State comparisons data for population,age, race, Hispanic Origin, and housing information for all states. Data include a national ranking.

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Face refers to the areal (polygon) topological primitives that make up MTDB. A face is bounded by one or more edges; its boundary includes only the edges that separate it from other faces, not any interior edges contained within the area of the face. The Topological Faces Shapefile contains the attributes of each topological primitive face. Each face has a unique topological face identifier (TFID) value. Each face in the shapefile includes the key geographic area codes for all geographic areas for which the Census Bureau tabulates data for both the 2020 Census and the annual estimates and surveys. The geometries of each of these geographic areas can then be built by dissolving the face geometries on the appropriate key geographic area codes in the Topological Faces Shapefile.

The 2020 TIGER/Line Shapefiles contain current geographic extent and boundaries of both legal and statistical entities (which have no governmental standing) for the United States, the District of Columbia, Puerto Rico, and the Island areas. This vintage includes boundaries of governmental units that match the data from the surveys that use 2020 geography (e.g., 2020 Population Estimates and the 2020 American Community Survey). In addition to geographic boundaries, the 2020 TIGER/Line Shapefiles also include geographic feature shapefiles and relationship files. Feature shapefiles represent the point, line and polygon features in the MTDB (e.g., roads and rivers). Relationship files contain additional attribute information users can join to the shapefiles. Both the feature shapefiles and relationship files reflect updates made in the database through September 2020. To see how the geographic entities, relate to one another, please see our geographic hierarchy diagrams here.Census Urbanized Areashttps://www2.census.gov/geo/tiger/TIGER2020/UACCensus Urban/Rural Census Block Shapefileshttps://www.census.gov/cgi-bin/geo/shapefiles/index.php2020 TIGER/Line and Redistricting shapefiles:https://www.census.gov/geographies/mapping-files/time-series/geo/tiger-line-file.2020.htmlTechnical documentation:https://www2.census.gov/geo/pdfs/maps-data/data/tiger/tgrshp2020/TGRSHP2020_TechDoc.pdfTIGERweb REST Services:https://tigerweb.geo.census.gov/tigerwebmain/TIGERweb_restmapservice.htmlTIGERweb WMS Services:https://tigerweb.geo.census.gov/tigerwebmain/TIGERweb_wms.htmlThe legal entities included in these shapefiles are:American Indian Off-Reservation Trust LandsAmerican Indian Reservations – FederalAmerican Indian Reservations – StateAmerican Indian Tribal Subdivisions (within legal American Indian areas)Alaska Native Regional CorporationsCongressional Districts – 116th CongressConsolidated CitiesCounties and Equivalent Entities (except census areas in Alaska)Estates (US Virgin Islands only)Hawaiian Home LandsIncorporated PlacesMinor Civil DivisionsSchool Districts – ElementarySchool Districts – SecondarySchool Districts – UnifiedStates and Equivalent EntitiesState Legislative Districts – UpperState Legislative Districts – LowerSubminor Civil Divisions (Subbarrios in Puerto Rico)The statistical entities included in these shapefiles are:Alaska Native Village Statistical AreasAmerican Indian/Alaska Native Statistical AreasAmerican Indian Tribal Subdivisions (within Oklahoma Tribal Statistical Areas)Block Groups3-5Census AreasCensus BlocksCensus County Divisions (Census Subareas in Alaska)Unorganized Territories (statistical county subdivisions)Census Designated Places (CDPs)Census TractsCombined New England City and Town AreasCombined Statistical AreasMetropolitan and Micropolitan Statistical Areas and related statistical areasMetropolitan DivisionsNew England City and Town AreasNew England City and Town Area DivisionsOklahoma Tribal Statistical AreasPublic Use Microdata Areas (PUMAs)State Designated Tribal Statistical AreasTribal Designated Statistical AreasUrban AreasZIP Code Tabulation Areas (ZCTAs)Shapefiles - Features:Address Range-FeatureAll Lines (called Edges)All RoadsArea HydrographyArea LandmarkCoastlineLinear HydrographyMilitary InstallationPoint LandmarkPrimary RoadsPrimary and Secondary RoadsTopological Faces (polygons with all geocodes)Relationship Files:Address Range-Feature NameAddress RangesFeature NamesTopological Faces – Area LandmarkTopological Faces – Area HydrographyTopological Faces – Military Installations

