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Dataset Title:  Tank conditions for pH experiments on Lophelia pertusa specimens collected in
the Norwegian Skagerrak and the Gulf of Mexico (Lophelia OA project)
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_659426)
Information:  Summary ? | License ? | ISO 19115 | Metadata | Background (external link) | Data Access Form | Files
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Things You Can Do With Your Graphs

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The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  location {
    String bcodmo_name "site";
    String description "Location where specimen was collected; Tisler Reef or the Gulf of Mexico";
    String long_name "Location";
    String units "unitless";
  pH_treatment {
    Float32 _FillValue NaN;
    Float32 actual_range 7.6, 8.1;
    String bcodmo_name "treatment";
    String description "Level of pH treatment";
    String long_name "P H Treatment";
    String units "unitless";
  tank {
    Byte _FillValue 127;
    Byte actual_range 1, 8;
    String bcodmo_name "tank";
    String description "Tank number";
    String long_name "Tank";
    String units "unitless";
  day {
    Byte _FillValue 127;
    Byte actual_range 1, 14;
    String bcodmo_name "day";
    String description "day of month";
    String long_name "Day";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/DAYXXXXX/";
    String units "dimensionless";
  DO {
    Float32 _FillValue NaN;
    Float32 actual_range 92.8, 249.1;
    String bcodmo_name "O2_umol_kg";
    String description "Dissolved oxygen level in tank";
    String long_name "DO";
    String units "micromoles per kilogram (umol/kg)";
  ttl_alkalinity {
    Float32 _FillValue NaN;
    Float32 actual_range 2237.98, 2353.06;
    String bcodmo_name "TALK";
    String description "Total alkanlinity of tank";
    String long_name "Ttl Alkalinity";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/MDMAP014/";
    String units "micromoles per kilogram (umol/kg)";
  salinity {
    Float32 _FillValue NaN;
    Float32 actual_range 7.75, 36.0;
    String bcodmo_name "sal";
    Float64 colorBarMaximum 37.0;
    Float64 colorBarMinimum 32.0;
    String description "Salinity of water in tank";
    String long_name "Sea Water Practical Salinity";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/PSALST01/";
    String units "practical salinity unit (PSU)";
  temperature {
    Float32 _FillValue NaN;
    Float32 actual_range 7.68, 33.8;
    String bcodmo_name "temperature";
    String description "Temperature of water in tank";
    String long_name "Temperature";
    String units "celsius";
  pH {
    Float32 _FillValue NaN;
    Float32 actual_range 7.51, 8.17;
    String bcodmo_name "pH";
    Float64 colorBarMaximum 9.0;
    Float64 colorBarMinimum 7.0;
    String description "pH level of water in tank";
    String long_name "Sea Water Ph Reported On Total Scale";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/PHXXZZXX/";
    String units "unitless";
  aragonite_saturation_state {
    Float32 _FillValue NaN;
    Float32 actual_range 0.61, 2.38;
    String bcodmo_name "OM_ar";
    String description "saturation state of aragonite";
    String long_name "Aragonite Saturation State";
    String units "unitless";
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv";
    String acquisition_description 
"Acquisition Description for Tisler\\u00a0Reef Data:
Net calcification was measured using the total alkalinity anomaly (Smith & Key
1975; Ohde & Hossain 2004). Corals were individually placed in closed glass
chambers (220 ml) in a water bath that maintained temperature to +/-0.2
degrees C during all trials. To avoid hypoxia or the severe reductions of pH
during incubations, ambient air was continuously bubbled into the chambers at
a slow rate (1-2 bubbles s-1). This also provided adequate circulation within
the chamber. A 60 ml water sample was collected by syringe before and after
the incubation period, and measured for total alkalinity in duplicate. The
respiration rate of each colony was measured as oxygen consumption in
a\\u00a0400 ml closed acrylic chamber during hour-long incubations. Dissolved
oxygen concentrations were measured in\\u00a0umol\\u00a0L-1\\u00a0using a
Strathkelvin 782 dual oxygen meter and SI130\\u00a0microcathode\\u00a0electrode.
The feeding rate of each colony was measured as the capture rate of
adult\\u00a0Artemia salina\\u00a0during a one-hour period in 0.8 L incubation
chambers containing a starting prey density of 125\\u00a0Artemia\\u00a0L-1.
