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

ERDDAP > tabledap > Data Access Form ?

Dataset Title:  [Cerro Mundo Temperature] - Temperature data collected at Cerro Mundo Bay, San
Cristobal, Galapagos from July 2019 to August 2022 using an Onset HOBO Water
Temperature Pro v2 Data Logger (The Role of Temperature in Regulating Herbivory
and Algal Biomass in Upwelling Systems)
Subscribe RSS
Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_894125_v1)
Information:  Summary ? | License ? | Metadata | Background (external link) | Files | Make a graph
 
Variable ?   Optional
Constraint #1 ?
Optional
Constraint #2 ?
   Minimum ?
 
   Maximum ?
 
 ISO_DateTime_Local (unitless) ?          "2019-07-28T10:30"    "2022-08-31T23:50"
 time (Iso_datetime_utc, UTC) ?          2019-07-28T16:30:00Z    2022-09-01T05:50:00Z
  < slider >
 Temp (degrees Celsius) ?          14.481    32.6
 
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.Hover here to see a list of options. Click on an option to select it.")

File type: (more information)

(Documentation / Bypass this form ? )
 
(Please be patient. It may take a while to get the data.)


 

The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  ISO_DateTime_Local {
    String long_name "Iso_datetime_local";
    String units "unitless";
  }
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 1.5643314e+9, 1.6620114e+9;
    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 14.481, 32.6;
    String long_name "Temp";
    String units "degrees Celsius";
  }
 }
  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.894125.1";
    String history 
"2024-11-21T09:08:31Z (local files)
2024-11-21T09:08:31Z https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_894125_v1.html";
    String infoUrl "https://www.bco-dmo.org/dataset/894125";
    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 a set of temperature (°C) data collected at Cerro Mundo Bay, San Cristobal, Galapagos from July 2019 to August 2022. 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 time_coverage_end "2022-09-01T05:50:00Z";
    String time_coverage_start "2019-07-28T16:30:00Z";
    String title "[Cerro Mundo Temperature] - Temperature data collected at Cerro Mundo Bay, San Cristobal, Galapagos from July 2019 to August 2022 using an Onset HOBO Water Temperature Pro v2 Data Logger (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.

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