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Dataset Title:  [Short-term heat stress assay: Photochemical yield data] - Photochemical yield
and bleaching severity data from a standardized short-term (18 hour) heat
stress assay of Montipora capitata and Porites compressa collected at a patch
reef in Kane'ohe Bay, O'ahu, Hawai'i in September of 2022 (RAPID: Collaborative
Research: Disentangling the effects of heat stress versus bleaching phenotype
on coral performance)
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_914723_v1)
Information:  Summary ? | License ? | Metadata | Background (external link) | Data Access Form | Files
 
Graph Type:  ?
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Y Axis: 
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Constraints ? Optional
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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.")
 
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   Minimum:   Maximum:   N Sections: 
Y Axis Minimum:   Maximum:   
 
(Please be patient. It may take a while to get the data.)
 
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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 {
  Treatment {
    String long_name "Treatment";
    String units "unitless";
  }
  Temperature {
    Float32 actual_range 27.7, 36.7;
    String long_name "Temperature";
    String units "degrees Celcius";
  }
  Species {
    String long_name "Species";
    String units "unitless";
  }
  Bleach {
    String long_name "Bleach";
    String units "unitless";
  }
  Colony_ID {
    Int32 actual_range 3, 248;
    String long_name "Colony_id";
    String units "unitless";
  }
  Rep {
    Int32 actual_range 1, 3;
    String long_name "Rep";
    String units "unitless";
  }
  F {
    Int32 actual_range 257, 801;
    String long_name "F";
    String units "unitless";
  }
  Y {
    Float32 actual_range 0.0, 0.755;
    String long_name "Y";
    String units "unitless";
  }
  M {
    Int32 actual_range 295, 2655;
    String long_name "M";
    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.914723.1";
    String history 
"2024-11-21T12:09:30Z (local files)
2024-11-21T12:09:30Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_914723_v1.das";
    String infoUrl "https://www.bco-dmo.org/dataset/914723";
    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 "Increasingly frequent marine heatwaves are devastating coral reefs. Corals that survive these extreme events must rapidly recover if they are to withstand subsequent events, and long-term survival in the face of rising ocean temperatures may hinge on recovery capacity and acclimatory gains in heat tolerance over an individual's lifespan. To better understand coral recovery trajectories in the face of successive marine heatwaves, we monitored the responses of bleaching-susceptible and bleaching-resistant individuals of two dominant coral species in Hawaiʻi, Montipora capitata and Porites compressa, over a decade that included three marine heatwaves.  This dataset includes the photochemical yield from the standardized short-term (18 hour) heat stress assay.";
    String title "[Short-term heat stress assay: Photochemical yield data] - Photochemical yield and bleaching severity data from a standardized short-term (18 hour) heat stress assay of Montipora capitata and Porites compressa collected at a patch reef in Kane'ohe Bay, O'ahu, Hawai'i in September of 2022 (RAPID: Collaborative Research: Disentangling the effects of heat stress versus bleaching phenotype on coral performance)";
  }
}

 

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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