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Dataset Title:  [Kāneʻohe Bay Time-series - microbial community] - Flow cytometry, 16S rRNA
gene amplicons, chlorophyll a, and surface seawater measurements taken between
August 2017 to June 2019 Kāneʻohe Bay, Oʻahu, Hawaiʻi (Population genomics and
ecotypic divergence in the most dominant lineage of marine bacteria)
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_930084_v1)
Information:  Summary ? | License ? | FGDC | ISO 19115 | Metadata | Background (external link) | Files | Make a graph
 
Variable ?   Optional
Constraint #1 ?
Optional
Constraint #2 ?
   Minimum ?
 
   Maximum ?
 
 Sample_ID (unitless) ?          "AR419_R2"    "STSe0270"
 collection_date (unitless) ?          "2017-08-23"    "2019-06-14"
 depth (m) ?          2    2
  < slider >
 env_broad_scale (unitless) ?          "surface seawater"    "surface seawater"
 env_local_scale (unitless) ?          "Coastal"    "Transition"
 env_medium (unitless) ?          "seawater"    "seawater"
 geo_loc_name (unitless) ?          "Pacific Ocean: Oah..."    "Pacific Ocean: Oah..."
 latitude (degrees_north) ?          21.43635    21.526
  < slider >
 longitude (degrees_east) ?          -157.8358    -157.7663
  < slider >
 Site_name (unitless) ?          "AR"    "STO1"
 chlorophyll_a_ug_per_L (micrograms per Liter) ?          0.22    2.74
 ph (no unit) ?          7.45    8.64
 salinity (ppt) ?          31.81    36.97
 Seawater_temperature (degrees Celsius (°C)) ?          23.07    28.99
 Prochlorococcus_cells_per_mL (cells per mL) ?          0    113833
 Synechococcus_cells_per_mL (cells per mL) ?          2074    517913
 Heterotrophic_bacteria_cells_per_mL (cells per mL) ?          348075    2667000
 Eukaryotic_picophytoplankton_cells_per_mL (cells per mL) ?          1549    117338
 Universal_Sample_ID (unitless) ?          "KBT_01.11.2019_AR"    "KBT_12.08.2017_STO1"
 SRA_accession (unitless) ?          "SRR13859927"    "SRR13860126"
 study (unitless) ?          "SRP309369"    "SRP309369"
 bioproject_accession (unitless) ?          "PRJNA706753"    "PRJNA706753"
 biosample_accession (unitless) ?          "SAMN18143076"    "SAMN18143275"
 library_ID (unitless) ?          "596_s001"    "596_s329"
 library_strategy (unitless) ?          "AMPLICON"    "AMPLICON"
 library_source (unitless) ?          "METAGENOMIC"    "METAGENOMIC"
 library_selection (unitless) ?          "PCR"    "PCR"
 library_layout (unitless) ?          "paired"    "paired"
 platform (unitless) ?          "ILLUMINA"    "ILLUMINA"
 instrument_model (unitless) ?          "Illumina MiSeq"    "Illumina MiSeq"
 design_description (unitless) ?          "16S rRNA gene ampl..."    "16S rRNA gene ampl..."
 filetype (unitless) ?          "fastq"    "fastq"
 filename (unitless) ?          "lane1-s001-index-C..."    "lane1-s329-index-C..."
 filename2 (unitless) ?          "lane1-s001-index-C..."    "lane1-s329-index-C..."
 
Server-side Functions ?
 distinct() ?
? ("Hover here to see a list of options. Click on an option to select it.Hover here to see a list of options. Click on an option to select it.Hover here to see a list of options. Click on an option to select it.Hover here to see a list of options. Click on an option to select it.Hover here to see a list of options. Click on an option to select it.")

File type: (more information)

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(Please be patient. It may take a while to get the data.)


 