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Face refers to the areal (polygon) topological primitives that make up MTDB. A face is bounded by one or more edges; its boundary includes only the edges that separate it from other faces, not any interior edges contained within the area of the face. The Topological Faces Shapefile contains the attributes of each topological primitive face. Each face has a unique topological face identifier (TFID) value. Each face in the shapefile includes the key geographic area codes for all geographic areas for which the Census Bureau tabulates data for both the 2020 Census and the annual estimates and surveys. The geometries of each of these geographic areas can then be built by dissolving the face geometries on the appropriate key geographic area codes in the Topological Faces Shapefile.

The Human Geography Dark Map (World Edition) web map provides a detailed world basemap with a dark monochromatic style and content adjusted to support human geography information. Where possible, the map content has been adjusted so that it observes WCAG contrast criteria.This basemap, included in the ArcGIS Living Atlas of the World, uses 3 vector tile layers:Human Geography Dark Label, a label reference layer including cities and communities, countries, administrative units, and at larger scales street names.Human Geography Dark Detail, a detail reference layer including administrative boundaries, roads and highways, and larger bodies of water. This layer is designed to be used with a high degree of transparency so that the detail does not compete with your information. It is set at approximately 50% in this web map, but can be adjusted.Human Geography Dark Base, a simple basemap consisting of land areas in a very dark gray only.The vector tile layers in this web map are built using the same data sources used for other Esri Vector Basemaps. For details on data sources contributed by the GIS community, view the map of Community Maps Basemap Contributors. Esri Vector Basemaps are updated monthly.Learn more about this basemap from the cartographic designer in A Dark Version of the Human Geography Basemap.Use this MapThis map is designed to be used as a basemap for overlaying other layers of information or as a stand-alone reference map. You can add layers to this web map and save as your own map. If you like, you can add this web map to a custom basemap gallery for others in your organization to use in creating web maps. If you would like to add this map as a layer in other maps you are creating, you may use the tile layers referenced in this map.

The Digital Geomorphic-GIS Map of the Ocracoke Area (1:24,000 scale 2007 mapping), North Carolina is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) a 10.1 file geodatabase (occk_geomorphology.gdb), and a 2.) Open Geospatial Consortium (OGC) geopackage. The file geodatabase format is supported with a 1.) ArcGIS Pro map file (.mapx) file (occk_geomorphology.mapx) and individual Pro layer (.lyrx) files (for each GIS data layer), as well as with a 2.) 10.1 ArcMap (.mxd) map document (occk_geomorphology.mxd) and individual 10.1 layer (.lyr) files (for each GIS data layer). Upon request, the GIS data is also available in ESRI 10.1 shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) A GIS readme file (caha_fora_wrbr_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (caha_fora_wrbr_geomorphology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (occk_geomorphology_metadata_faq.pdf). Please read the caha_fora_wrbr_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. QGIS software is available for free at: https://www.qgis.org/en/site/. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). For a complete listing of GRI products visit the GRI publications webpage: For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri,htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: North Carolina Geological Survey. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (occk_geomorphology_metadata.txt or occk_geomorphology_metadata_faq.pdf). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:24,000 and United States National Map Accuracy Standards features are within (horizontally) 12.2 meters or 40 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in ArcGIS, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm).

This map service contains data and information from a variety of data sources, including non-NOAA data. NOAA provides the information “as-is” and shall incur no responsibility or liability as to the completeness or accuracy of this information. NOAA assumes no responsibility arising from the use of this information.

GeoMarine Geo-Marine Inc., Environmental Services 2201 K Avenue, Suite A2 Plano, Texas 75074 Phone: 972.423.5480 http://www.geo-marine.com/

© GeoMarine Geo-Marine Inc. This layer is a component of North Carolina Offshore Renewable Energy Planning.

