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Dataset Title:  [bacteria_ice] - Ice core bacteria data from RVIB Nathaniel B. Palmerand ARSV
Laurence M. Gould cruises NBP0104, LMG0106, NBP0204,and LMG0205 in the Southern
Ocean from 2001-2002 (SOGLOBEC project; Sea Ice Microbes project) (U.S. GLOBEC
Southern Ocean)
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_2348)
Range: longitude = -76.781 to -65.61°E, latitude = -69.25 to -65.62°N
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 {
  cruiseid {
    String bcodmo_name "cruiseid";
    String description "cruise identification";
    String long_name "Cruiseid";
  }
  year {
    Int16 _FillValue 32767;
    Int16 actual_range 2001, 2002;
    String bcodmo_name "year";
    String description "year";
    String long_name "Year";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/YEARXXXX/";
  }
  station {
    String bcodmo_name "station";
    String description "station identification";
    String long_name "Station";
  }
  event {
    Float64 _FillValue NaN;
    Float64 actual_range 19.0, 25402.011;
    String bcodmo_name "event";
    String description "event number from event log";
    String long_name "Event";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/EVTAGFL/";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 _FillValue NaN;
    Float64 actual_range -69.25, -65.62;
    String axis "Y";
    String bcodmo_name "latitude";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String description "latitude, negative = South";
    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 -76.781, -65.61;
    String axis "X";
    String bcodmo_name "longitude";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String description "longitude, negative = West";
    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";
  }
  month_gmt {
    String bcodmo_name "month_gmt";
    String description "month of year";
    String long_name "Month Gmt";
    String units "GMT";
  }
  day_gmt {
    String bcodmo_name "day_gmt";
    String description "day of month";
    String long_name "Day Gmt";
    String units "GMT";
  }
  yrday_gmt {
    Int16 _FillValue 32767;
    Int16 actual_range 209, 254;
    String bcodmo_name "yrday_gmt";
    String long_name "Yrday Gmt";
    String units "GMT";
  }
  core_no {
    String bcodmo_name "core_id";
    String description "ice core number/identification";
    String long_name "Core No";
  }
  sect_top_depth {
    String bcodmo_name "unknown";
    String description "top depth of ice core interval sampled";
    String long_name "Sect Top Depth";
    String units "decimal meters";
  }
  sect_bot_depth {
    Float64 _FillValue NaN;
    Float64 actual_range 0.05, 3.16;
    String bcodmo_name "unknown";
    String description "bottom depth of ice core interval sampled";
    String long_name "Sect Bot Depth";
    String units "decimal meters";
  }
  bact_abun {
    Float64 _FillValue NaN;
    Float64 actual_range 1.33e+9, 5.34e+11;
    String bcodmo_name "bact_abundance";
    String description "bacteria abundance";
    String long_name "Bact Abun";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/BNTX";
    String units "cells/meter3";
  }
  bact_biomass_C {
    Float32 _FillValue NaN;
    Float32 actual_range 0.02, 5.72;
    String bcodmo_name "bact_biomass_C";
    String description "bacteria carbon biomass";
    String long_name "Bact Biomass C";
    String units "milligrams C/meter3";
  }
  chl_a_ugm {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 238.81;
    String bcodmo_name "chl_a_ugm";
    Float64 colorBarMaximum 30.0;
    Float64 colorBarMinimum 0.03;
    String colorBarScale "Log";
    String description "total chlorophyll a pigment concentration";
    String long_name "Concentration Of Chlorophyll In Sea Water";
    String units "micrograms/liter";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson";
    String acquisition_description 
"Sampling methods for recovery of chlorophyll a and bacteria from sea ice cores
follows those described in:  
 Garrison, D.L. and K.R. Buck(1986), Organism losses during ice melting: a
serious bias in sea ice community studies. Polar Biol., 6:237-239.
