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Dataset Title:  [AT26-14 Alvin sample logs] - Sample logs from R/V Atlantis (AT26-14) Alvin
dives in the Gulf of Mexico during 2014 (Lophelia OA project) (Physiological
and genetic responses of the deep-water coral, Lophelia pertusa, to ongoing
ocean acidification in the Gulf of Mexico)
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_659440)
Range: longitude = -93.598915 to -88.01208°E, latitude = 27.080294 to 29.17451°N, depth = 402.04 to 1083.6m
Information:  Summary ? | License ? | FGDC | ISO 19115 | Metadata | Background (external link) | Data Access Form | Files
 
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Things You Can Do With Your Graphs

Well, you can do anything you want with your graphs, of course. But some things you might not have considered are:

The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  dive {
    String bcodmo_name "dive_id";
    String description "Dive ID number";
    String long_name "Dive";
    String units "unitless";
  }
  sampleLog_date {
    String bcodmo_name "date";
    String description "Date sample was taken; mm/dd/yy";
    String long_name "Sample Log Date";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/ADATAA01/";
    String units "unitless";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 _FillValue NaN;
    Float64 actual_range 27.08029275, 29.17450947;
    String axis "Y";
    String bcodmo_name "latitude";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String description "Latitude";
    String ioos_category "Location";
    String long_name "Latitude";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/LATX/";
    String standard_name "latitude";
    String units "degrees_north";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float64 _FillValue NaN;
    Float64 actual_range -93.59891607, -88.0120774;
    String axis "X";
    String bcodmo_name "longitude";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String description "Longitude";
    String ioos_category "Location";
    String long_name "Longitude";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/LONX/";
    String standard_name "longitude";
    String units "degrees_east";
  }
  utmx {
    Float64 _FillValue NaN;
    Float64 actual_range 225143.68, 675208.3;
    String bcodmo_name "UTM Coordinates";
    String description "Universal Transverse Mercator coordinate system X coordinates";
    String long_name "Utmx";
    String units "meters";
  }
  utmy {
    Float64 _FillValue NaN;
    Float64 actual_range 2995341.67, 3227749.34;
    String bcodmo_name "UTM Coordinates";
    String description "Universal Transverse Mercator coordinate system Y coordinates";
    String long_name "Utmy";
    String units "meters";
  }
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    Float64 _FillValue NaN;
    Float64 actual_range 402.04, 1083.6;
    String axis "Z";
    String bcodmo_name "depth";
    Float64 colorBarMaximum 8000.0;
    Float64 colorBarMinimum -8000.0;
    String colorBarPalette "TopographyDepth";
    String description "Depth of sample";
    String ioos_category "Location";
    String long_name "Depth";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/DEPH/";
    String positive "down";
    String standard_name "depth";
    String units "m";
  }
  sampleLog_time {
    String bcodmo_name "time";
    String description "Time sample was taken; HH:MM";
    String long_name "Sample Log Time";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/AHMSAA01/";
    String units "unitless";
  }
  time2 {
    String bcodmo_name "time";
    String description "Time sample was taken as it occurs in footage; HH:MM:SS";
    String long_name "Time";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/AHMSAA01/";
    String units "unitless";
  }
  sampleLog_seconds {
    Int32 _FillValue 2147483647;
    Int32 actual_range 50040, 82260;
    String bcodmo_name "seconds_local";
    String description "Seconds into dive sampling occurs; SSSSS";
    String long_name "Sample Log Seconds";
    String units "seconds";
  }
  time_sec {
    Int32 _FillValue 2147483647;
    Int32 actual_range 50034, 82257;
    String bcodmo_name "seconds_local";
    String description "Seconds into dive the start of sampling occurs";
    String long_name "Time Sec";
    String units "seconds";
  }
  sampleLog_sample {
    String bcodmo_name "sample";
    String description "Sampling method";
    String long_name "Sample Log Sample";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/ACYC/";
    String units "unitless";
  }
  sampleLog_location {
    String bcodmo_name "site";
    String description "Sampling location";
    String long_name "Sample Log Location";
    String units "unitless";
  }
  sampleLog_pump {
    String bcodmo_name "sample";
    String description "Sampling pump; on or off";
    String long_name "Sample Log Pump";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/ACYC/";
    String units "unitless";
  }
  sampleLog_species {
    String bcodmo_name "species";
    String description "Species sampled";
    String long_name "Sample Log Species";
    String units "unitless";
  }
  sampleLog_notes {
    String bcodmo_name "comment";
    String description "Notes on sampling";
    String long_name "Sample Log Notes";
    String units "unitless";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson";
    String acquisition_description 
"Sample logs were acquired for each dive. UTM coordinates,