A task force of officials from state, local, and federal government agencies was convened by the Department of Interior’s Bureau of Ocean Energy Management (BOEM) to discuss the designation of wind energy areas in federal waters off the coast of North Carolina. The task force helps minimize the potential for significant conflicts with offshore wind farm construction and operations. Information needs include data on existing ocean uses like military operation areas, marine transportation and navigation, important fishing areas, sensitive habitat, and viewsheds. MarineCadastre.gov, a joint BOEM and National Oceanic and Atmospheric Administration initiative providing authoritative data to meet the needs of the offshore energy and marine planning communities, worked with the North Carolina Task Force to develop this map, which includes many of the data layers being used in their decision-making process. This map service presents spatial information about MarineCadastre.gov services across the United States and Territories in the Web Mercator projection. The service was developed by the National Oceanic and Atmospheric Administration (NOAA), but may contain data and information from a variety of data sources, including non-NOAA data. NOAA provides the information “as-is” and shall incur no responsibility or liability as to the completeness or accuracy of this information. NOAA assumes no responsibility arising from the use of this information. The NOAA Office for Coastal Management will make every effort to provide continual access to this service but it may need to be taken down during routine IT maintenance or in case of an emergency. If you plan to ingest this service into your own application and would like to be informed about planned and unplanned service outages or changes to existing services, please register for our Data Services Newsletter (http://coast.noaa.gov/digitalcoast/publications/subscribe). For additional information, please contact the NOAA Office for Coastal Management (coastal.info@noaa.gov).

© Bureau of Ocean Energy Management (BOEM); National Oceanic and Atmospheric Association (NOAA), Office for Coastal Management (OCM); NOAA, Office of Coast Survey (OCS); North Carolina Renewable Energy Task Force

This map service contains data and information from a variety of data sources, including non-NOAA data. NOAA provides the information “as-is” and shall incur no responsibility or liability as to the completeness or accuracy of this information. NOAA assumes no responsibility arising from the use of this information.

GeoMarine Geo-Marine Inc., Environmental Services 2201 K Avenue, Suite A2 Plano, Texas 75074 Phone: 972.423.5480 http://www.geo-marine.com/

© GeoMarine Geo-Marine Inc. This layer is a component of North Carolina Offshore Renewable Energy Planning.

A task force of officials from state, local, and federal government agencies was convened by the Department of Interior’s Bureau of Ocean Energy Management (BOEM) to discuss the designation of wind energy areas in federal waters off the coast of North Carolina. The task force helps minimize the potential for significant conflicts with offshore wind farm construction and operations. Information needs include data on existing ocean uses like military operation areas, marine transportation and navigation, important fishing areas, sensitive habitat, and viewsheds. MarineCadastre.gov, a joint BOEM and National Oceanic and Atmospheric Administration initiative providing authoritative data to meet the needs of the offshore energy and marine planning communities, worked with the North Carolina Task Force to develop this map, which includes many of the data layers being used in their decision-making process. This map service presents spatial information about MarineCadastre.gov services across the United States and Territories in the Web Mercator projection. The service was developed by the National Oceanic and Atmospheric Administration (NOAA), but may contain data and information from a variety of data sources, including non-NOAA data. NOAA provides the information “as-is” and shall incur no responsibility or liability as to the completeness or accuracy of this information. NOAA assumes no responsibility arising from the use of this information. The NOAA Office for Coastal Management will make every effort to provide continual access to this service but it may need to be taken down during routine IT maintenance or in case of an emergency. If you plan to ingest this service into your own application and would like to be informed about planned and unplanned service outages or changes to existing services, please register for our Data Services Newsletter (http://coast.noaa.gov/digitalcoast/publications/subscribe). For additional information, please contact the NOAA Office for Coastal Management (coastal.info@noaa.gov).

© Bureau of Ocean Energy Management (BOEM); National Oceanic and Atmospheric Association (NOAA), Office for Coastal Management (OCM); NOAA, Office of Coast Survey (OCS); North Carolina Renewable Energy Task Force

Hourly sub-skin Sea Surface Temperature product derived from GOES-East at 75°E longitude, covering 60S-60N and 135W-15W and re-projected on a 0.05° regular grid. The product format is compliant with the Data Specification (GDS) version 2 from the Group for High Resolution Sea Surface Temperatures (GHRSST).

