and a “robust” very high likelihood prediction that indicates grid cells for which all the models fit to the bootstrap samples were classified as having a very high likelihood of containing suitable habitat.

Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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Layer: Virgularia - Thresholded Mean (696)

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Description: This data layer contains the draft output of the habitat suitability models for the taxon group Virgularia offshore California, Oregon, and Washington. Depicted is a classified prediction created by reclassifying the mean prediction into classes of increasing likelihood of habitat suitability. NCCOS obtained the April 5, 2018 version of the NOAA Deep Sea Coral Research and Technology Program national database of deep-sea corals and sponges and extracted presence locations of deep-sea corals and sponges offshore California, Oregon, and Washington and shallower than the 1200m depth contour. The project science team identified 44 taxa of deep-sea coral and sponges with sufficient presence locations to develop habitat suitability models. For each taxon, the R package ‘maxnet’ was used to fit models of habitat suitability using the values of the environmental covariates at locations of deep-sea coral or sponge occurrence. A stepwise model selection procedure was performed to select a final model for each taxon that balanced model predictive performance with model complexity. The set of environmental covariates in the final model was used to fit models to ten bootstrap samples to generate spatially explicit predictions of the relative likelihood of habitat suitability. Outputs from these predictions include the mean prediction across the models fit to the ten bootstrap samples, the coefficient of variation across the predictions, a classified prediction created by reclassifying the mean prediction into classes of increasing likelihood of habitat suitability, and a “robust” very high likelihood prediction that indicates grid cells for which all the models fit to the bootstrap samples were classified as having a very high likelihood of containing suitable habitat.

Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS)

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