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Dataset Title:  [Larval morphometrics Strongylocentrotus purpuratus under ocean warming and
food availability scenarios] - Larval morphometrics of Strongylocentrotus
purpuratus under ocean warming and food availability scenarios (Collaborative
Research: The effects of marine heatwaves on reproduction, larval transport and
recruitment in sea urchin metapopulations)
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_963425_v1)
Information:  Summary ? | License ? | Metadata | Background (external link) | Data Access Form | Files
 
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    [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 {
  dpf {
    Int32 actual_range 4, 15;
    String long_name "Dpf";
    String units "days";
  }
  temp {
    Int32 actual_range 10, 20;
    String long_name "Temp";
    String units "degrees Celsius";
  }
  food {
    Int32 actual_range 500, 10000;
    String long_name "Food";
    String units "cells per mL";
  }
  rep {
    Int32 actual_range 1, 4;
    String long_name "Rep";
    String units "unitless";
  }
  individual {
    Int32 actual_range 1, 20;
    String long_name "Individual";
    String units "unitless";
  }
  POA1 {
    Float32 actual_range 91.0992, 664.0512;
    String long_name "Poa1";
    String units "µm";
  }
  POA2 {
    Float32 actual_range 100.1838, 679.0476;
    String long_name "Poa2";
    String units "µm";
  }
  BL {
    Float32 actual_range 79.4904, 410.463;
    String long_name "Bl";
    String units "µm";
  }
  SW {
    Float32 actual_range 21.3654, 179.4414;
    String long_name "Sw";
    String units "µm";
  }
  SH {
    Float32 actual_range 23.0904, 219.312;
    String long_name "Sh";
    String units "µm";
  }
  POA {
    Float32 actual_range 95.6415, 667.0095;
    String long_name "Poa";
    String units "µm";
  }
  SA {
    Float32 actual_range 415.1201, 30908.29;
    String long_name "Sa";
    String units "µm2";
  }
 }
  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.963425.1";
    String history 
"2025-08-25T21:09:49Z (local files)
2025-08-25T21:09:49Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_963425_v1.das";
    String infoUrl "https://osprey.bco-dmo.org/dataset/963425";
    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 
"Trends in survival, morphometric patterns, and time to metamorphic competency across temperature and food availability treatments were measured in S. purpuratus larvae. 

Larvae were spawned from adult purple urchins collected in Santa Barbara, CA. Effects of temperature and food availability were tested using a 6 x 4 factorial experimental design with six temperature treatments (10, 12, 14, 16, 18, 20°C) and four concentrations of Rhodomonas sp. microalgae (500, 2500, 5000, 10,000 cells mL-1) for a total of 24 treatment combinations. Food treatments represented algal concentrations from starvation to ad libitum conditions. Temperature and food treatments were based on historical observations of temperature trends and chlorophyll abundance. Larval samples were collected 4, 9, and 15 days post-fertilization and fixed in 10% PBS buffered formalin for morphometric analyses. 

Samples were collected before feeding to minimize influence of algae on stomach measurements. Fixed larvae were then photographed using an Olympus BX41 compound microscope with a Nikon 3400 DSLR camera at 4X magnification and postoral arm length, body length, stomach length and height were measured in 20 randomly selected larvae from each sample using ImageJ software (Schneider et al. 2012). Metamorphic competency was determined when >50% of larvae exhibited tube feet and adhered to the bottle.";
    String title "[Larval morphometrics Strongylocentrotus purpuratus under ocean warming and food availability scenarios] - Larval morphometrics of Strongylocentrotus purpuratus under ocean warming and food availability scenarios (Collaborative Research: The effects of marine heatwaves on reproduction, larval transport and recruitment in sea urchin metapopulations)";
  }
}

 

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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