BCO-DMO ERDDAP
Accessing BCO-DMO data

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Dataset Title:	[Caribbean sponges - nanoSIMS] - NanoSIMS data from sponges collected in Summerland Key in Florida between July 27 - August 19, 2021 (Collaborative Research: Investigations into microbially mediated ecological diversification in sponges)
Institution:	BCO-DMO (Dataset ID: bcodmo_dataset_954439_v1)
Range:	longitude = -81.40839 to -81.40839°E, latitude = 24.56382 to 24.56382°N
Information:	Summary \| License \| FGDC \| ISO 19115 \| Metadata \| Background \| Data Access Form \| Files

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Constraints	Optional Constraint #1		Optional Constraint #2

Server-side Functions

distinct()

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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 {
  Roi_name {
    String long_name "Roi_name";
    String units "unitless";
  }
  Roi_group {
    String long_name "Roi_group";
    String units "unitless";
  }
  area {
    Int32 actual_range 1, 10195;
    String long_name "Area";
    String units "pixels^2";
  }
  mean13C {
    Float32 actual_range 59.40882, 529.7137;
    String long_name "Mean13c";
    String units "ratio (x10000)";
  }
  stddev13C {
    Float32 actual_range 0.0, 151.231;
    String long_name "Stddev13c";
    String units "ratio (x10000)";
  }
  R_13C12C_12C2 {
    Float32 actual_range 0.005940882, 0.05297137;
    String long_name "R_13c12c_12c2";
    String units "ratio";
  }
  corr_R_13C_13C {
    Float32 actual_range 0.003118963, 0.02780997;
    String long_name "Corr_r_13c_13c";
    String units "ratio";
  }
  d_13C_12C {
    Float32 actual_range -722.4431, 1474.813;
    String long_name "D_13c_12c";
    String units "delta 13C in permille";
  }
  species {
    String long_name "Species";
    String units "unitless";
  }
  Collection_date {
    String long_name "Collection_date";
    String units "unitless";
  }
  time_sample {
    Float32 actual_range 0.5, 75.0;
    String long_name "Time";
    String units "unitless";
  }
  SEM_region {
    Float32 actual_range 1.0, 5.0;
    String long_name "Sem_region";
    String units "unitless";
  }
  mean15N {
    Float32 actual_range 8.396305, 151.2143;
    String long_name "Mean15n";
    String units "ratio (x10000)";
  }
  stddev15N {
    Float32 actual_range 0.0, 294.3397;
    String long_name "Stddev15n";
    String units "ratio (x10000)";
  }
  R_15N_14N {
    Float32 actual_range 8.3963e-4, 0.01512143;
    String long_name "R_15n_14n";
    String units "ratio";
  }
  corr_R_15N_14N {
    Float32 actual_range 8.3963e-4, 0.01512143;
    String long_name "Corr_r_15n_14n";
    String units "ratio";
  }
  d_15N_14N {
    Float32 actual_range -771.7277, 3111.096;
    String long_name "D_15n_14n";
    String units "delta 15N in permille";
  }
  experiment {
    String long_name "Experiment";
    String units "unitless";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float32 actual_range 24.56382, 24.56382;
    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 -81.40839, -81.40839;
    String axis "X";
    String ioos_category "Location";
    String long_name "Longitude";
    String standard_name "longitude";
    String units "degrees_east";
  }
 }
  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.954439.1";
    Float64 Easternmost_Easting -81.40839;
    Float64 geospatial_lat_max 24.56382;
    Float64 geospatial_lat_min 24.56382;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -81.40839;
    Float64 geospatial_lon_min -81.40839;
    String geospatial_lon_units "degrees_east";
    String history 
"2025-05-11T05:27:11Z (local files)
2025-05-11T05:27:11Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_954439_v1.das";
    String infoUrl "https://osprey.bco-dmo.org/dataset/954439";
    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 24.56382;
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 24.56382;
    String summary "Sponges represent one of the oldest extant animal phyla, and their associations with microbial symbionts have likely played a critical role in their success on oligotrophic coral reefs. For example, variation in the abundance, diversity, and community composition of microbiomes across host species may drive niche partitioning due to differential assimilation and recycling of nutrients across sponge species. With Nanoscale secondary ion mass spectrometry (NanoSIMS), we evaluated the respective roles of host and microbial symbiont cells in the uptake and recycling of three resource pools (dissolved organic matter: DOM, particulate organic matter: POM, and inorganic nutrients: NaHCO3 and NaNO3) over 72 hr. NanoSIMS analysis revealed enrichment of individual host and symbiont cells over time and highlighted the differing roles of host and symbiont cells in the uptake and recycling of diverse sources of carbon and nitrogen within two of these species. For instance, dissolved organic matter uptake was mediated by microbial symbionts in one species and by host cells in another species. Together , these results demonstrate that associations with microbial symbionts have facilitated niche partitioning by allowing host sponges to acquire and recycle diverse nutrient pools via unique mechanisms. Field and lab work for this research was carried out in the Florida Keys during June/August of 2021.";
    String title "[Caribbean sponges - nanoSIMS] - NanoSIMS data from sponges collected in Summerland Key in Florida between July 27 - August 19, 2021 (Collaborative Research: Investigations into microbially mediated ecological diversification in sponges)";
    Float64 Westernmost_Easting -81.40839;
  }
}

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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