A digital event log to record all instrument deployments during the cruise. access_formats=.htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson acquisition_description="" awards_0_award_nid=54892 awards_0_award_number=ANT-1044982 awards_0_data_url=http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1044982 awards_0_funder_name=NSF Antarctic Sciences awards_0_funding_acronym=NSF ANT awards_0_funding_source_nid=369 awards_0_program_manager=Dr Peter Milne awards_0_program_manager_nid=51468 cdm_data_type=Other comment=PI: Ann Bucklin (UConn) event log from LMG11-10 Antarctic Salps, 2011 version: 2011-12-28 Conventions=COARDS, CF-1.6, ACDD-1.3 data_source=extract_data_as_tsv version 2.3 19 Dec 2019 defaultDataQuery=&time<now doi=10.1575/1912/bco-dmo.661345 Easternmost_Easting=-53.55507 geospatial_lat_max=-53.1695 geospatial_lat_min=-65.08178 geospatial_lat_units=degrees_north geospatial_lon_max=-53.55507 geospatial_lon_min=-70.907 geospatial_lon_units=degrees_east geospatial_vertical_max=2500.0 geospatial_vertical_min=0.5 geospatial_vertical_positive=down geospatial_vertical_units=m infoUrl=https://www.bco-dmo.org/dataset/3565 institution=BCO-DMO metadata_source=https://www.bco-dmo.org/api/dataset/3565 Northernmost_Northing=-53.1695 param_mapping={'3565': {'lat': 'flag - latitude', 'depth': 'flag - depth', 'lon': 'flag - longitude'}} parameter_source=https://www.bco-dmo.org/mapserver/dataset/3565/parameters people_0_affiliation=University of Connecticut people_0_affiliation_acronym=UConn - Avery Point people_0_person_name=Ann Bucklin people_0_person_nid=50389 people_0_role=Chief Scientist people_0_role_type=originator people_1_affiliation=Woods Hole Oceanographic Institution people_1_affiliation_acronym=WHOI BCO-DMO people_1_person_name=Nancy Copley people_1_person_nid=50396 people_1_role=BCO-DMO Data Manager people_1_role_type=related project=Salp_Antarctic projects_0_acronym=Salp_Antarctic projects_0_description=The Antarctic salp, Salpa thompsoni, is an increasingly important player in the vulnerable Antarctic Peninsula pelagic ecosystem. Observations of high abundance of Salpa thompsoni during the summer in the Southern Ocean suggest that this species is capable of rapid somatic and population growth, and frequently forms dense blooms under favorable environmental conditions. The proposed research will examine genome-wide patterns of gene expression, target gene expression levels, and patterns of population genetic diversity and structure of the target salp species. Our preliminary results and data analysis have provided a promising basis for transcriptomic studies of S. thompsoni in the Southern Ocean. The proposed next steps in our genomic/transcriptomic analysis of Salpa thompsoni are: 1) completion of a reference transcriptome as a basis for genome-wide analysis of gene expression; 2) whole transcriptome shotgun sequencing (RNA-Seq) analysis to characterize gene expression in relation to individual characteristics and environmental conditions; 3) quantitative real-time PCR (qRT-PCR) characterization and validation of gene expression for 10-20 top differentially-expressed genes; and 4) detection of strand-specific allelic variation at SNP (Single Nucleotide Polymorphic) sites to analyze clonal diversity and population genetic diversity and structure. We hypothesize that: 1) deep analysis of the Salpa thompsoni transcriptome will reveal significant associations among selected set of differentially-expressed genes and critical life history stages and events (e.g., ontogenetic maturation, sexual reproduction, senescence) of the salp; and 2) the species will show variable levels of clonal diversity and significant genetic differentiation among salp populations in different regions of the Southern Ocean. Samples will be obtained from research cruises during 2011-2013 in diverse regions of the Southern Ocean; dedicated sample and data collection will be carried out during a cruise of the R/V LM GOULD (LMG11-10) to the Western Antarctic Peninsula region in November, 2011. The significance of this effort lies in new understanding of the molecular processes underlying the complex life history and population dynamics of S. thompsoni in relation to the Antarctic pelagic ecosystem and extreme and variable environmental conditions of the Southern Ocean. Most of the data from this project are available from the Marine Geoscience Data System (MGDS), part of IEDA and is available at https://www.marine-geo.org/tools/search/Files.php?data_set_uid=18148. projects_0_end_date=2014-05 projects_0_geolocation=Southern Ocean projects_0_name=Population ecology of Salpa thompsoni based on molecular indicators projects_0_project_nid=2174 projects_0_start_date=2011-06 sourceUrl=(local files) Southernmost_Northing=-65.08178 standard_name_vocabulary=CF Standard Name Table v55 version=1 Westernmost_Easting=-70.907 xml_source=osprey2erddap.update_xml() v1.3