Acquisition Description for Gulf of Mexico Data:
The buoyant weight of each colony was obtained at the start and end of the
two-week experimental period by weighing fragments submerged in seawater and
attached by a hook to an analytical balance (Denver
Instrument,\\u00a0precision\\u00a0of 0.1 mg). The respiration rate of each
colony was measured as oxygen consumption in an 800 ml closed acrylic chamber
during hour-long incubations. Dissolved oxygen concentrations were measured
in\\u00a0umol\\u00a0L-1\\u00a0using a Strathkelvin 782 dual oxygen meter and
SI130\\u00a0microcathode\\u00a0electrode. The feeding rate of each colony was
measured as the capture rate of adult\\u00a0Artemia salina\\u00a0during a one-
hour period in 0.8 L incubation chambers containing a starting prey density of
    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 
"Physiology - Water Chemistry 
  E. Cordes & R. Kulalthinal, PIs 
  Version 16 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 "2016-09-20T21:30:08Z";
    String date_modified "2019-04-24T15:31:53Z";
    String defaultDataQuery "&time<now";
    String doi "10.1575/1912/bco-dmo.659426.1";
    String history 
"2022-08-16T03:17:20Z (local files)
2022-08-16T03:17:20Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_659426.das";
    String infoUrl "https://www.bco-dmo.org/dataset/659426";
    String institution "BCO-DMO";
    String instruments_0_acronym "Water Temp Sensor";
    String instruments_0_dataset_instrument_description "Indicates water temperature";
    String instruments_0_dataset_instrument_nid "659609";
    String instruments_0_description "General term for an instrument that measures the temperature of the water with which it is in contact (thermometer).";
    String instruments_0_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/134/";
    String instruments_0_instrument_name "Water Temperature Sensor";
    String instruments_0_instrument_nid "647";
    String instruments_0_supplied_name "Temperature sensor";
    String instruments_1_acronym "pH Sensor";
    String instruments_1_dataset_instrument_description "Indicates pH of water";
    String instruments_1_dataset_instrument_nid "659611";
    String instruments_1_description "General term for an instrument that measures the pH or how acidic or basic a solution is.";
    String instruments_1_instrument_name "pH Sensor";
    String instruments_1_instrument_nid "674";
    String instruments_1_supplied_name "pH sensor";
    String instruments_2_acronym "O2 microsensor";
    String instruments_2_dataset_instrument_description "Measured dissolved oxygen concentrations";
    String instruments_2_dataset_instrument_nid "659435";
    String instruments_2_description "A miniaturized Clark-type dissolved oxygen instrument, including glass micro-sensors with minute tips (diameters ranging from 1 to 800 um). A gold or platinum sensing cathode is polarized against an internal reference and, driven by external partial pressure, oxygen from the environment penetrates through the sensor tip membrane and is reduced at the sensing cathode surface. A picoammeter converts the resulting reduction current to a signal. The size of the signal generated by the electrode is proportional to the flux of oxygen molecules to the cathode.The sensor also includes a polarized guard cathode, which scavenges oxygen in the electrolyte, thus minimizing zero-current and pre-polarization time.With the addition of a meter and a sample chamber, the respiration of a small specimen can be measured.  Example: Strathkelvin Inst. http://www.strathkelvin.com";
    String instruments_2_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/351/";
    String instruments_2_instrument_name "Oxygen Microelectrode Sensor";
    String instruments_2_instrument_nid "701";
    String instruments_2_supplied_name "SI130 microcathode electrode";
    String instruments_3_acronym "Dissolved Oxygen Sensor";
    String instruments_3_dataset_instrument_description "Measured dissolved oxygen concentrations";
    String instruments_3_dataset_instrument_nid "659436";
    String instruments_3_description "An electronic device that measures the proportion of oxygen (O2) in the gas or liquid being analyzed";
    String instruments_3_instrument_name "Dissolved Oxygen Sensor";
    String instruments_3_instrument_nid "705";
    String instruments_3_supplied_name "Strathkelvin 782 dual oxygen meter";
    String instruments_4_acronym "Salinity Sensor";
    String instruments_4_dataset_instrument_description "Indicates salinity of water";
    String instruments_4_dataset_instrument_nid "659610";
    String instruments_4_description "Category of instrument that simultaneously measures electrical conductivity and temperature in the water column to provide temperature and salinity data.";
    String instruments_4_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/350/";
    String instruments_4_instrument_name "Salinity Sensor";
    String instruments_4_instrument_nid "710";
    String instruments_4_supplied_name "Salinity sensor";
    String keywords "alkalinity, aragonite, aragonite_saturation_state, bco, bco-dmo, biological, chemical, chemistry, data, dataset, day, density, dmo, earth, Earth Science > Oceans > Ocean Chemistry > pH, Earth Science > Oceans > Salinity/Density > Salinity, erddap, management, ocean, oceanography, oceans, office, pH_treatment, practical, preliminary, reported, salinity, saturation, scale, science, sea, sea_water_ph_reported_on_total_scale, sea_water_practical_salinity, seawater, state, tank, temperature, total, treatment, ttl, ttl_alkalinity, water";
    String keywords_vocabulary "GCMD Science Keywords";
    String license "https://www.bco-dmo.org/dataset/659426/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/659426";
    String param_mapping "{'659426': {}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/659426/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 "Dr Robert  J. Kulathinal";
    String people_1_person_nid "51540";
    String people_1_role "Co-Principal Investigator";
    String people_1_role_type "originator";
    String people_2_affiliation "Temple University";
    String people_2_affiliation_acronym "Temple";
    String people_2_person_name "Erik E Cordes";
    String people_2_person_nid "51539";
    String people_2_role "Contact";
    String people_2_role_type "related";
    String people_3_affiliation "Woods Hole Oceanographic Institution";
    String people_3_affiliation_acronym "WHOI BCO-DMO";
    String people_3_person_name "Hannah Ake";
    String people_3_person_nid "650173";
    String people_3_role "BCO-DMO Data Manager";
    String people_3_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)";
    String standard_name_vocabulary "CF Standard Name Table v55";
    String summary "Tank conditions for pH experiments on Lophelia pertusa specimens collected in the Norwegian Skagerrak and the Gulf of Mexico (Lophelia OA project)";
    String title "Tank conditions for pH experiments on Lophelia pertusa specimens collected in the Norwegian Skagerrak and the Gulf of Mexico (Lophelia OA project)";
    String version "1";
    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
For example,
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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