ERDDAP > tabledap > Data Access Form

Dataset Title:	[Bacterial communities and relative abundances of the pathogen Vibrio coralliilyticus in feces of coral reef fish] - Bacterial communities and relative abundances of the pathogen Vibrio coralliilyticus in feces of coral reef fish collected on the north shore of Mo’orea, French Polynesia, Oct 2020 (CAREER: Testing the effects of predator-derived feces on host symbiont acquisition and health)
Institution:	BCO-DMO   (Dataset ID: bcodmo_dataset_935908_v1)
Information:	Summary | License | Metadata | Background | Files

 

Variable	Optional Constraint #1		Optional Constraint #2		Minimum	Maximum
sample_name (unitless)	!= =~ <= >= = < >		!= =~ <= >= = < >		"20ACRAF"	"Mock5"
SRA (unitless)	!= =~ <= >= = < >		!= =~ <= >= = < >		"SRS16785882"	"SRS16786069"
BioSample (unitless)	!= =~ <= >= = < >		!= =~ <= >= = < >		"SAMN33295601"	"SAMN33295788"
organism (unitless)	!= =~ <= >= = < >		!= =~ <= >= = < >		"Bacteria"	"Bacteria"
strain (unitless)	!= =~ <= >= = < >		!= =~ <= >= = < >		"Mixed community"	"Mock community"
isolation_source (unitless)	!= =~ <= >= = < >		!= =~ <= >= = < >		"Coral reef"	"not applicable"
collection_date (unitless)	!= =~ <= >= = < >		!= =~ <= >= = < >		"2020-10"	"2020-10"
geo_loc_name (unitless)	!= =~ <= >= = < >		!= =~ <= >= = < >		"French Polynesia: ..."	"French Polynesia: ..."
depth_r (Depth, m)	!= =~ <= >= = < >		!= =~ <= >= = < >		"0-10 m"	"0-10 m"
env_broad_scale (unitless)	!= =~ <= >= = < >		!= =~ <= >= = < >		"Coral reef biome"	"Coral reef biome"
host_description (unitless)	!= =~ <= >= = < >		!= =~ <= >= = < >		"Acropora hyacinthus"	"Zebrasoma scopas"
host_tissue_sampled (unitless)	!= =~ <= >= = < >		!= =~ <= >= = < >		"Algal tissue"	"not applicable"
host_diet (unitless)	!= =~ <= >= = < >		!= =~ <= >= = < >		"Facultative corall..."	"Obligate corallivore"
host_feces_dCT (cycles)	!= =~ <= >= = < >		!= =~ <= >= = < >		8.23	20.507
host_AphiaID (unitless)	!= =~ <= >= = < >		!= =~ <= >= = < >		"143809"	"712772"
host_ScientificName (unitless)	!= =~ <= >= = < >		!= =~ <= >= = < >		"Acropora hyacinthus"	"Zebrasoma scopas"
host_LSID (unitless)	!= =~ <= >= = < >		!= =~ <= >= = < >		"urn:lsid:marinespe..."	"urn:lsid:marinespe..."

 

Server-side Functions

distinct()

orderBy orderByDescending orderByClosest orderByCount orderByLimit orderByMax orderByMin orderByMinMax orderByMean orderBySum (" sample_name SRA BioSample organism strain isolation_source collection_date geo_loc_name depth_r env_broad_scale host_description host_tissue_sampled host_diet host_feces_dCT host_AphiaID host_ScientificName host_LSID sample_name SRA BioSample organism strain isolation_source collection_date geo_loc_name depth_r env_broad_scale host_description host_tissue_sampled host_diet host_feces_dCT host_AphiaID host_ScientificName host_LSID sample_name SRA BioSample organism strain isolation_source collection_date geo_loc_name depth_r env_broad_scale host_description host_tissue_sampled host_diet host_feces_dCT host_AphiaID host_ScientificName host_LSID sample_name SRA BioSample organism strain isolation_source collection_date geo_loc_name depth_r env_broad_scale host_description host_tissue_sampled host_diet host_feces_dCT host_AphiaID host_ScientificName host_LSID sample_name SRA BioSample organism strain isolation_source collection_date geo_loc_name depth_r env_broad_scale host_description host_tissue_sampled host_diet host_feces_dCT host_AphiaID host_ScientificName host_LSID ")