This web map presents a vector basemap of OpenStreetMap (OSM) data hosted by Esri. Esri created this vector tile basemap from the Daylight map distribution of OSM data, which is supported by Facebook and supplemented with additional data from Microsoft. This version of the map is rendered using OSM cartography. The OSM Daylight map will be updated every month with the latest version of OSM Daylight data.OpenStreetMap is an open collaborative project to create a free editable map of the world. Volunteers gather location data using GPS, local knowledge, and other free sources of information and upload it. The resulting free map can be viewed and downloaded from the OpenStreetMap site:www.OpenStreetMap.org. Esri is a supporter of the OSM project and is excited to make this enhanced vector basemap available to the ArcGIS user and developer communities.

This dataset is a log of the Salpa thompsoni specimens used for genomics/transcriptomics. Reported parameters include cruise id, region, season and area, location, number of samples collected, temperature, salinity, depth range of the samples, and the depth of the water at the collection site.

Related Dataset: Salp genome and transcriptome access_formats=.htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson acquisition_description=1) Cruise R/V LM GOULD (LMG1110): Samples collected using Multiple Opening/Closing Net and Environmental Sensing System (MOCNESS) with a mouth opening of 1-m2 and nine 335\u03bcm mesh nets; upper 200 m were sampled with a 2.3 m2 Isaacs-Kidd Midwater Trawl (IKMT) with a 505 \u00b5m mesh net.\u00a0Western Antarctic Peninsula region, Southern Ocean (November- December 2011)

2) Cruise\u00a0R/V Polarstern (PS-ANT-XVII/2): Samples collected using a Rectangular Midwater Trawl (RMT 1+8) from the upper 200 m.\u00a0Western Antarctic Peninsula region, Southern Ocean (January 2011)

