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Dataset Title:  Global observations Prochlorococcus, Synechococcus, and picoeukaryotic
phytoplankton with ancillary environmental data from 1987 to 2008
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_793451)
Range: longitude = 0.59829 to 359.92°E, latitude = -78.05 to 81.162°N, depth = 0.0 to 5441.0m
Information:  Summary ? | License ? | 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 {
  Year {
    Int16 _FillValue 32767;
    Int16 actual_range 1987, 2008;
    String bcodmo_name "year";
    String description "year (format:YYYY)";
    String long_name "Year";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/YEARXXXX/";
    String units "unitless";
  }
  Day {
    Int16 _FillValue 32767;
    Int16 actual_range 1, 366;
    String bcodmo_name "julian_day";
    String description "Julian day";
    String long_name "Day";
    String units "unitless";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 _FillValue NaN;
    Float64 actual_range -78.05, 81.162;
    String axis "Y";
    String bcodmo_name "latitude";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String description "Latitude, south is negative";
    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 0.59829, 359.92;
    String axis "X";
    String bcodmo_name "longitude";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String description "Longitude, west is negative";
    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";
  }
  Nitrite_Nitrate {
    Float64 _FillValue NaN;
    Float64 actual_range -0.056, 147.35;
    String bcodmo_name "NO3_NO2";
    Float64 colorBarMaximum 50.0;
    Float64 colorBarMinimum 0.0;
    String description "Sun of nitrite and nitrate concentration";
    String long_name "Mole Concentration Of Nitrate In Sea Water";
    String units "Micromoles per Liter (umol/l)";
  }
  Phosphate {
    Float64 _FillValue NaN;
    Float64 actual_range -0.04, 367.0;
    String bcodmo_name "PO4";
    String description "Phosphate concentration";
    String long_name "Mass Concentration Of Phosphate In Sea Water";
    String units "Micromoles per Liter (umol/l)";
  }
  Temperature {
    Float64 _FillValue NaN;
    Float64 actual_range -1.976, 35.43;
    String bcodmo_name "temperature";
    String description "Water temperature";
    String long_name "Temperature";
    String units "Degrees Celcius (°C)";
  }
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    Float64 _FillValue NaN;
    Float64 actual_range 0.0, 5441.0;
    String axis "Z";
    String bcodmo_name "depth";
    Float64 colorBarMaximum 8000.0;
    Float64 colorBarMinimum -8000.0;
    String colorBarPalette "TopographyDepth";
    String description "Water column depth";
    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";
  }
  Prochlorococcus {
    Float64 _FillValue NaN;
    Float64 actual_range 0.0, 1820000.0;
    String bcodmo_name "coccus_p";
    String description "Cell abundance";
    String long_name "Prochlorococcus";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/P701A90Z/";
    String units "Cells per milliliter (cells/ml)";
  }
  Synechococcus {
    Float64 _FillValue NaN;
    Float64 actual_range 0.0, 3720000.0;
    String bcodmo_name "coccus_s";
    String description "Cell abundance";
    String long_name "Synechococcus";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/PATX/";
    String units "Cells per milliliter (cells/ml)";
  }
  Pico_eukaryotes {
    Float64 _FillValue NaN;
    Float64 actual_range 0.0, 576000.0;
    String bcodmo_name "pico_euks";
    String description "Picoeukaryotic phytoplankton cell abundance";
    String long_name "Pico Eukaryotes";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/PNTX";
    String units "Cells per milliliter (cells/ml)";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson";
    String acquisition_description 
"We compiled in situ observations with ancillary environment data of
Prochlorococcus, Synechococcus and picoeukaryotic phytoplankton abundances in
the global ocean.
