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Dataset Title:  [Hawaiian sponge cryptofauna] - Specimen vouchers of sponges collected in a
study of hidden sponge biodiversity within the Hawaiian reef cryptofauna
conducted on Oahu, Hawaii from 2016 to 2018 (Testing the most striking tropical
marine biodiversity gradient on the planet: does it hold for sponges?) Subscribe RSS
Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_986892_v1)
Range: longitude = -157.894 to -157.6692°E, latitude = 21.3181 to 21.509°N
Information:  Summary ? | License ? | FGDC | ISO 19115 | Metadata | Background (external link) | 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:

The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  Species {
    String long_name "Species";
    String units "unitless";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float32 actual_range 21.3181, 21.509;
    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 -157.894, -157.6692;
    String axis "X";
    String ioos_category "Location";
    String long_name "Long";
    String standard_name "longitude";
    String units "degrees_east";
  }
  Station {
    String long_name "Station";
    String units "unitless";
  }
  Date {
    String long_name "Date";
    String units "unitless";
  }
  FMNH_voucher {
    String long_name "Fmnh_voucher";
    String units "unitless";
  }
  HIMB_voucher {
    String long_name "Himb_voucher";
    String units "unitless";
  }
  Field_ID {
    String long_name "Field_id";
    String units "unitless";
  }
  COI_accession {
    String long_name "Coi_accession";
    String units "unitless";
  }
  COI_base_pairs {
    String long_name "Coi_base_pairs";
    String units "unitless";
  }
  COI_blastn_result_1 {
    String long_name "Coi_blastn_result_1";
    String units "unitless";
  }
  COI_blastn_result_2 {
    String long_name "Coi_blastn_result_2";
    String units "% similarity";
  }
  rRNA_accession_28S {
    String long_name "Rrna_accession_28s";
    String units "unitless";
  }
  rRNA_base_pairs_28S {
    String long_name "Rrna_base_pairs_28s";
    String units "number of DNA nucleotides in the sequence";
  }
  rRNA_blastn_result_28S_1 {
    String long_name "Rrna_blastn_result_28s_1";
    String units "unitless";
  }
  rRNA_blastn_result_28S_2 {
    String long_name "Rrna_blastn_result_28s_2";
    String units "% similarity";
  }
 }
  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.986892.1";
    Float64 Easternmost_Easting -157.6692;
    Float64 geospatial_lat_max 21.509;
    Float64 geospatial_lat_min 21.3181;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -157.6692;
    Float64 geospatial_lon_min -157.894;
    String geospatial_lon_units "degrees_east";
    String history 
"2026-02-13T04:29:21Z (local files)
2026-02-13T04:29:21Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_986892_v1.das";
    String infoUrl "https://osprey.bco-dmo.org/dataset/986892";
    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 21.509;
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 21.3181;
    String summary "Sponges are abundant and conspicuous on the reef surface in productive, continental reefs, but largely vanish from surveys of the oligotrophic reefs of Oceania. However, their diversity in the cryptobiota remains poorly characterized. Here, we explore the contribution of cryptobenthic sponges to overall sponge diversity on 1,750 square meters of reef habitat in Kāne'ohe Bay and Waimanalo in the island of O'ahu, Hawai'i. We also assessed cryptic sponges using 15 square meters of Autonomous Reef Monitoring Structures (ARMS) deployed in this same area. We used integrative taxonomy combining morphology, COI and 28S barcoding to delineate and track species, most of which are poorly known or undescribed. We documented 186 OTUs, 150 of which are new records for the Hawaiian Islands, increasing the known sponge fauna of Kāne'ohe Bay by 3.5 fold, and that of the Hawaiian Islands by 2.5 fold. More than ¾ of the sponge OTUs were cryptobenthic. Reef sampling provided access to 31% (44 OTUs), whereas 52% (75 OTUs) were retrieved exclusively from ARMS. These results illustrate that the interstices of ARMS units provide suitable habitat for settlement of cryptobenthic sponges that would otherwise be impossible to access through traditional field surveys. Tracking species with provisional names, using integrative species delineation anchored to vouchers, images, and DNA barcodes provides a powerful approach for working with such a poorly understood fauna.";
    String title "[Hawaiian sponge cryptofauna] - Specimen vouchers of sponges collected in a study of hidden sponge biodiversity within the Hawaiian reef cryptofauna conducted on Oahu, Hawaii from 2016 to 2018 (Testing the most striking tropical marine biodiversity gradient on the planet: does it hold for sponges?)";
    Float64 Westernmost_Easting -157.894;
  }
}

 

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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