BCO-DMO ERDDAP
Accessing BCO-DMO data
log in    
Brought to you by BCO-DMO    

ERDDAP > tabledap > Make A Graph ?

Dataset Title:  [SALT larval geochemical fingerprints] - Shell trace elemental
data (geochemical fingerprints) from larval samples collected during cruises
AT42-24, AT50-04, and TN391 in the Gulf of Mexico and Northwestern Atlantic in
2020, 2021, and 2022 (Collaborative Research: dispersal depth and the transport
of deep-sea, methane-seep larvae around a biogeographic barrier)
Subscribe RSS
Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_995312_v1)
Range: longitude = -91.50824 to -76.1903°E, latitude = 26.02868 to 32.49499°N, depth = 540.0 to 3287.0m
Information:  Summary ? | License ? | FGDC | ISO 19115 | Metadata | Background (external link) | Data Access Form | Files
 
Graph Type:  ?
X Axis: 
Y Axis: 
Color: 
-1+1
 
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.Hover here to see a list of options. Click on an option to select it.Hover here to see a list of options. Click on an option to select it.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: 
Draw land mask: 
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 ? )
    Click on the map to specify a new center point. ?
Zoom: 
[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:

The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  YearSampled {
    Int32 actual_range 2020, 2022;
    String long_name "Yearsampled";
    String units "unitless";
  }
  Date {
    String long_name "Date";
    String units "unitless";
  }
  Cruise {
    String long_name "Cruise";
    String units "unitless";
  }
  Vehicle {
    String long_name "Vehicle";
    String units "unitless";
  }
  Dive_Number {
    Int32 actual_range 1331, 5121;
    String long_name "Dive_number";
    String units "unitless";
  }
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    Int32 actual_range 540, 3287;
    String axis "Z";
    String ioos_category "Location";
    String long_name "Depth";
    String positive "down";
    String standard_name "depth";
    String units "m";
  }
  Site {
    String long_name "Site";
    String units "unitless";
  }
  Site_Name {
    String long_name "Site_name";
    String units "unitless";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float32 actual_range 26.02868, 32.49499;
    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 -91.50824, -76.1903;
    String axis "X";
    String ioos_category "Location";
    String long_name "Longitude";
    String standard_name "longitude";
    String units "degrees_east";
  }
  Sample {
    String long_name "Sample";
    String units "unitless";
  }
  Mgof25 {
    Float32 actual_range 1.86537, 529.7109;
    String long_name "Mgof25";
    String units "mmol/mol";
  }
  Mn {
    Float32 actual_range 2.6e-4, 0.08018;
    String long_name "Mn";
    String units "mmol/mol";
  }
  Ni {
    Float32 actual_range 0.00101, 54.50176;
    String long_name "Ni";
    String units "mmol/mol";
  }
  Sr {
    Float32 actual_range 0.6916, 6.61898;
    String long_name "Sr";
    String units "mmol/mol";
  }
  Ba {
    Float32 actual_range 0.00138, 0.95225;
    String long_name "Ba";
    String units "mmol/mol";
  }
  ValveID {
    String long_name "Valveid";
    String units "unitless";
  }
  ShortLong {
    String long_name "Shortlong";
    String units "unitless";
  }
  LengthCont {
    Float32 actual_range 290.0, 2575.5;
    String long_name "Lengthcont";
    String units "micromoles (um)";
  }
  WidthCont {
    Float32 actual_range 320.0, 2009.2;
    String long_name "Widthcont";
    String units "micromoles (um)";
  }
  LengthCat {
    String long_name "Lengthcat";
    String units "unitless";
  }
  WidthCat {
    String long_name "Widthcat";
    String units "unitless";
  }
  YearAblated {
    Int32 actual_range 2021, 2024;
    String long_name "Yearablated";
    String units "unitless";
  }
  AblationOrderValvesAndStandards {
    Int32 actual_range 7, 360;
    String long_name "Ablationordervalvesandstandards";
    String units "unitless";
  }
  AblationOrderValvesOnly {
    Int32 actual_range 1, 205;
    String long_name "Ablationordervalvesonly";
    String units "unitless";
  }
  Subsample {
    Int32 actual_range 1, 764;
    String long_name "Subsample";
    String units "unitless";
  }
  Slide {
    Int32 actual_range 1, 8;
    String long_name "Slide";
    String units "unitless";
  }
  SampleID {
    String long_name "Sampleid";
    String units "unitless";
  }
  GrowthRegion {
    String long_name "Growthregion";
    String units "unitless";
  }
  GeoReg {
    String long_name "Georeg";
    String units "unitless";
  }
  Species {
    String long_name "Species";
    String units "unitless";
  }
  Run {
    String long_name "Run";
    String units "unitless";
  }
  SubRun {
    String long_name "Subrun";
    String units "unitless";
  }
  HighTinCollapseFine {
    String long_name "Hightincollapsefine";
    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.995312.1";
    Float64 Easternmost_Easting -76.1903;
    Float64 geospatial_lat_max 32.49499;
    Float64 geospatial_lat_min 26.02868;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -76.1903;
    Float64 geospatial_lon_min -91.50824;
    String geospatial_lon_units "degrees_east";
    Float64 geospatial_vertical_max 3287.0;
    Float64 geospatial_vertical_min 540.0;
    String geospatial_vertical_positive "down";
    String geospatial_vertical_units "m";
    String history 
"2026-04-05T13:30:01Z (local files)
2026-04-05T13:30:01Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_995312_v1.das";
    String infoUrl "https://osprey.bco-dmo.org/dataset/995312";
    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 32.49499;
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 26.02868;
    String summary "Larval dispersal drives metapopulation connectivity, a key metric of population resilience to disturbance. Deep-sea larval disperal remains poorly understood due to the limited applicability of nearshore approaches such as larval rearing in-situ. Here, we used laser ablation spectrometry (Jackson School of Geosciences at the University of Texas at Austin) and multivariate statistical analyses (i.e., PERMANOVA and CAP) to quantify larval shell trace elemental fingerprints for deep-sea methane seep mussels Gigantidas childressi and Bathymodiolus heckerae to infer spatiotemporal mixing of larval population pools in the Gulf of Mexico and Western Atlantic Margin. Larvae were collected during R/V Atlantis cruises AT42-24 (Spring 2020) and AT50-04 (Fall 2022), and R/V Thomas G. Thompson  cruise TN-391 (Summer 2021). We analysed variation in fingerprints of 366 larvae among depths (500-3,000m), seven seep sites, and three sampling years (spawning periods). Fingerprints differed significantly among depths across spawning periods, among sites within spawning periods, and among spawning periods themselves. Results may reflect divergence in sources of organic matter during dispersal due to shifts in dispersal trajectories or water mass environmental chemistry over time. Additionally, results indicate that larvae may mix during early dispersal (i.e., during formation of the prodissoconch I shell growth region) and become more isolated by later dispersal (i.e., formation of prodissoconch II). Overall, over timescales of only a few years, deep-sea mussel larval pools may be subtly spatiotemporally isolated, which may limit population resilience to natural and anthropogenic disturbance.";
    String title "[SALT larval geochemical fingerprints] - Shell trace elemental data (geochemical fingerprints) from larval samples collected during cruises AT42-24, AT50-04, and TN391 in the Gulf of Mexico and Northwestern Atlantic in 2020, 2021, and 2022 (Collaborative Research: dispersal depth and the transport of deep-sea, methane-seep larvae around a biogeographic barrier)";
    Float64 Westernmost_Easting -91.50824;
  }
}

 

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.


 
ERDDAP, Version 2.22
Disclaimers | Privacy Policy | Contact