The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  Sample_ID {
    String long_name "Sample_id";
    String units "unitless";
  }
  collection_date {
    String long_name "Collection_date";
    String units "unitless";
  }
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    Int32 actual_range 2, 2;
    String axis "Z";
    String ioos_category "Location";
    String long_name "Depth";
    String positive "down";
    String standard_name "depth";
    String units "m";
  }
  env_broad_scale {
    String long_name "Env_broad_scale";
    String units "unitless";
  }
  env_local_scale {
    String long_name "Env_local_scale";
    String units "unitless";
  }
  env_medium {
    String long_name "Env_medium";
    String units "unitless";
  }
  geo_loc_name {
    String long_name "Geo_loc_name";
    String units "unitless";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float32 actual_range 21.43635, 21.526;
    String axis "Y";
    String ioos_category "Location";
    String long_name "Latitude";
    String standard_name "latitude";
    String units "degrees_north";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float32 actual_range -157.8358, -157.7663;
    String axis "X";
    String ioos_category "Location";
    String long_name "Longitude";
    String standard_name "longitude";
    String units "degrees_east";
  }
  Site_name {
    String long_name "Site_name";
    String units "unitless";
  }
  chlorophyll_a_ug_per_L {
    Float32 actual_range 0.22, 2.74;
    String long_name "Chlorophyll_a_ug_per_l";
    String units "micrograms per Liter";
  }
  ph {
    Float32 actual_range 7.45, 8.64;
    String long_name "Ph";
    String units "no unit";
  }
  salinity {
    Float32 actual_range 31.81, 36.97;
    String long_name "Salinity";
    String units "ppt";
  }
  Seawater_temperature {
    Float32 actual_range 23.07, 28.99;
    String long_name "Seawater_temperature";
    String units "degrees Celsius  (°C)";
  }
  Prochlorococcus_cells_per_mL {
    Int32 actual_range 0, 113833;
    String long_name "Prochlorococcus_cells_per_ml";
    String units "cells per mL";
  }
  Synechococcus_cells_per_mL {
    Int32 actual_range 2074, 517913;
    String long_name "Synechococcus_cells_per_ml";
    String units "cells per mL";
  }
  Heterotrophic_bacteria_cells_per_mL {
    Int32 actual_range 348075, 2667000;
    String long_name "Heterotrophic_bacteria_cells_per_ml";
    String units "cells per mL";
  }
  Eukaryotic_picophytoplankton_cells_per_mL {
    Int32 actual_range 1549, 117338;
    String long_name "Eukaryotic_picophytoplankton_cells_per_ml";
    String units "cells per mL";
  }
  Universal_Sample_ID {
    String long_name "Universal_sample_id";
    String units "unitless";
  }
  SRA_accession {
    String long_name "Sra_accession";
    String units "unitless";
  }
  study {
    String long_name "Study";
    String units "unitless";
  }
  bioproject_accession {
    String long_name "Bioproject_accession";
    String units "unitless";
  }
  biosample_accession {
    String long_name "Biosample_accession";
    String units "unitless";
  }
  library_ID {
    String long_name "Library_id";
    String units "unitless";
  }
  library_strategy {
    String long_name "Library_strategy";
    String units "unitless";
  }
  library_source {
    String long_name "Library_source";
    String units "unitless";
  }
  library_selection {
    String long_name "Library_selection";
    String units "unitless";
  }
  library_layout {
    String long_name "Library_layout";
    String units "unitless";
  }
  platform {
    String long_name "Platform";
    String units "unitless";
  }
  instrument_model {
    String long_name "Instrument_model";
    String units "unitless";
  }
  design_description {
    String long_name "Design_description";
    String units "unitless";
  }
  filetype {
    String long_name "Filetype";
    String units "unitless";
  }
  filename {
    String long_name "Filename";
    String units "unitless";
  }
  filename2 {
    String long_name "Filename2";
    String units "unitless";
  }
 }
  NC_GLOBAL {
    String cdm_data_type "Other";
    String Conventions "COARDS, CF-1.6, ACDD-1.3";
    String creator_email "info@bco-dmo.org";
    String creator_name "BCO-DMO";
    String creator_url "https://www.bco-dmo.org/";
    String doi "10.26008/1912/bco-dmo.930084.1";
    Float64 Easternmost_Easting -157.7663;
    Float64 geospatial_lat_max 21.526;
    Float64 geospatial_lat_min 21.43635;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -157.7663;
    Float64 geospatial_lon_min -157.8358;
    String geospatial_lon_units "degrees_east";
    Float64 geospatial_vertical_max 2.0;
    Float64 geospatial_vertical_min 2.0;
    String geospatial_vertical_positive "down";
    String geospatial_vertical_units "m";
    String history 
"2024-10-12T07:22:16Z (local files)
2024-10-12T07:22:16Z https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_930084_v1.html";
    String infoUrl "https://www.bco-dmo.org/dataset/930084";
    String institution "BCO-DMO";
    String license 
"The data may be used and redistributed for free but is not intended
for legal use, since it may contain inaccuracies. Neither the data
Contributor, ERD, NOAA, nor the United States Government, nor any
of their employees or contractors, makes any warranty, express or
implied, including warranties of merchantability and fitness for a
particular purpose, or assumes any legal liability for the accuracy,
completeness, or usefulness, of this information.";
    Float64 Northernmost_Northing 21.526;
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 21.43635;
    String summary 
"These data include temperature, pH, salinity, chlorophyll a concentrations, cellular abundances of Prochlorococcus, Synechococcus, photosynthetic picoeukaryotes, and heterotrophic bacteria, and 16S ribosomal RNA gene amplicon libraries from 200 surface seawater samples collected as part of the Kāneʻohe Bay Time-series (KByT). Near-monthly sampling of surface seawater was conducted between August 2017 to June 2019 at 10 sites within coastal waters of Kāneʻohe Bay, Oʻahu, Hawaiʻi and in the adjacent offshore. Instruments used were a YSI 6,600 sonde, a Turner 10AU fluorometer, an EPICS ALTRA flow cytometer, and an Illumina MiSeq v2 platform.

These data characterize the partitioning of microbial communities across sharp physiochemical gradients in surface seawaters connecting nearshore and offshore waters in the tropical Pacific. This study provides evidence for the ecological differentiation of SAR11 marine bacteria across nearshore to offshore waters in the tropical Pacific and further increases our understanding of how SAR11 genetic diversity partitions into distinct ecological units. Data were collected by Sarah J. Tucker, Kelle C. Freel, Elizabeth A. Monaghan, Clarisse E. S. Sullivan, Oscar Ramfelt, Yoshimi M. Rii, and Michael S. Rappé.";
    String title "[Kāneʻohe Bay Time-series - microbial community] - Flow cytometry, 16S rRNA gene amplicons, chlorophyll a, and surface seawater measurements  taken between August 2017 to June 2019 Kāneʻohe Bay, Oʻahu, Hawaiʻi (Population genomics and ecotypic divergence in the most dominant lineage of marine bacteria)";
    Float64 Westernmost_Easting -157.8358;
  }
}

 

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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