3) Cruise R/V Umitaka Maru (UM-08-09): Samples collected using a RMT 1+8 from 2,000 m to surface. Indian Sector, Southern Ocean (January 2009) awards_0_award_nid=54892 awards_0_award_number=ANT-1044982 awards_0_data_url=http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1044982 awards_0_funder_name=NSF Antarctic Sciences awards_0_funding_acronym=NSF ANT awards_0_funding_source_nid=369 awards_0_program_manager=Dr Peter Milne awards_0_program_manager_nid=51468 cdm_data_type=Other comment=Salpa thompsoni collection information PI: A. Bucklin (UConn) version: 2017-01-06 NOTE: These data were published in Table 1, Batta-Lona et al (2016) Pol. Bio. doi:10.1007/s00300-016-2051-6 Conventions=COARDS, CF-1.6, ACDD-1.3 data_source=extract_data_as_tsv version 2.3 19 Dec 2019 defaultDataQuery=&time<now doi=10.1575/1912/bco-dmo.728220 Easternmost_Easting=42.002 geospatial_lat_max=-60.901 geospatial_lat_min=-66.183 geospatial_lat_units=degrees_north geospatial_lon_max=42.002 geospatial_lon_min=-74.567 geospatial_lon_units=degrees_east infoUrl=https://www.bco-dmo.org/dataset/672600 institution=BCO-DMO instruments_0_acronym=MOC1 instruments_0_dataset_instrument_nid=674089 instruments_0_description=The Multiple Opening/Closing Net and Environmental Sensing System or MOCNESS is a family of net systems based on the Tucker Trawl principle. The MOCNESS-1 carries nine 1-m2 nets usually of 335 micrometer mesh and is intended for use with the macrozooplankton. All nets are black to reduce contrast with the background. A motor/toggle release assembly is mounted on the top portion of the frame and stainless steel cables with swaged fittings are used to attach the net bar to the toggle release. A stepping motor in a pressure compensated case filled with oil turns the escapement crankshaft of the toggle release which sequentially releases the nets to an open then closed position on command from the surface. -- from the MOCNESS Operations Manual (1999 + 2003). instruments_0_instrument_external_identifier=https://vocab.nerc.ac.uk/collection/L22/current/NETT0097/ instruments_0_instrument_name=MOCNESS1 instruments_0_instrument_nid=437 instruments_0_supplied_name=Multiple Opening/Closing Net and Environmental Sensing System (MOCNESS) with a mouth opening of 1-m2 and nine 335μm mesh nets instruments_1_acronym=TrawlMid instruments_1_dataset_instrument_nid=674090 instruments_1_description=A mid-water or pelagic trawl is a net towed at a chosen depth in the water column to catch schooling fish such as herring and mackerel. Midwater trawl nets have very large front openings to herd schooling fish toward the back end where they become trapped in the narrow "broiler". The sides of the deployed net are spread horizontally with two large metal foils, called "doors," positioned in front of the net. As the trawler moves forward, the doors, and therefore the net, are forced outward, keeping the net open. This instrument designation is used when specific make and model are not known. instruments_1_instrument_external_identifier=https://vocab.nerc.ac.uk/collection/L05/current/23/ instruments_1_instrument_name=Midwater Trawl instruments_1_instrument_nid=467 instruments_1_supplied_name=Rectangular Midwater Trawl (RMT 1+8) instruments_2_acronym=IKMT instruments_2_dataset_instrument_nid=674091 instruments_2_description=A trawl with a pentagonal mouth opening and a dihedral depressor vane as part of the mouth opening. IKMTs come in various dimensions (refer to individual dataset documentation).

