Data Access Form

Dataset Title:	[Cerro Mundo Temperature 2] - Environmental temperature data collected at Cerro Mundo Bay, San Cristobal, Galapagos from 2022-2023 (Galapagos 2021 project) (Temperature Regulation of Top-Down Control in a Pacific Upwelling System)
Institution:	BCO-DMO (Dataset ID: bcodmo_dataset_904195_v1)
Information:	Summary \| License \| Metadata \| Background \| Files \| Make a graph

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Variable	Minimum	Maximum
DateTime_Local (unitless)	"2022-09-01T00:00"	"2023-02-15T09:53"
time (Iso_datetime_utc, UTC)
Temp (Celcius)	14.601	27.5
Latitude (degrees_north)	-0.87044	-0.87044
longitude (degrees_east)	-89.58189	-89.58189

depth (m)	10.0	10.0

Server-side Functions

distinct()

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File type: (more information)

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The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  DateTime_Local {
    String long_name "Datetime_local";
    String units "unitless";
  }
  time {
    String _CoordinateAxisType "Time";
    String axis "T";
    String ioos_category "Time";
    String long_name "Iso_datetime_utc";
    String standard_name "time";
    String time_origin "01-JAN-1970 00:00:00";
    String units "seconds since 1970-01-01T00:00:00Z";
  }
  Temp {
    Float32 actual_range 14.601, 27.5;
    String long_name "Temp";
    String units "Celcius";
  }
  Latitude {
    Float32 actual_range -0.87044, -0.87044;
    String long_name "Latitude";
    String units "degrees_north";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float32 actual_range -89.58189, -89.58189;
    String axis "X";
    String ioos_category "Location";
    String long_name "Longitude";
    String standard_name "longitude";
    String units "degrees_east";
  }
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    Float32 actual_range 10.0, 10.0;
    String axis "Z";
    String ioos_category "Location";
    String long_name "Depth";
    String positive "down";
    String standard_name "depth";
    String units "m";
  }
 }
  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.904195.1";
    Float64 Easternmost_Easting -89.58189;
    Float64 geospatial_lon_max -89.58189;
    Float64 geospatial_lon_min -89.58189;
    String geospatial_lon_units "degrees_east";
    Float64 geospatial_vertical_max 10.0;
    Float64 geospatial_vertical_min 10.0;
    String geospatial_vertical_positive "down";
    String geospatial_vertical_units "m";
    String history 
"2024-11-15T16:12:21Z (local files)
2024-11-15T16:12:21Z https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_904195_v1.html";
    String infoUrl "https://www.bco-dmo.org/dataset/904195";
    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 is 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 a set of temperature (°C) data collected at Cerro Mundo Bay, San Cristobal, Galapagos from September 2022 to February 2023. The environmental temperature was recorded every 15 minutes using a HOBO Water Temperature pro V2 Data Logger (Onset®) attached to the seafloor at a 10 meters depth mark.";
    String title "[Cerro Mundo Temperature 2] - Environmental temperature data collected at Cerro Mundo Bay, San Cristobal, Galapagos from 2022-2023 (Galapagos 2021 project) (Temperature Regulation of Top-Down Control in a Pacific Upwelling System)";
    Float64 Westernmost_Easting -89.58189;
  }
}

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.