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Dataset Title:	[Abalone Recruitment Modules] - Abalone recruitment data from Baja California and Baja California Sur, Mexico in 2019 (Collaborative Research: Evaluating how abalone populations in the California Current are structured by the interplay of large-scale oceanographic forcing and nearshore variability)
Institution:	BCO-DMO   (Dataset ID: bcodmo_dataset_907383_v1)
Range:	longitude = -115.799 to -113.7003°E
Information:	Summary | License | Metadata | Background | Data Access Form | Files

 

Graph Type:  lines linesAndMarkers markers sticks X Axis:  number depth_f lat longitude individual_num Y Axis:  number depth_f lat longitude individual_num Color:  number depth_f lat longitude individual_num   Constraints Optional Constraint #1 Optional Constraint #2 date Site Bouy divers BART_transect number depth_f camera lat longitude Organism_Identification Taxonomic_name Species_note individual_num size_mm size_mm_note     != =~ <= >= = < >     != =~ <= >= = < > date Site Bouy divers BART_transect number depth_f camera lat longitude Organism_Identification Taxonomic_name Species_note individual_num size_mm size_mm_note     != =~ <= >= = < >     != =~ <= >= = < > date Site Bouy divers BART_transect number depth_f camera lat longitude Organism_Identification Taxonomic_name Species_note individual_num size_mm size_mm_note     != =~ <= >= = < >     != =~ <= >= = < > date Site Bouy divers BART_transect number depth_f camera lat longitude Organism_Identification Taxonomic_name Species_note individual_num size_mm size_mm_note     != =~ <= >= = < >     != =~ <= >= = < > date Site Bouy divers BART_transect number depth_f camera lat longitude Organism_Identification Taxonomic_name Species_note individual_num size_mm size_mm_note     != =~ <= >= = < >     != =~ <= >= = < >   Server-side Functions  distinct() orderBy orderByDescending orderByClosest orderByCount orderByLimit orderByMax orderByMin orderByMinMax orderByMean orderBySum (" date Site Bouy divers BART_transect number depth_f camera lat longitude Organism_Identification Taxonomic_name Species_note individual_num size_mm size_mm_note date Site Bouy divers BART_transect number depth_f camera lat longitude Organism_Identification Taxonomic_name Species_note individual_num size_mm size_mm_note date Site Bouy divers BART_transect number depth_f camera lat longitude Organism_Identification Taxonomic_name Species_note individual_num size_mm size_mm_note date Site Bouy divers BART_transect number depth_f camera lat longitude Organism_Identification Taxonomic_name Species_note individual_num size_mm size_mm_note ")   Graph Settings Marker Type:  None Plus X Dot Square Filled Square Circle Filled Circle Up Triangle Filled Up Triangle Borderless Filled Square Borderless Filled Circle Borderless Filled Up Triangle  Size:  3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 Color:  Color Bar:  BlackBlueWhite BlackGreenWhite BlackRedWhite BlackWhite BlueWhiteRed BlueWideWhiteRed LightRainbow Ocean OceanDepth Rainbow Rainbow2 Rainfall ReverseRainbow RedWhiteBlue RedWhiteBlue2 RedWideWhiteBlue Spectrum Topography TopographyDepth WhiteBlueBlack WhiteGreenBlack WhiteRedBlack WhiteBlack YellowRed KT_algae KT_amp KT_balance KT_curl KT_deep KT_delta KT_dense KT_gray KT_haline KT_ice KT_matter KT_oxy KT_phase KT_solar KT_speed KT_tempo KT_thermal KT_turbid  Continuity:  Continuous Discrete  Scale:  Linear Log    Minimum:   Maximum:   N Sections:  2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 Y Axis Minimum:   Maximum:    Ascending Descending Linear Log   Redraw the Graph (Please be patient. It may take a while to get the data.)   Optional: Then set the File Type: .asc .csv .csvp .csv0 .dataTable .das .dds .dods .esriCsv .fgdc .geoJson .graph .help .html .htmlTable .iso19115 .itx .json .jsonlCSV1 .jsonlCSV .jsonlKVP .mat .nc .ncHeader .ncCF .ncCFHeader .ncCFMA .ncCFMAHeader .nccsv .nccsvMetadata .ncoJson .odvTxt .subset .tsv .tsvp .tsv0 .wav .xhtml .kml .smallPdf .pdf .largePdf .smallPng .png .largePng .transparentPng (File Type information) and or view the URL: (Documentation / Bypass this form )

 

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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.
   

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The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  date {
    String long_name "Date";
    String units "unitless";
  }
  Site {
    String long_name "Site";
    String units "unitless";
  }
  Bouy {
    String long_name "Bouy";
    String units "unitless";
  }
  divers {
    String long_name "Divers";
    String units "unitless";
  }
  BART_transect {
    String long_name "Bart_transect";
    String units "unitless";
  }
  number {
    Int32 actual_range 1, 7;
    String long_name "Number";
    String units "unitless";
  }
  depth_f {
    Int32 actual_range 5, 41;
    String long_name "Depth";
    String units "feet (ft)";
  }
  camera {
    String long_name "Camera";
    String units "unitless";
  }
  lat {
    Float32 actual_range 26.77558, 29.79086;
    String long_name "Lat";
    String units "degrees_north";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float32 actual_range -115.799, -113.7003;
    String axis "X";
    String ioos_category "Location";
    String long_name "Long";
    String standard_name "longitude";
    String units "degrees_east";
  }
  Organism_Identification {
    String long_name "Organism_identification";
    String units "unitless";
  }
  Taxonomic_name {
    String long_name "Taxonomic_name";
    String units "unitless";
  }
  Species_note {
    String long_name "Species_note";
    String units "unitless";
  }
  individual_num {
    Int32 actual_range 1, 35;
    String long_name "Individual_num";
    String units "unitless";
  }
  size_mm {
    String long_name "Size_mm";
    String units "millimeters (mm)";
  }
  size_mm_note {
    String long_name "Size_mm_note";
    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.907383.1";
    Float64 Easternmost_Easting -113.7003;
    Float64 geospatial_lon_max -113.7003;
    Float64 geospatial_lon_min -115.799;
    String geospatial_lon_units "degrees_east";
    String history 
"2024-11-08T06:06:49Z (local files)
2024-11-08T06:06:49Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_907383_v1.das";
    String infoUrl "https://www.bco-dmo.org/dataset/907383";
    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 "Abalone support commercial and recreational fishery, however their population have decline dramatically since 1950's. To understand the recruitment of abalone populations, standarized abalone recruitment modules made of half cinder blocks inside cages were deployed in Baja California and Baja California Sur, Mexico. 12 cages were deployed at three sites (i.e., El Rosario, Isla Natividad and La Bocana) in Mexico. The abundances of abalone and invertebrates found in the cages were checked after 12months. This dataset presents all the information collected from the cages deployed at three sites (El Rosario, Isla Natividad and La Bocana) in Baja California and Baja California Sur, Mexico.";
    String title "[Abalone Recruitment Modules] - Abalone recruitment data from Baja California and Baja California Sur, Mexico in 2019 (Collaborative Research: Evaluating how abalone populations in the California Current are structured by the interplay of large-scale oceanographic forcing and nearshore variability)";
    Float64 Westernmost_Easting -115.799;
  }
}

 

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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 Data Access Protocol (DAP) and its selection constraints.

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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