The original IKMTs were 10 foot (304 cm) and 15 foot (457 cm) at the mouth. The 10 foot IKMT net was 31 feet (9.45 m) in length (Wiebe and Benfield 2003). instruments_2_instrument_external_identifier=https://vocab.nerc.ac.uk/collection/L22/current/NETT0071/ instruments_2_instrument_name=Isaacs-Kidd Midwater Trawl instruments_2_instrument_nid=715 instruments_2_supplied_name=2.3 m2 Isaacs-Kidd Midwater Trawl (IKMT) with a 505 µm mesh net metadata_source=https://www.bco-dmo.org/api/dataset/672600 Northernmost_Northing=-60.901 param_mapping={'672600': {'lat': 'master - latitude', 'lon': 'master - longitude'}} parameter_source=https://www.bco-dmo.org/mapserver/dataset/672600/parameters people_0_affiliation=University of Connecticut people_0_affiliation_acronym=UConn - Avery Point people_0_person_name=Ann Bucklin people_0_person_nid=50389 people_0_role=Chief Scientist people_0_role_type=originator people_1_affiliation=University of Connecticut people_1_affiliation_acronym=UConn - Avery Point people_1_person_name=Ann Bucklin people_1_person_nid=50389 people_1_role=Principal Investigator people_1_role_type=originator people_2_affiliation=University of Connecticut people_2_affiliation_acronym=UConn people_2_person_name=Dr Rachel J. O'Neill people_2_person_nid=51393 people_2_role=Co-Principal Investigator people_2_role_type=originator people_3_affiliation=Connecticut Sea Grant people_3_affiliation_acronym=CTSG people_3_person_name=Dr Diana Payne people_3_person_nid=51392 people_3_role=Co-Principal Investigator people_3_role_type=originator people_4_affiliation=Woods Hole Oceanographic Institution people_4_affiliation_acronym=WHOI BCO-DMO people_4_person_name=Nancy Copley people_4_person_nid=50396 people_4_role=BCO-DMO Data Manager people_4_role_type=related project=Salp_Antarctic projects_0_acronym=Salp_Antarctic projects_0_description=The Antarctic salp, Salpa thompsoni, is an increasingly important player in the vulnerable Antarctic Peninsula pelagic ecosystem. Observations of high abundance of Salpa thompsoni during the summer in the Southern Ocean suggest that this species is capable of rapid somatic and population growth, and frequently forms dense blooms under favorable environmental conditions. The proposed research will examine genome-wide patterns of gene expression, target gene expression levels, and patterns of population genetic diversity and structure of the target salp species. Our preliminary results and data analysis have provided a promising basis for transcriptomic studies of S. thompsoni in the Southern Ocean. The proposed next steps in our genomic/transcriptomic analysis of Salpa thompsoni are: 1) completion of a reference transcriptome as a basis for genome-wide analysis of gene expression; 2) whole transcriptome shotgun sequencing (RNA-Seq) analysis to characterize gene expression in relation to individual characteristics and environmental conditions; 3) quantitative real-time PCR (qRT-PCR) characterization and validation of gene expression for 10-20 top differentially-expressed genes; and 4) detection of strand-specific allelic variation at SNP (Single Nucleotide Polymorphic) sites to analyze clonal diversity and population genetic diversity and structure. We hypothesize that: 1) deep analysis of the Salpa thompsoni transcriptome will reveal significant associations among selected set of differentially-expressed genes and critical life history stages and events (e.g., ontogenetic maturation, sexual reproduction, senescence) of the salp; and 2) the species will show variable levels of clonal diversity and significant genetic differentiation among salp populations in different regions of the Southern Ocean. Samples will be obtained from research cruises during 2011-2013 in diverse regions of the Southern Ocean; dedicated sample and data collection will be carried out during a cruise of the R/V LM GOULD (LMG11-10) to the Western Antarctic Peninsula region in November, 2011. The significance of this effort lies in new understanding of the molecular processes underlying the complex life history and population dynamics of S. thompsoni in relation to the Antarctic pelagic ecosystem and extreme and variable environmental conditions of the Southern Ocean. Most of the data from this project are available from the Marine Geoscience Data System (MGDS), part of IEDA and is available at https://www.marine-geo.org/tools/search/Files.php?data_set_uid=18148. projects_0_end_date=2014-05 projects_0_geolocation=Southern Ocean projects_0_name=Population ecology of Salpa thompsoni based on molecular indicators projects_0_project_nid=2174 projects_0_start_date=2011-06 sourceUrl=(local files) Southernmost_Northing=-66.183 standard_name_vocabulary=CF Standard Name Table v55 version=1 Westernmost_Easting=-74.567 xml_source=osprey2erddap.update_xml() v1.3

Mild cognitive impairment (MCI) is a transition between normal cognition (NC) and Alzheimer’s disease (AD). Differences in cortical thickness (ΔCT) have been reported in cases that degenerate from MCI to AD. The aspects of genetic and transcriptional variation related to ΔCT are vague. In this study, using an 8-year longitudinal follow-up outcome, we investigated the genetic correlates of ΔCT in MCI subjects with degeneration from MCI to AD (MCI_AD). We employed partial least squares regression (PLSR) on brain T1-weighted magnetic resonance imaging (MRI) images of 180 participants [143 stable MCI (MCI_S) participants and 37 MCI_AD participants] and brain gene expression data from the Allen Institute for Brain Science (AIBS) database to investigate genes associated with ΔCT. We found that upregulated PLS component 1 ΔCT-related genes were enriched in chemical synaptic transmission. To verify the robustness and specificity of the results, we conducted PLSR analysis invalidation and specificity datasets and performed weighted gene co-expression network analysis instead of PLSR for the above three datasets. We also used gene expression data in the brain prefrontal cortex from the Gene Expression Omnibus (GEO) database to indirectly validate the robustness and specificity of our results. We conclude that transcriptionally upregulated genes involved in chemical synaptic transmission are strongly related to global ΔCT in MCI patients who experience degeneration from MCI to AD.

This map is designed to be used as a basemap by marine GIS professionals and as a reference map by anyone interested in ocean data. The map is intended to support the ArcGIS Online basemap gallery. For more details on the map, please visit the Ocean Basemap.

