BCO-DMO ERDDAP
Accessing BCO-DMO data

Make A Graph

Dataset Title:	[Microbiome dynamics of coral reef and cleanerfish] - Microbiome dynamics of coral reef and cleanerfish from ecological surveys, in situ manipulations, and laboratory experiments conducted from 2020-2021 (Collaborative Research: Cleaning stations as hubs for the maintenance and recovery of microbial diversity on coral reefs.)
Institution:	BCO-DMO (Dataset ID: bcodmo_dataset_906740_v1)
Range:	longitude = -80.81375 to -64.8109°E
Information:	Summary \| License \| Metadata \| Background \| Data Access Form \| Files

To work correctly, this web page requires that JavaScript be enabled in your browser. Please:
1) Enable JavaScript in your browser:
      • Chrome: "Settings : Advanced : Privacy and security : Site Settings : JavaScript"
      • Firefox: (it should be always on!)"
      • Opera: "Settings : Websites : JavaScript"
      • Safari: "Safari : Preferences : Security : Enable JavaScript"
2) Reload this web page.

Graph Type:

X Axis:

Y Axis:

Color:

Constraints	Optional Constraint #1		Optional Constraint #2

Server-side Functions

distinct()

Hover here to see a list of options. Click on an option to select it.

Graph Settings

Marker Type:

Size:

Color:

Color Bar:

Continuity:

Scale:

Minimum:

Maximum:

N Sections:

Y Axis Minimum:

Maximum:

(Please be patient. It may take a while to get the data.)

Optional:
Then set the File Type: (File Type information)
and

or view the URL:
(Documentation / Bypass this form

)

[The graph you specified. Please be patient.]

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 {
  BioProject_accession {
    String long_name "Bioproject_accession";
    String units "unitless";
  }
  BioSample_accession {
    String long_name "Biosample_accession";
    String units "unitless";
  }
  sample_name {
    String long_name "Sample_name";
    String units "unitless";
  }
  SRA_accession {
    String long_name "Sra_accession";
    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";
  }
  host {
    String long_name "Host";
    String units "unitless";
  }
  lat {
    Float32 actual_range 17.7734, 24.82614;
    String long_name "Lat";
    String units "degrees_north";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float32 actual_range -80.81375, -64.8109;
    String axis "X";
    String ioos_category "Location";
    String long_name "Longitude";
    String standard_name "longitude";
    String units "degrees_east";
  }
  isolation_source {
    String long_name "Isolation_source";
    String units "unitless";
  }
  host_common_name {
    String long_name "Host_common_name";
    String units "unitless";
  }
  host_disease {
    String long_name "Host_disease";
    String units "unitless";
  }
  host_condition {
    String long_name "Host_condition";
    String units "unitless";
  }
  host_coral_cleaner_goby_pretreatment {
    String long_name "Host_coral_cleaner_goby_pretreatment";
    String units "unitless";
  }
  host_coral_reef_id {
    String long_name "Host_coral_reef_id";
    String units "unitless";
  }
  location_survey_date {
    String long_name "Location_survey_date";
    String units "unitless";
  }
  location_mean_total_species {
    Float32 actual_range 0.0, 3.666667;
    String long_name "Location_mean_total_species";
    String units "unitless";
  }
  FCM_Pro_mL {
    Float32 actual_range 1601.96, 255552.0;
    String long_name "Fcm_pro_ml";
    String units "cells per milliliter (cells/mL)";
  }
  FCM_Syn_mL {
    Float32 actual_range 22466.83, 84431.17;
    String long_name "Fcm_syn_ml";
    String units "cells per milliliter (cells/mL)";
  }
  FCM_Peuk_mL {
    Float32 actual_range 1181.774, 4136.208;
    String long_name "Fcm_peuk_ml";
    String units "cells per milliliter (cells/mL)";
  }
  FCM_Hbac_mL {
    Float32 actual_range 593263.6, 914023.3;
    String long_name "Fcm_hbac_ml";
    String units "cells per milliliter (cells/mL)";
  }
  NPOC_uM {
    Float32 actual_range 70.05134, 257.6029;
    String long_name "Npoc_um";
    String units "micromolar (uM)";
  }
  TN_uM {
    Float32 actual_range 5.411319, 11.66622;
    String long_name "Tn_um";
    String units "micromolar (uM)";
  }
  phosphate {
    Float32 actual_range 0.0755, 0.1634;
    String long_name "Phosphate";
    String units "micromolar (uM)";
  }
  nitrate_nitrite {
    Float32 actual_range 0.0851, 1.259;
    String long_name "Nitrate_nitrite";
    String units "micromolar (uM)";
  }
  silicate {
    Float32 actual_range 1.0046, 4.2762;
    String long_name "Silicate";
    String units "micromolar (uM)";
  }
  NO2 {
    Float32 actual_range -0.0049, 0.0764;
    String long_name "No2";
    String units "micromolar (uM)";
  }
  ammonium {
    Float32 actual_range 0.2235, 0.8573;
    String long_name "Ammonium";
    String units "micromolar (uM)";
  }
  nitrate {
    Float32 actual_range 0.0881, 1.2039;
    String long_name "Nitrate";
    String units "micromolar (uM)";
  }
 }
  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.906740.1";
    Float64 Easternmost_Easting -64.8109;
    Float64 geospatial_lon_max -64.8109;
    Float64 geospatial_lon_min -80.81375;
    String geospatial_lon_units "degrees_east";
    String history 
"2024-11-13T09:24:30Z (local files)
2024-11-13T09:24:30Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_906740_v1.das";
    String infoUrl "https://www.bco-dmo.org/dataset/906740";
    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 "Coral reefs host some of the most iconic symbiotic interactions in nature and are host to the highest diversity of life on the planet. Cleaning symbiosis, wherein small fish or shrimp remove external parasites and associated microorganisms from specific clients, is common on coral reefs. Sites on the reef occupied by cleaners, or \"cleaning stations\", attract a wide variety of fish species that engage in direct physical contact with the cleaner. In this study, we used a combination of ecological surveys, in situ manipulations, and laboratory experiments to examine the unique features of cleaning stations to understand transfer of bacterial and archaeal symbionts amongst fish and within coral reef environment. We used microbial 16S rRNA gene amplicons, environmental parameters, and other molecular tools to evaluate the dynamics between coral microbiomes, cleanerfish skin microbiomes, and the environment. This dataset contains metadata describing sequenced samples, including sample name, data deposition accession records, and measurements at the time of sample collection.";
    String title "[Microbiome dynamics of coral reef and cleanerfish] - Microbiome dynamics of coral reef and cleanerfish from ecological surveys, in situ manipulations, and laboratory experiments conducted from 2020-2021 (Collaborative Research: Cleaning stations as hubs for the maintenance and recovery of microbial diversity on coral reefs.)";
    Float64 Westernmost_Easting -80.81375;
  }
}

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.

ERDDAP, Version 2.22
Disclaimers | Privacy Policy | Contact