BCO-DMO ERDDAP
Accessing BCO-DMO data

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Dataset Title:	[Shallow USVI fate tracking data] - Fate data for corals sampled at the U.S. Virgin Islands from April 2022 to April 2023 (A multi-scale approach to predicting infectious multi-host disease spread in marine benthic communities)
Institution:	BCO-DMO (Dataset ID: bcodmo_dataset_986534_v1)
Range:	longitude = -64.8148 to -64.607°E, latitude = 17.77335 to 18.34465°N
Information:	Summary \| License \| FGDC \| ISO 19115 \| 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 {
  Date_Sampling {
    String long_name "Date_sampling";
    String units "unitless";
  }
  Site {
    String long_name "Site";
    String units "unitless";
  }
  Species {
    String long_name "Species";
    String units "unitless";
  }
  Tag {
    String long_name "Tag";
    String units "unitless";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float32 actual_range 17.77335, 18.34465;
    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 -64.8148, -64.607;
    String axis "X";
    String ioos_category "Location";
    String long_name "Longitude";
    String standard_name "longitude";
    String units "degrees_east";
  }
  SamplingHealthState {
    String long_name "Samplinghealthstate";
    String units "unitless";
  }
  Date_SixMonths {
    String long_name "Date_sixmonths";
    String units "unitless";
  }
  HealthState_SixMonths {
    String long_name "Healthstate_sixmonths";
    String units "unitless";
  }
  Length_SixMonths {
    Int32 actual_range 6, 180;
    String long_name "Length_sixmonths";
    String units "centimeters (cm)";
  }
  Width_SixMonths {
    Int32 actual_range 4, 175;
    String long_name "Width_sixmonths";
    String units "centimeters (cm)";
  }
  Height_SixMonths {
    Int32 actual_range 1, 130;
    String long_name "Height_sixmonths";
    String units "centimeters (cm)";
  }
  Pcnt_Old_SixMonths {
    Int32 actual_range 0, 100;
    String long_name "Pcnt_old_sixmonths";
    String units "percent (%)";
  }
  Pcnt_Rec_SixMonths {
    Int32 actual_range 0, 50;
    String long_name "Pcnt_rec_sixmonths";
    String units "percent (%)";
  }
  Pcnt_Bl_SixMonths {
    Int32 actual_range 0, 100;
    String long_name "Pcnt_bl_sixmonths";
    String units "percent (%)";
  }
  Pcnt_Pale_SixMonths {
    Int32 actual_range 0, 50;
    String long_name "Pcnt_pale_sixmonths";
    String units "percent (%)";
  }
  Date_OneYear {
    String long_name "Date_oneyear";
    String units "unitless";
  }
  HealthState_OneYear {
    String long_name "Healthstate_oneyear";
    String units "unitless";
  }
  Length_OneYear {
    Int32 actual_range 8, 250;
    String long_name "Length_oneyear";
    String units "centimeters (cm)";
  }
  Width_OneYear {
    Int32 actual_range 6, 210;
    String long_name "Width_oneyear";
    String units "centimeters (cm)";
  }
  Height_OneYear {
    Int32 actual_range 1, 120;
    String long_name "Height_oneyear";
    String units "centimeters (cm)";
  }
  Pcnt_Old_OneYear {
    Int32 actual_range 0, 100;
    String long_name "Pcnt_old_oneyear";
    String units "percent (%)";
  }
  Pcnt_Rec_OneYear {
    Int32 actual_range 0, 10;
    String long_name "Pcnt_rec_oneyear";
    String units "percent (%)";
  }
  Pcnt_Bl_OneYear {
    Int32 actual_range 0, 20;
    String long_name "Pcnt_bl_oneyear";
    String units "percent (%)";
  }
  Pcnt_Pale_OneYear {
    Int32 actual_range 0, 10;
    String long_name "Pcnt_pale_oneyear";
    String units "percent (%)";
  }
 }
  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.986534.1";
    Float64 Easternmost_Easting -64.607;
    Float64 geospatial_lat_max 18.34465;
    Float64 geospatial_lat_min 17.77335;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -64.607;
    Float64 geospatial_lon_min -64.8148;
    String geospatial_lon_units "degrees_east";
    String history 
"2026-04-05T18:14:05Z (local files)
2026-04-05T18:14:05Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_986534_v1.das";
    String infoUrl "https://osprey.bco-dmo.org/dataset/986534";
    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 18.34465;
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 17.77335;
    String summary "These data summarize the fates of sampled corals from a stony coral tissue loss disease (SCTLD) outbreak in the U.S. Virgin Islands (USVI). In January of 2019, a coral disease outbreak consistent with the gross morphology case description for Stony Coral Tissue Loss Disease (SCTLD) was observed off the south shore of St. Thomas, USVI. Approximately one year later, the disease was observed on the western reefs of St. John, and approximately 1.5 years later, the disease was observed off the south shore of St. Croix. Our interdisciplinary research team of ecologists, connectivity and disease modelers, microbiologists, and coral immunologists are using colony fate-tracking, molecular and microscopy approaches, as well as modeling of disease reservoirs and dispersal to better understand characteristics of this outbreak. A sampling mission occurred March 28 to April 15, 2022 to mark and collect samples from diseased and healthy corals at four sites: Coral Bay and South Haulover in St. John and Cane Bay and Buck Island in St. Croix. 233 stony coral colonies were tagged for sampling and tagging consisted of hammering a uniquely numbered cattle tag into adjacent dead substrate with a masonry nail. Samples were taken from all tagged corals, which included colonies of the species Acropora cervicornis, Agaricia agaricites, Colpophyllia natans, Diploria labyrinthifornis, Montastraea cavernosa, Orbicella annularis, Porites astreoides. Monitoring surveys were conducted approximately 6 months and 1 year post-sampling when sampled corals were relocated and their current health status was recorded. This dataset includes the health status of each coral at the time of sampling in March/April 2022, and its health characteristics in the Fall of 2022 and Spring of 2023 if it was found.";
    String title "[Shallow USVI fate tracking data] - Fate data for corals sampled at the U.S. Virgin Islands from April 2022 to April 2023 (A multi-scale approach to predicting infectious multi-host disease spread in marine benthic communities)";
    Float64 Westernmost_Easting -64.8148;
  }
}

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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