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Face refers to the areal (polygon) topological primitives that make up MTDB. A face is bounded by one or more edges; its boundary includes only the edges that separate it from other faces, not any interior edges contained within the area of the face. The Topological Faces Shapefile contains the attributes of each topological primitive face. Each face has a unique topological face identifier (TFID) value. Each face in the shapefile includes the key geographic area codes for all geographic areas for which the Census Bureau tabulates data for both the 2010 Census and the annual estimates and surveys. The geometries of each of these geographic areas can then, be built by dissolving the face geometries on the appropriate key geographic area codes in the Topological Faces Shapefile.

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Face refers to the areal (polygon) topological primitives that make up MTDB. A face is bounded by one or more edges; its boundary includes only the edges that separate it from other faces, not any interior edges contained within the area of the face. The Topological Faces Shapefile contains the attributes of each topological primitive face. Each face has a unique topological face identifier (TFID) value. Each face in the shapefile includes the key geographic area codes for all geographic areas for which the Census Bureau tabulates data for both the 2010 Census and the annual estimates and surveys. The geometries of each of these geographic areas can then, be built by dissolving the face geometries on the appropriate key geographic area codes in the Topological Faces Shapefile.

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Face refers to the areal (polygon) topological primitives that make up MTDB. A face is bounded by one or more edges; its boundary includes only the edges that separate it from other faces, not any interior edges contained within the area of the face. The Topological Faces Shapefile contains the attributes of each topological primitive face. Each face has a unique topological face identifier (TFID) value. Each face in the shapefile includes the key geographic area codes for all geographic areas for which the Census Bureau tabulates data for both the 2010 Census and the annual estimates and surveys. The geometries of each of these geographic areas can then, be built by dissolving the face geometries on the appropriate key geographic area codes in the Topological Faces Shapefile.

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Face refers to the areal (polygon) topological primitives that make up MTDB. A face is bounded by one or more edges; its boundary includes only the edges that separate it from other faces, not any interior edges contained within the area of the face. The Topological Faces Shapefile contains the attributes of each topological primitive face. Each face has a unique topological face identifier (TFID) value. Each face in the shapefile includes the key geographic area codes for all geographic areas for which the Census Bureau tabulates data for both the 2010 Census and the annual estimates and surveys. The geometries of each of these geographic areas can then, be built by dissolving the face geometries on the appropriate key geographic area codes in the Topological Faces Shapefile.

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Face refers to the areal (polygon) topological primitives that make up MTDB. A face is bounded by one or more edges; its boundary includes only the edges that separate it from other faces, not any interior edges contained within the area of the face. The Topological Faces Shapefile contains the attributes of each topological primitive face. Each face has a unique topological face identifier (TFID) value. Each face in the shapefile includes the key geographic area codes for all geographic areas for which the Census Bureau tabulates data for both the 2010 Census and the annual estimates and surveys. The geometries of each of these geographic areas can then, be built by dissolving the face geometries on the appropriate key geographic area codes in the Topological Faces Shapefile.

This data set contains imagery from the National Agriculture Imagery Program (NAIP). The NAIP acquires digital ortho imagery during the agricultural growing seasons in the continental U.S.. A primary goal of the NAIP program is to enable availability of ortho imagery within one year of acquisition. The NAIP provides 60 centimeter ground sample distance (GSD) ortho imagery rectified to a horizontal accuracy within +/- 4 meters of reference digital ortho quarter quads (DOQQ's) from the National Digital Ortho Program (NDOP) or from the National Agriculture Imagery Program (NAIP). The tiling format of NAIP imagery is based on a 3.75' x 3.75' quarter quadrangle with a 300 pixel buffer on all four sides. The NAIP imagery is formatted to the UTM coordinate system using the North American Datum of 1983 (NAD83). The NAIP imagery may contain as much as 10% cloud cover per tile. This file was generated by compressing NAIP imagery that cover the county extent. Two types of compression may be used for NAIP imagery: MrSID and JPEG 2000. The target value for the compression ratio is 40:1 for imagery.