File type: (more information) .asc - View OPeNDAP-style ISO-8859-1 comma-separated text. .csv - Download a ISO-8859-1 comma-separated text table (line 1: names; line 2: units; ISO 8601 times). .csvp - Download a ISO-8859-1 .csv file with line 1: name (units). Times are ISO 8601 strings. .csv0 - Download a ISO-8859-1 .csv file without column names or units. Times are ISO 8601 strings. .dataTable - A JSON file formatted for use with the Google Visualization client library (Google Charts). .das - View the dataset's metadata via an ISO-8859-1 OPeNDAP Dataset Attribute Structure (DAS). .dds - View the dataset's structure via an ISO-8859-1 OPeNDAP Dataset Descriptor Structure (DDS). .dods - OPeNDAP clients use this to download the data in the DODS binary format. .esriCsv - Download a ISO_8859_1 .csv file for ESRI's ArcGIS 9.x and below (separate date and time columns). .fgdc - View the dataset's UTF-8 FGDC .xml metadata. .geoJson - Download longitude,latitude,otherColumns data as a UTF-8 GeoJSON .json file. .graph - View a Make A Graph web page. .help - View a web page with a description of tabledap. .html - View an OPeNDAP-style HTML Data Access Form. .htmlTable - View a UTF-8 .html web page with the data in a table. Times are ISO 8601 strings. .iso19115 - View the dataset's ISO 19115-2/19139 UTF-8 .xml metadata. .itx - Download an ISO-8859-1 Igor Text File. Each response column becomes a wave. .json - View a table-like UTF-8 JSON file (missing value = 'null'; times are ISO 8601 strings). .jsonlCSV1 - View a UTF-8 JSON Lines CSV file with column names on line 1 (mv = 'null'; times are ISO 8601 strings). .jsonlCSV - View a UTF-8 JSON Lines CSV file without column names (mv = 'null'; times are ISO 8601 strings). .jsonlKVP - View a UTF-8 JSON Lines file with Key:Value pairs (missing value = 'null'; times are ISO 8601 strings). .mat - Download a MATLAB binary file. .nc - Download a flat, table-like, NetCDF-3 binary file with COARDS/CF/ACDD metadata. .ncHeader - View the UTF-8 header (the metadata) for the NetCDF-3 .nc file. .ncCF - Download a NetCDF-3 CF Discrete Sampling Geometries file (Contiguous Ragged Array). .ncCFHeader - View the UTF-8 header (the metadata) for the .ncCF file. .ncCFMA - Download a NetCDF-3 CF Discrete Sampling Geometries file (Multidimensional Array). .ncCFMAHeader - View the UTF-8 header (the metadata) for the .ncCFMA file. .nccsv - Download a NetCDF-3-like 7-bit ASCII NCCSV .csv file with COARDS/CF/ACDD metadata. .nccsvMetadata - View the dataset's metadata as the top half of a 7-bit ASCII NCCSV .csv file. .ncoJson - Download a UTF-8 NCO lvl=2 JSON file with COARDS/CF/ACDD metadata. .odvTxt - Download longitude,latitude,time,otherColumns as an ISO-8859-1 ODV Generic Spreadsheet File (.txt). .subset - View an HTML form which uses faceted search to simplify picking subsets of the data. .tsv - Download a ISO-8859-1 tab-separated text table (line 1: names; line 2: units; ISO 8601 times). .tsvp - Download a ISO-8859-1 .tsv file with line 1: name (units). Times are ISO 8601 strings. .tsv0 - Download a ISO-8859-1 .tsv file without column names or units. Times are ISO 8601 strings. .wav - Download a .wav audio file. All columns must be numeric and of the same type. .xhtml - View a UTF-8 XHTML (XML) file with the data in a table. Times are ISO 8601 strings. .kml - View a .kml file, suitable for Google Earth. .smallPdf - View a small .pdf image file with a graph or map. .pdf - View a standard, medium-sized .pdf image file with a graph or map. .largePdf - View a large .pdf image file with a graph or map. .smallPng - View a small .png image file with a graph or map. .png - View a standard, medium-sized .png image file with a graph or map. .largePng - View a large .png image file with a graph or map. .transparentPng - View a .png image file (just the data, without axes, landmask, or legend).

