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Dataset Title:  [DOM remineralization bioassays] - Bacterial abundance, bacterial organic
carbon, and total organic carbon from remineralization bioassays conducted on R/
V Robert Gordon Sproul cruises along the Southern California coast during July
and August 2023 (Postdoctoral Fellowship: OCE-PRF: Smoke on the water: the
impacts of wildfire ash deposition on surface ocean biology)
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_953702_v1)
Information:  Summary ? | License ? | FGDC | ISO 19115 | Metadata | Background (external link) | Files | Make a graph
 
Variable ?   Optional
Constraint #1 ?
Optional
Constraint #2 ?
   Minimum ?
 
   Maximum ?
 
 stn (unitless) ?          4    16
 latitude (degrees_north) ?          33.54503    34.37358
  < slider >
 longitude (degrees_east) ?          -120.7948    -118.402
  < slider >
 time (Dt, UTC) ?          2023-08-02T15:35:00Z    2023-08-22T16:00:00Z
  < slider >
 trt (unitless) ?          "Control"    "Thomas Fire Ash"
 bact_cells (cells per milliliter) ?          91784    1084210
 sd_bact_cells (cells per milliliter) ?          1607    330253
 boc (micromoles C per liter (umol C/L)) ?          0.01    3.85
 mean_toc (micromoles C per liter (umol C/L)) ?          64.2    76.4
 sd_toc (micromoles C per liter (umol C/L)) ?          0.1    2.4
 
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)

(Documentation / Bypass this form ? )
 
(Please be patient. It may take a while to get the data.)


 

The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  stn {
    Int32 actual_range 4, 16;
    String long_name "Stn";
    String units "unitless";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float32 actual_range 33.54503, 34.37358;
    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 -120.7948, -118.402;
    String axis "X";
    String ioos_category "Location";
    String long_name "Longitude";
    String standard_name "longitude";
    String units "degrees_east";
  }
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 1.6909905e+9, 1.69272e+9;
    String axis "T";
    String ioos_category "Time";
    String long_name "Dt";
    String standard_name "time";
    String time_origin "01-JAN-1970 00:00:00";
    String units "seconds since 1970-01-01T00:00:00Z";
  }
  trt {
    String long_name "Trt";
    String units "unitless";
  }
  bact_cells {
    Int32 actual_range 91784, 1084210;
    String long_name "Bact_cells";
    String units "cells per milliliter";
  }
  sd_bact_cells {
    Int32 actual_range 1607, 330253;
    String long_name "Sd_bact_cells";
    String units "cells per milliliter";
  }
  boc {
    Float32 actual_range 0.01, 3.85;
    String long_name "Boc";
    String units "micromoles C per liter (umol C/L)";
  }
  mean_toc {
    Float32 actual_range 64.2, 76.4;
    String long_name "Mean_toc";
    String units "micromoles C per liter (umol C/L)";
  }
  sd_toc {
    Float32 actual_range 0.1, 2.4;
    String long_name "Sd_toc";
    String units "micromoles C per liter (umol C/L)";
  }
 }
  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 defaultDataQuery "&amp;time&lt;now";
    String doi "10.26008/1912/bco-dmo.953702.1";
    Float64 Easternmost_Easting -118.402;
    Float64 geospatial_lat_max 34.37358;
    Float64 geospatial_lat_min 33.54503;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -118.402;
    Float64 geospatial_lon_min -120.7948;
    String geospatial_lon_units "degrees_east";
    String history 
"2025-04-02T00:18:39Z (local files)
2025-04-02T00:18:39Z https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_953702_v1.html";
    String infoUrl "https://www.bco-dmo.org/dataset/953702";
    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 34.37358;
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 33.54503;
    String summary 
"These data include bacterial abundance, bacterial organic carbon, and total organic carbon from remineralization bioassays conducted to assess bacterioplankton growth and DOC degradation. Experiments were conducted on cruises aboard the R/V Robert Gordon Sproul (SP2319, SP2320) between dates 2023-07-28 and 2023-08-19 along the Southern California coast. 

Deposition of wildfire ash on the ocean can fertilize microbial production but also has the potential to inhibit microbial growth due to heavy metal toxicity. The data collected from these field experiments can contribute to elevating understanding of wildfire-driven material transfer from the terrestrial system to the ocean and its impact on carbon and energy flow in marine food webs. These data were collected by Dr. Nicholas Baetge,  Dr. Allen Milligan, Brian Ver Wey, and Parker Hansen of Oregon State University. Data were also collected by Dr. Craig Carlson, Elisa Halewood, and Keri Opalk of the University of California Santa Barbara";
    String time_coverage_end "2023-08-22T16:00:00Z";
    String time_coverage_start "2023-08-02T15:35:00Z";
    String title "[DOM remineralization bioassays] - Bacterial abundance, bacterial organic carbon, and total organic carbon from remineralization bioassays conducted on R/V Robert Gordon Sproul cruises along the Southern California coast during July and August 2023 (Postdoctoral Fellowship: OCE-PRF: Smoke on the water: the impacts of wildfire ash deposition on surface ocean biology)";
    Float64 Westernmost_Easting -120.7948;
  }
}

 

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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