 
Recommendations for reporting were used as outlined by:  
 Horner, R. et al.,(1992), Ecology of Sea Ice Biota. I: Habitat, Terminology
and Methodology.  Polar Biol. 12:417-427
 
    
     #  Ice core bacteria data from Southern Ocean GLOBEC #     C. Fritsen and F. Stewart #            * BactAbun = bacterial abundance = cells m-3 #            * BactBio = bacterial biomass = mg C m-3 = ug C l-1 #            * chla = mg chla m-3 = ug chla l-1 #            * sect_top_depth = depth(m) at top of core section";
    String awards_0_award_nid "54688";
    String awards_0_award_number "ANT-9910098";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=9910098";
    String awards_0_funder_name "NSF Antarctic Sciences";
    String awards_0_funding_acronym "NSF ANT";
    String awards_0_funding_source_nid "369";
    String awards_0_program_manager "Dr Roberta Marinelli";
    String awards_0_program_manager_nid "51469";
    String cdm_data_type "Other";
    String comment 
"Ice core bacteria data from Southern Ocean GLOBEC 
     C. Fritsen and F. Stewart 
            * BactAbun = bacterial abundance = cells m-3 
            * BactBio = bacterial biomass = mg C m-3 = ug C l-1 
            * chla = mg chla m-3 = ug chla l-1 
            * sect_top_depth = depth(m) at top of core section 
            * sect_bot_depth = depth(m) at bottom of core section 
  NBP0104: core 4, sect_top_depth changed from -0.39 to 0.00 (mda 8/18/03) 
         : CR-27DNA renumbered CR-26DNA. (mda 8/18/03) 
  LMG0106: \"a\" \"b\" \"c\" labels appended to core numbers denote replicate cores. 
            \"-1\" \"-2\" \"-3\" labels appended to core numbers denote different 
  NBP0204: Bacteria Abundance and Bacteria Carbon Biomass  
                were not routinely sampled on this cruise. 
           The term slush in the core interval field for core_no 17  
                indicates that slush/unconsolidated ice existed between 
                sections of ice cores from the same ice coring hole. 
  LMG0205: Bacteria Abundance and Bacteria Carbon Biomass were not routinely 
              sampled on this cruise. 
           Corrections have been applied to the data per Fritsen's e-mail  
              of 12/03/03.";
    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 "2009-11-25T16:49:37Z";
    String date_modified "2019-03-04T18:24:19Z";
    String defaultDataQuery "&time<now";
    String doi "10.1575/1912/bco-dmo.2348.1";
    Float64 Easternmost_Easting -65.61;
    Float64 geospatial_lat_max -65.62;
    Float64 geospatial_lat_min -69.25;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -65.61;
    Float64 geospatial_lon_min -76.781;
    String geospatial_lon_units "degrees_east";
    String history 
"2024-11-06T00:39:59Z (local files)
2024-11-06T00:39:59Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_2348.das";
    String infoUrl "https://www.bco-dmo.org/dataset/2348";
    String institution "BCO-DMO";
    String instruments_0_acronym "Ice Corer";
    String instruments_0_dataset_instrument_description "Ice Cores used to collect Bacteria Abundance, Biomass and Chlorophyll a data";
    String instruments_0_dataset_instrument_nid "4168";
    String instruments_0_description "An ice corer is used to drill into deep ice and remove long cylinders of ice from which information about the past and present can be inferred. Polar ice cores contain a record of the past atmosphere - temperature, precipitation, gas content, chemical composition, and other properties. This can reveal a broad spectrum of information on past environmental, and particularly climatic, changes. They can also be used to study bacteria and chlorophyll production in the waters from which the ice core was extracted.";
    String instruments_0_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/56/";
    String instruments_0_instrument_name "Ice Corer";
    String instruments_0_instrument_nid "462";
    String instruments_0_supplied_name "IceCoring";
    String keywords "abun, bact, bact_abun, bact_biomass_C, bco, bco-dmo, biological, biomass, bot, chemical, chemistry, chl_a_ugm, chlorophyll, concentration, concentration_of_chlorophyll_in_sea_water, core, core_no, cruiseid, data, dataset, day, day_gmt, depth, dmo, earth, Earth Science > Oceans > Ocean Chemistry > Chlorophyll, erddap, event, latitude, longitude, management, month, month_gmt, ocean, oceanography, oceans, office, preliminary, science, sea, seawater, sect, sect_bot_depth, sect_top_depth, station, top, water, year, yrday, yrday_gmt";
    String keywords_vocabulary "GCMD Science Keywords";
    String license "https://www.bco-dmo.org/dataset/2348/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/2348";
    Float64 Northernmost_Northing -65.62;
