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Dataset Title:	[Lobster Larvae Respirometry Data] - Oxygen consumption by lobster larvae at different temperatures using closed cell respirometry for lobster larvae from Gulf of Maine near Boothbay Maine from 2021 to 2023 (Lobster Thermal Thresholds project) (RUI: Collaborative Research: Linking physiological thermal thresholds to the distribution of lobster settlers and juveniles)
Institution:	BCO-DMO (Dataset ID: bcodmo_dataset_939782_v1)
Range:	time = 2021-06-14T21:30:00Z to 2023-07-18T10:39:00Z
Information:	Summary \| License \| Metadata \| Background \| 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:

Web page authors can embed a graph of the latest data in a web page using HTML <img> tags.
Anyone can use ERDDAPs Slide Sorter to build a personal web page that displays graphs with the latest data (or other images or HTML content), each in its own, draggable slide.

The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  Larva_ID {
    String long_name "Larva_id";
    String units "unitless";
  }
  Treatment_Temperature {
    Int32 actual_range 4, 32;
    String long_name "Treatment_temperature";
    String units "degrees C";
  }
  Diet {
    String long_name "Diet";
    String units "unitless";
  }
  Rearing_Temperature {
    String long_name "Rearing_temperature";
    String units "degrees C";
  }
  Developmental_Stage {
    Int32 actual_range 1, 5;
    String long_name "Developmental_stage";
    String units "unitless";
  }
  Individual_Larva_Number {
    String long_name "Individual_larva_number";
    String units "unitless";
  }
  Year {
    Int32 actual_range 2021, 2023;
    String long_name "Year";
    String units "unitless";
  }
  Hatch_or_Capture_Date {
    String long_name "Hatch_or_capture_date";
    String units "unitless";
  }
  Trial_Date {
    String long_name "Trial_date";
    String units "unitless";
  }
  Trial_Time_Local_EST {
    String long_name "Trial_time_local_est";
    String units "unitless";
  }
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 1.6237062e+9, 1.68967674e+9;
    String axis "T";
    String ioos_category "Time";
    String long_name "Trial_datetime_utc";
    String standard_name "time";
    String time_origin "01-JAN-1970 00:00:00";
    String units "seconds since 1970-01-01T00:00:00Z";
  }
  Treatment {
    Float32 actual_range 0.1, 2.0;
    String long_name "Treatment";
    String units "unitless";
  }
  O2_Slope {
    Float32 actual_range -256.623, 1.835;
    String long_name "O2_slope";
    String units "micromole per liter per hour (umol/l/h)";
  }
  Chamber_Number {
    Float32 actual_range 4.1, 40.4;
    String long_name "Chamber_number";
    String units "unitless";
  }
  Chamber_Volume {
    Float32 actual_range 0.00415, 0.04186;
    String long_name "Chamber_volume";
    String units "liters (l)";
  }
  Treatment_O2_Consumption {
    Float32 actual_range -0.076, 5.0461;
    String long_name "Treatment_o2_consumption";
    String units "micromole per hour (umol/h)";
  }
  Control_O2_Consumption {
    Float32 actual_range -0.0051, 1.1136;
    String long_name "Control_o2_consumption";
    String units "micromole per hour (umol/h)";
  }
  Control_Corrected {
    Float32 actual_range -0.1709, 4.2672;
    String long_name "Control_corrected";
    String units "micromole per larva per hour (umol/larva/h)";
  }
  Dry_Weights {
    Float32 actual_range 0.5, 33.2;
    String long_name "Dry_weights";
    String units "milligram (mg)";
  }
  O2_Consumption_Normalized {
    Float32 actual_range -0.03974, 0.49591;
    String long_name "O2_consumption_normalized";
    String units "micromole per milligram of larva per hour (umol/mg larva/hr";
  }
 }
  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.939782.1";
    String history 
"2025-05-18T11:34:24Z (local files)
2025-05-18T11:34:24Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_939782_v1.das";
    String infoUrl "https://osprey.bco-dmo.org/dataset/939782";
    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.";
    String sourceUrl "(local files)";
    String summary "We used the American lobster (Homarus americanus lsid:marinespecies.org:taxname:156134) in the Gulf of Maine as a model system to define thermal tolerance in larvae and establish mechanistic linkages between thermal tolerance of the individual larva and the patterns of settlement in the field.  We assessed and compared the thermal tolerances of larvae reared in the laboratory using conventional methods with larvae captured in the wild, and examined ontogenetic changes in thermal tolerance.  The upper and lower thermal thresholds larval stages I-IV and the first juvenile stage were defined in part by oxygen consumption and scope for activity (defined as the difference in oxygen consumption between larvae at rest and larvae swimming actively).  This data set includes the raw oxygen consumption data obtained through closed system microrespirometry and subsequently used to calculate scope for activity.  These data were collected between 2021-2023 at Bigelow Laboratory for Ocean Sciences, led by Eric Annis.";
    String time_coverage_end "2023-07-18T10:39:00Z";
    String time_coverage_start "2021-06-14T21:30:00Z";
    String title "[Lobster Larvae Respirometry Data] - Oxygen consumption by lobster larvae at different temperatures using closed cell respirometry for lobster larvae from Gulf of Maine near Boothbay Maine from 2021 to 2023 (Lobster Thermal Thresholds project) (RUI: Collaborative Research: Linking physiological thermal thresholds to the distribution of lobster settlers and juveniles)";
  }
}

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.

(easy) You can get data by using the dataset's Data Access Form or Subset form. They make the URL for you.
(easy) You can make a graph or map by using the dataset's Make A Graph form. It makes the URL for you.
(not hard) You can bypass the forms and get the data or make a graph or map by generating the URL by hand or with a computer program or script.

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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