lat/lons,\\u00a0depths, and sampling descriptions are included.";
    String awards_0_award_nid "54992";
    String awards_0_award_number "OCE-1220478";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward?AWD_ID=1220478";
    String awards_0_funder_name "NSF Division of Ocean Sciences";
    String awards_0_funding_acronym "NSF OCE";
    String awards_0_funding_source_nid "355";
    String awards_0_program_manager "David L. Garrison";
    String awards_0_program_manager_nid "50534";
    String cdm_data_type "Other";
    String comment 
"Sample Logs 
  Erik Cordes, PI 
  Version 20 September 2016";
    String Conventions "COARDS, CF-1.6, ACDD-1.3";
    String creator_email "info@bco-dmo.org";
    String creator_name "BCO-DMO";
    String creator_type "institution";
    String creator_url "https://www.bco-dmo.org/";
    String data_source "extract_data_as_tsv version 2.3  19 Dec 2019";
    String date_created "2016-09-21T00:00:17Z";
    String date_modified "2019-04-24T14:42:41Z";
    String defaultDataQuery "&time<now";
    String doi "10.1575/1912/bco-dmo.659440.1";
    Float64 Easternmost_Easting -88.0120774;
    Float64 geospatial_lat_max 29.17450947;
    Float64 geospatial_lat_min 27.08029275;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -88.0120774;
    Float64 geospatial_lon_min -93.59891607;
    String geospatial_lon_units "degrees_east";
    Float64 geospatial_vertical_max 1083.6;
    Float64 geospatial_vertical_min 402.04;
    String geospatial_vertical_positive "down";
    String geospatial_vertical_units "m";
    String history 
"2024-11-08T05:44:17Z (local files)
2024-11-08T05:44:17Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_659440.das";
    String infoUrl "https://www.bco-dmo.org/dataset/659440";
    String institution "BCO-DMO";
    String instruments_0_acronym "Niskin bottle";
    String instruments_0_dataset_instrument_description "Used to collect water samples";
    String instruments_0_dataset_instrument_nid "659476";
    String instruments_0_description "A Niskin bottle (a next generation water sampler based on the Nansen bottle) is a cylindrical, non-metallic water collection device with stoppers at both ends.  The bottles can be attached individually on a hydrowire or deployed in 12, 24 or 36 bottle Rosette systems mounted on a frame and combined with a CTD.  Niskin bottles are used to collect discrete water samples for a range of measurements including pigments, nutrients, plankton, etc.";
    String instruments_0_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L22/current/TOOL0412/";
    String instruments_0_instrument_name "Niskin bottle";
    String instruments_0_instrument_nid "413";
    String instruments_0_supplied_name "Niskin";
    String instruments_1_dataset_instrument_description "Pump used to collect samples from seafloor or water column";
    String instruments_1_dataset_instrument_nid "659475";
    String instruments_1_description "Small and large capacity vacuum pump samplers. May have single or multiple chambers. See https://www.whoi.edu/main/alvin/subsystems/optional-scientific-samplers";
    String instruments_1_instrument_name "Alvin Slurp Sampler";
    String instruments_1_instrument_nid "644821";
    String instruments_1_supplied_name "Pump";
    String keywords "bco, bco-dmo, biological, chemical, data, dataset, date, depth, dive, dmo, erddap, latitude, log, longitude, management, notes, oceanography, office, preliminary, pump, sample, sampleLog_date, sampleLog_location, sampleLog_notes, sampleLog_pump, sampleLog_sample, sampleLog_seconds, sampleLog_species, sampleLog_time, sec, seconds, species, time, time2, time_sec, utmx, utmy";
    String license "https://www.bco-dmo.org/dataset/659440/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/659440";
    Float64 Northernmost_Northing 29.17450947;
    String param_mapping "{'659440': {'lat': 'master - latitude', 'depth': 'flag - depth', 'lon': 'master - longitude'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/659440/parameters";
    String people_0_affiliation "Temple University";
    String people_0_affiliation_acronym "Temple";
    String people_0_person_name "Erik E Cordes";
    String people_0_person_nid "51539";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "Temple University";
    String people_1_affiliation_acronym "Temple";
    String people_1_person_name "Erik E Cordes";
    String people_1_person_nid "51539";
    String people_1_role "Contact";
    String people_1_role_type "related";
    String people_2_affiliation "Woods Hole Oceanographic Institution";
    String people_2_affiliation_acronym "WHOI BCO-DMO";
    String people_2_person_name "Hannah Ake";
    String people_2_person_nid "650173";
    String people_2_role "BCO-DMO Data Manager";
    String people_2_role_type "related";
    String project "Lophelia OA";
    String projects_0_acronym "Lophelia OA";
    String projects_0_description 
