BCO-DMO ERDDAP
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Dataset Title:	[Cerro Mundo Algal Ash-Free Dry Weight] - Macroalgal biomass data (Preburn, Postburn, and Ash-Free Dry Weight) collected in the nearshore shallow subtidal during six field experiments conducted at Cerro Mundo Bay in the Galapagos Islands between July 2021 and May 2022 (The Role of Temperature in Regulating Herbivory and Algal Biomass in Upwelling Systems)
Institution:	BCO-DMO (Dataset ID: bcodmo_dataset_894169_v1)
Information:	Summary \| License \| Metadata \| Background \| Data Access Form \| Files

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Constraints	Optional Constraint #1		Optional Constraint #2

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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 {
  Trial {
    String long_name "Trial";
    String units "unitless";
  }
  Cage {
    Int32 actual_range 1, 64;
    String long_name "Cage";
    String units "unitless";
  }
  Treatment {
    String long_name "Treatment";
    String units "unitless";
  }
  N {
    String long_name "N";
    String units "unitless";
  }
  Algae_Type {
    String long_name "Algae_type";
    String units "unitless";
  }
  Foil_cup_weight {
    Float32 actual_range 0.0, 135.415;
    String long_name "Foil_cup_weight";
    String units "grams (g)";
  }
  Sample_and_foil_cup_weight {
    Float32 actual_range 0.0, 140.976;
    String long_name "Sample_and_foil_cup_weight";
    String units "grams (g)";
  }
  Preburn_weight {
    Float32 actual_range 0.0, 28.715;
    String long_name "Preburn_weight";
    String units "grams (g)";
  }
  Ceramic_cup_weight {
    Float32 actual_range 0.0, 399.557;
    String long_name "Ceramic_cup_weight";
    String units "grams (g)";
  }
  Sample_and_ceramic_cup_weight {
    Float32 actual_range 0.0, 412.863;
    String long_name "Sample_and_ceramic_cup_weight";
    String units "grams (g)";
  }
  Postburn_weight {
    Float32 actual_range 0.0, 22.58;
    String long_name "Postburn_weight";
    String units "grams (g)";
  }
  AFDW {
    Float32 actual_range 0.0, 16.267;
    String long_name "Afdw";
    String units "grams (g)";
  }
 }
  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.894169.1";
    String history 
"2024-11-08T05:44:43Z (local files)
2024-11-08T05:44:43Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_894169_v1.das";
    String infoUrl "https://www.bco-dmo.org/dataset/894169";
    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 
"Increased standing macroalgal biomass in upwelling zones is generally assumed to be the result of higher nutrient flux due to upwelled waters. However, other factors can strongly impact macroalgal communities. For example, herbivory and temperature, via their effects on primary producers and the metabolic demands of consumers, can also influence macroalgal biomass and productivity, respectively.  Although there are a fair number of studies looking at the interactive effects of herbivores and nutrients in both tropical and temperate regions, there is a lack of studies looking at these effects in tropical or subtropical upwelling regions. The purpose of this study was to measure the effects that herbivores, temperature, and nutrient availability have on standing macroalgal biomass. We manipulated nutrient availability and herbivory in six field experiments during contrasting productivity and thermal regimes (cool-upwelling and warm, non-upwelling season) on a subtidal nearshore rocky reef.

Here, we present the macroalgal biomass raw data (Preburn, Postburn, and Ash-Free Dry Weight) collected in the nearshore shallow subtidal during the six field experiments.";
    String title "[Cerro Mundo Algal Ash-Free Dry Weight] - Macroalgal biomass data (Preburn, Postburn, and Ash-Free Dry Weight) collected in the nearshore shallow subtidal during six field experiments conducted at Cerro Mundo Bay in the Galapagos Islands between July 2021 and May 2022 (The Role of Temperature in Regulating Herbivory and Algal Biomass in Upwelling Systems)";
  }
}

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.

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