(Documentation / Bypass this form )
 
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The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  sample_name {
    String long_name "Sample_name";
    String units "unitless";
  }
  SRA {
    String long_name "Sra";
    String units "unitless";
  }
  BioSample {
    String long_name "Biosample";
    String units "unitless";
  }
  organism {
    String long_name "Organism";
    String units "unitless";
  }
  strain {
    String long_name "Strain";
    String units "unitless";
  }
  isolation_source {
    String long_name "Isolation_source";
    String units "unitless";
  }
  collection_date {
    String long_name "Collection_date";
    String units "unitless";
  }
  geo_loc_name {
    String long_name "Geo_loc_name";
    String units "unitless";
  }
  depth_r {
    String long_name "Depth";
    String units "m";
  }
  env_broad_scale {
    String long_name "Env_broad_scale";
    String units "unitless";
  }
  host_description {
    String long_name "Host_description";
    String units "unitless";
  }
  host_tissue_sampled {
    String long_name "Host_tissue_sampled";
    String units "unitless";
  }
  host_diet {
    String long_name "Host_diet";
    String units "unitless";
  }
  host_feces_dCT {
    Float32 actual_range 8.23, 20.507;
    String long_name "Host_feces_dct";
    String units "cycles";
  }
  host_AphiaID {
    String long_name "Host_aphiaid";
    String units "unitless";
  }
  host_ScientificName {
    String long_name "Host_scientificname";
    String units "unitless";
  }
  host_LSID {
    String long_name "Host_lsid";
    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.935908.1";
    String history 
"2024-12-21T07:07:35Z (local files)
2024-12-21T07:07:35Z https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_935908_v1.html";
    String infoUrl "https://www.bco-dmo.org/dataset/935908";
    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 "Understanding how microbial communities in consumer feces may impact ecosystem health may improve conservation and restoration efforts. To test how microbial communities in fish feces may affect coral reef health, we collected fecal samples from ten fish species, ranging from obligate corallivore to grazer/detritivore. Additionally, samples of corals, algae, sediments, and seawater were collected to test whether bacterial taxa in these samples were also represented in fish feces (N = 5-14 per fish, coral, or algae species/genus). All collections were conducted in October 2020 from the back reef (1-2 m depth) and fore reef (5-10 m depth) in Moorea, between LTER sites 1 and 2 of the Moorea Coral Reef (MCR) Long Term Ecological Research (LTER) site. We conducted bacterial 16S rRNA gene metabarcoding on all samples and found that fecal communities of bacteria differed among fish guilds (obligate corallivores, facultative corallivores, grazer/detritivores). We also used real-time PCR to quantify abundances of Vibrio coralliilyticus, a known coral pathogen,  in all fecal samples. Samples were collected and processed, and data were analyzed, by the authors of Grupstra et al., 2023.";
    String title "[Bacterial communities and relative abundances of the pathogen Vibrio coralliilyticus in feces of coral reef fish] - Bacterial communities and relative abundances of the pathogen Vibrio coralliilyticus in feces of coral reef fish collected on the north shore of Mo’orea, French Polynesia, Oct 2020 (CAREER: Testing the effects of predator-derived feces on host symbiont acquisition and health)";
  }
}

 

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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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