    String param_mapping "{'2348': {'lat': 'master - latitude', 'lon': 'master - longitude', 'sect_bot_depth': 'flag - depth'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/2348/parameters";
    String people_0_affiliation "Desert Research Institute";
    String people_0_affiliation_acronym "DRI";
    String people_0_person_name "Dr Chris H. Fritsen";
    String people_0_person_nid "50502";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "Woods Hole Oceanographic Institution";
    String people_1_affiliation_acronym "WHOI BCO-DMO";
    String people_1_person_name "Ms Dicky Allison";
    String people_1_person_nid "50382";
    String people_1_role "BCO-DMO Data Manager";
    String people_1_role_type "related";
    String project "SOGLOBEC,Sea Ice Microbes";
    String projects_0_acronym "SOGLOBEC";
    String projects_0_description "The fundamental objectives of United States Global Ocean Ecosystems Dynamics (U.S. GLOBEC) Program are dependent upon the cooperation of scientists from several disciplines. Physicists, biologists, and chemists must make use of data collected during U.S. GLOBEC field programs to further our understanding of the interplay of physics, biology, and chemistry. Our objectives require quantitative analysis of interdisciplinary data sets and, therefore, data must be exchanged between researchers. To extract the full scientific value, data must be made available to the scientific community on a timely basis.";
    String projects_0_geolocation "Southern Ocean";
    String projects_0_name "U.S. GLOBEC Southern Ocean";
    String projects_0_project_nid "2039";
    String projects_0_project_website "http://www.ccpo.odu.edu/Research/globec_menu.html";
    String projects_0_start_date "2001-01";
    String projects_1_acronym "Sea Ice Microbes";
    String projects_1_description "The U.S. Global Ocean Ecosystems Dynamics (U.S. GLOBEC) program has the goal of understanding and ultimately predicting how populations of marine animal species respond to natural and anthropogenic changes in climate. Research in the Southern Ocean (SO) indicates strong coupling between climatic processes and ecosystem dynamics via the annual formation and destruction of sea ice. The Southern Ocean GLOBEC Program (SO GLOBEC) will investigate the dynamic relationship between physical processes and ecosystem responses through identification of critical parameters that affect the distribution, abundance and population dynamics of target species. The overall goals of the SO GLOBEC program are to elucidate shelf circulation processes and their effect on sea ice formation and krill distribution, and to examine the factors which govern krill survivorship and availability to higher trophic levels, including penguins, seals and whales. The focus of the U.S. contribution to the international SO GLOBEC program will be on winter processes. This component will focus on the distribution and activities of sea ice microbial communities. This will be accomplished using an integrated combination of sampling (vertical profiles, horizontal surveys, and under-ice surveys) and observational protocols. Experiments will be designed to estimate microbial activity within the sea ice and at the ice-seawater interface. The research will be coordinated with components studying the water column productivity and the sea ice habitat. The result of the integrated SO GLOBEC program will be to improve the predictability of living marine resources, especially with respect to local and global climatic shifts.";
    String projects_1_end_date "2005-08";
    String projects_1_geolocation "Southern Ocean";
    String projects_1_name "GLOBEC: Sea Ice Microbial Communities";
    String projects_1_project_nid "616163";
    String projects_1_start_date "2000-09";
    String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
    String publisher_type "institution";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing -69.25;
    String standard_name_vocabulary "CF Standard Name Table v55";
    String summary "Ice core bacteria data from RVIB Nathaniel B. Palmerand ARSV Laurence M. Gould cruises NBP0104, LMG0106, NBP0204,and LMG0205 in the Southern Ocean from 2001-2002 (SOGLOBEC project; Sea Ice Microbes project)";
    String title "[bacteria_ice] - Ice core bacteria data from RVIB Nathaniel B. Palmerand ARSV Laurence M. Gould cruises NBP0104, LMG0106, NBP0204,and LMG0205 in the Southern Ocean from 2001-2002 (SOGLOBEC project; Sea Ice Microbes project) (U.S. GLOBEC Southern Ocean)";
    String version "1";
    Float64 Westernmost_Easting -76.781;
    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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