"The Gulf of Mexico deep water ecosystems are threatened by the persistent threat of ocean acidification. Deep-water corals will be among the first to feel the effects of this process, in particular the deep-water scleractinians that form their skeleton from aragonite. The continued shoaling of the aragonite saturation horizon (the depth below which aragonite is undersaturated) will place many of the known, and as yet undiscovered, deep-water corals at risk in the very near future. The most common deep-water framework-forming scleractinian in the world's oceans is Lophelia pertusa. This coral is most abundant in the North Atlantic, where aragonite saturation states are relatively high, but it also creates extensive reef structures between 300 and 600 m depth in the Gulf of Mexico where aragonite saturation states were previously unknown. Preliminary data indicate that pH at this depth range is between 7.85 and 8.03, and the aragonite saturation state is typically between 1.28 and 1.69. These are the first measurements of aragonite saturation state for the deep Gulf of Mexico, and are among the lowest Aragonite saturation state yet recorded for framework-forming corals in any body of water, at any depth.
This project will examine the effects of ocean acidification on L. pertusa, combining laboratory experiments, rigorous oceanographic measurements, the latest genome and transcriptome sequencing platforms, and quantitative PCR and enzyme assays to examine changes in coral gene expression and enzyme activity related to differences in carbonate chemistry. Short-term and long-term laboratory experiments will be performed at Aragonite saturation state of 1.45 and 0.75 and the organismal (e.g., survivorship and calcification rate) and genetic (e.g., transcript abundance) responses of the coral will be monitored. Genomic DNA and RNA will be extracted, total mRNA purified, and comprehensive and quantitative profiles of the transcriptome generated using a combination of 454 and Illumina sequencing technologies. Key genes in the calcification pathways as well as other differentially expressed genes will be targeted for specific qPCR assays to verify the Illumina sequencing results. On a research cruise, L. pertusa will be sampled (preserved at depth) along a natural gradient in carbonate chemistry, and included in the Illumina sequencing and qPCR assays. Water samples will be obtained by submersible-deployed niskin bottles adjacent to the coral collections as well as CTD casts of the water column overlying the sites. Water samples will be analyzed for pH, alkalinity, nitrates and soluble reactive phosphorus. These will be used in combination with historical data in a model to hindcast Aragonite saturation state.
This project will provide new physiological and genetic data on an ecologically-significant and anthropogenically-threatened deepwater coral in the Gulf of Mexico. An experimental system, already developed by the PIs, offers controlled conditions to test the effect of Aragonite saturation state on calcification rates in scleractinians and, subsequently, to identify candidate genes and pathways involved in the response to reduced pH and Aragonite saturation state. Both long-term and population sampling experiments will provide additional transcriptomic data and specifically investigate the expression of the candidate genes. These results will contribute to our understanding of the means by which scleractinians may acclimate and acclimatize to low pH, alkalinity, and Aragonite saturation state. Furthermore, the investigators will continue a time series of oceanographic measurements of the carbonate system in the Gulf of Mexico, which will allow the inclusion of this significant body of water in models of past and future ocean acidification scenarios.";
    String projects_0_end_date "2015-08";
    String projects_0_geolocation "Northern Gulf of Mexico";
    String projects_0_name "Physiological and genetic responses of the deep-water coral, Lophelia pertusa, to ongoing ocean acidification in the Gulf of Mexico";
    String projects_0_project_nid "2224";
    String projects_0_start_date "2012-09";
    String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
    String publisher_type "institution";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 27.08029275;
    String standard_name_vocabulary "CF Standard Name Table v55";
    String summary "Sample logs from R/V Atlantis (AT26-14) Alvin dives in the Gulf of Mexico during 2014 (Lophelia OA project)";
    String title "[AT26-14 Alvin sample logs] - Sample logs from R/V Atlantis (AT26-14) Alvin dives in the Gulf of Mexico during 2014 (Lophelia OA project) (Physiological and genetic responses of the deep-water coral, Lophelia pertusa, to ongoing ocean acidification in the Gulf of Mexico)";
    String version "1";
    Float64 Westernmost_Easting -93.59891607;
    String xml_source "osprey2erddap.update_xml() v1.3";
  }
}

 

Using tabledap to Request Data and Graphs from Tabular Datasets

tabledap lets you request a data subset, a graph, or a map from a tabular dataset (for example, buoy data), via a specially formed URL. tabledap uses the OPeNDAP (external link) Data Access Protocol (DAP) (external link) and its selection constraints (external link).

The URL specifies what you want: the dataset, a description of the graph or the subset of the data, and the file type for the response.

Tabledap request URLs must be in the form
https://coastwatch.pfeg.noaa.gov/erddap/tabledap/datasetID.fileType{?query}
For example,
https://coastwatch.pfeg.noaa.gov/erddap/tabledap/pmelTaoDySst.htmlTable?longitude,latitude,time,station,wmo_platform_code,T_25&time>=2015-05-23T12:00:00Z&time<=2015-05-31T12:00:00Z
Thus, the query is often a comma-separated list of desired variable names, followed by a collection of constraints (e.g., variable<value), each preceded by '&' (which is interpreted as "AND").

For details, see the tabledap Documentation.


 
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