 
For list of cruises and time series included please refer to Flombaum et al.,
2013 Table S1 for Prochlorococcus and Synechococcus, and to Flombaum et al.,
in press Supplementary Table 1.";
    String awards_0_award_nid "764269";
    String awards_0_award_number "OCE-1848576";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1848576";
    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 "Michael E. Sieracki";
    String awards_0_program_manager_nid "50446";
    String awards_1_award_nid "783470";
    String awards_1_award_number "PICT-2017-3020";
    String awards_1_funder_name "Agencia Nacional de Promoción Científica y Tecnológica";
    String awards_1_funding_source_nid "783468";
    String awards_2_award_nid "783471";
    String awards_2_award_number "UBACyT 20020170100620BA";
    String awards_2_funder_name "Universidad de Buenos Aires";
    String awards_2_funding_source_nid "783469";
    String cdm_data_type "Other";
    String comment 
"Global obs 
  PI: Adam Martiny  
  Data Version data: 2020-02-14";
    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 "2020-02-13T20:26:30Z";
    String date_modified "2020-03-10T21:20:18Z";
    String defaultDataQuery "&time<now";
    String doi "10.1575/1912/bco-dmo.793451.1";
    Float64 Easternmost_Easting 359.92;
    Float64 geospatial_lat_max 81.162;
    Float64 geospatial_lat_min -78.05;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max 359.92;
    Float64 geospatial_lon_min 0.59829;
    String geospatial_lon_units "degrees_east";
    Float64 geospatial_vertical_max 5441.0;
    Float64 geospatial_vertical_min 0.0;
    String geospatial_vertical_positive "down";
    String geospatial_vertical_units "m";
    String history 
"2024-03-29T08:58:54Z (local files)
2024-03-29T08:58:54Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_793451.das";
    String infoUrl "https://www.bco-dmo.org/dataset/793451";
    String institution "BCO-DMO";
    String keywords "bco, bco-dmo, biological, chemical, chemistry, concentration, data, dataset, day, depth, dmo, earth, Earth Science > Oceans > Ocean Chemistry > Nitrate, Earth Science > Oceans > Ocean Chemistry > Phosphate, erddap, eukaryotes, latitude, longitude, management, mass, mass_concentration_of_phosphate_in_sea_water, mole, mole_concentration_of_nitrate_in_sea_water, n02, nitrate, Nitrite_Nitrate, no3, ocean, oceanography, oceans, office, phosphate, pico, Pico_eukaryotes, po4, preliminary, prochlorococcus, science, sea, seawater, synechococcus, temperature, water, year";
    String keywords_vocabulary "GCMD Science Keywords";
    String license "https://www.bco-dmo.org/dataset/793451/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/793451";
    Float64 Northernmost_Northing 81.162;
    String param_mapping "{'793451': {'Latitude': 'master - latitude', 'Depth': 'master - depth', 'Longitude': 'master - longitude'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/793451/parameters";
    String people_0_affiliation "University of California-Irvine";
    String people_0_affiliation_acronym "UC Irvine";
    String people_0_person_name "Adam Martiny";
    String people_0_person_nid "51402";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "Universidad de Buenos Aires";
    String people_1_person_name "Pedro Flombaum";
    String people_1_person_nid "783475";
    String people_1_role "Co-Principal Investigator";
    String people_1_role_type "originator";
    String people_2_affiliation "Universidad de Buenos Aires";
    String people_2_person_name "Pedro Flombaum";
    String people_2_person_nid "783475";
    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 "Karen Soenen";
    String people_3_person_nid "748773";
    String people_3_role "BCO-DMO Data Manager";
    String people_3_role_type "related";
    String project "Ocean_Stoichiometry";
    String projects_0_acronym "Ocean_Stoichiometry";
    String projects_0_description 
"NSF Award Abstract:
Due to their sheer abundance and high activity, microorganisms have the potential to greatly influence how ecosystems are affected by changes in their environment. However, descriptions of microbial physiology and diversity are local and highly complex and thus rarely considered in Earth System Models. Thus, the researchers focus on a convergence research framework that can qualitatively and quantitatively integrate eco-evolutionary changes in microorganisms with global biogeochemistry. Here, the investigators will develop an approach that integrates the knowledge and tools of biologists, mathematicians, engineers, and geoscientists to understand the link between the ocean nutrient and carbon cycles. The integration of data and knowledge from diverse fields will provide a robust, biologically rich, and computationally efficient prediction for the variation in plankton resource requirements and the biogeochemical implications, addressing a fundamental challenge in ocean science. In addition, the project can serve as a road map for many other research groups facing a similar lack of convergence between biology and geoscience.
Traditionally, the cellular elemental ratios of Carbon, Nitrogen, and Phosphorus (C:N:P) of marine communities have been considered static at Redfield proportions but recent studies have demonstrated strong latitudinal variation. Such regional variation may have large - but poorly constrained - implications for marine biodiversity, biogeochemical functioning, and atmospheric carbon dioxide levels. As such, variations in ocean community C:N:P may represent an important biological feedback. Here, the investigators propose a convergence research framework integrating cellular and ecological processes controlling microbial resource allocations with an Earth System model. The approach combines culture experiments and omics measurements to provide a molecular understanding of cellular resource allocations. Using a mathematical framework of increasing complexity describing communicating, moving demes, the team will quantify the extent to which local mixing, environmental heterogeneity and evolution lead to systematic deviations in plankton resource allocations and C:N:P. Optimization tools from engineering science will be used to facilitate the quantitative integration of models and observations across a range of scales and complexity levels. Finally, global ocean modeling will enable understanding of how plankton resource use impacts Earth System processes. By integrating data and knowledge across fields, scales and complexity, the investigators will develop a robust link between variation in plankton C:N:P and global biogeochemical cycles.";
    String projects_0_end_date "2021-08";
    String projects_0_name "Convergence: RAISE: Linking the adaptive dynamics of plankton with emergent global ocean biogeochemistry";
    String projects_0_project_nid "764270";
    String projects_0_start_date "2018-09";
    String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
    String publisher_type "institution";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing -78.05;
    String standard_name_vocabulary "CF Standard Name Table v55";
    String summary "Prochlorococcus, Synechococcus, and picoeukaryotic phytoplankton global observations with ancillary environmental data (nitrate, phosphate and temperature)from 1987 to 2008.";
    String title "Global observations Prochlorococcus, Synechococcus, and picoeukaryotic phytoplankton with ancillary environmental data from 1987 to 2008";
    String version "1";
    Float64 Westernmost_Easting 0.59829;
    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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