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Dataset Title:  Environmental sensor data collected in Palau marine lakes from small boats,
2011-2015
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_768037)
Range: depth = 0.0 to 34.0m
Information:  Summary ? | License ? | ISO 19115 | Metadata | Background (external link) | Data Access Form | Files
 
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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:

The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  lake_code {
    String bcodmo_name "site";
    String description "3-letter code for sampled lake name";
    String long_name "Lake Code";
    String units "unitless";
  }
  year {
    Int16 _FillValue 32767;
    Int16 actual_range 2011, 2015;
    String bcodmo_name "year";
    String description "Sampling year";
    String long_name "Year";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/YEARXXXX/";
    String units "unitless";
  }
  date_ISO {
    String bcodmo_name "date";
    String description "Sampling date in ISO  format (yyyy-mm-dd)";
    String long_name "Date ISO";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/ADATAA01/";
    String source_name "date_ISO";
    String time_precision "1970-01-01";
    String units "unitless";
  }
  face {
    String bcodmo_name "unknown";
    String description "cardinal direction indicating in which section of the lake basin sampling was conducted";
    String long_name "Face";
    String units "unitless";
  }
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    Float64 _FillValue NaN;
    Float64 actual_range 0.0, 34.0;
    String axis "Z";
    String bcodmo_name "depth";
    Float64 colorBarMaximum 8000.0;
    Float64 colorBarMinimum -8000.0;
    String colorBarPalette "TopographyDepth";
    String description "depth at which the measurement made";
    String ioos_category "Location";
    String long_name "Depth";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/DEPH/";
    String positive "down";
    String standard_name "depth";
    String units "m";
  }
  temperature {
    Float32 _FillValue NaN;
    Float32 actual_range 26.93, 37.04;
    String bcodmo_name "temperature";
    String description "water temperature";
    String long_name "Temperature";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/TEMPP901/";
    String units "degrees Celsius";
  }
  conductivity {
    Float32 _FillValue NaN;
    Float32 actual_range 7.24, 52.5;
    String bcodmo_name "conductivity";
    Float64 colorBarMaximum 40.0;
    Float64 colorBarMinimum 30.0;
    String description "Conductivity";
    String long_name "Sea Water Electrical Conductivity";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/CNDC/";
    String units "microSiemans/centimeter (mS/cm)";
  }
  salinity {
    Float32 _FillValue NaN;
    Float32 actual_range 4.0, 34.81;
    String bcodmo_name "sal";
    Float64 colorBarMaximum 37.0;
    Float64 colorBarMinimum 32.0;
    String description "salinity";
    String long_name "Sea Water Practical Salinity";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/PSALST01/";
    String units "parts per thousand (ppt)";
  }
  oxygen {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 300.0;
    String bcodmo_name "dissolved Oxygen";
    String description "Dissolved oxygen; LDO";
    String long_name "Oxygen";
    String units "milligrams/liter (mg/L)";
  }
  pH {
    Float32 _FillValue NaN;
    Float32 actual_range 6.37, 8.38;
    String bcodmo_name "pH";
    Float64 colorBarMaximum 9.0;
    Float64 colorBarMinimum 7.0;
    String description "pH";
    String long_name "Sea Water Ph Reported On Total Scale";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/PHXXZZXX/";
    String units "unitless";
  }
  PAR {
    Int16 _FillValue 32767;
    Int16 actual_range 1, 3120;
    String bcodmo_name "PAR";
    Float64 colorBarMaximum 70.0;
    Float64 colorBarMinimum 0.0;
    String description "Photosynthetically Active Radiation; Li-Cor Ambient Light sensor";
    String long_name "Downwelling Photosynthetic Photon Radiance In Sea Water";
    String units "micromol/second/meter^2  (umol s-1m-2)";
  }
  CHL {
    Float32 _FillValue NaN;
    Float32 actual_range 0.22, 1251.8;
    String bcodmo_name "chlorophyll a";
    String description "Chlorophyll a concentration";
    String long_name "CHL";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/CPHLHPP1/";
    String units "micrograms/liter (ug/L)";
  }
  method {
    String bcodmo_name "instrument";
    String description "Type of meter used for the measurement: \"Quanta\" or \"DS5\" or \"old-meter\" (an earlier Quanta)";
    String long_name "Method";
    String units "unitless";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv";
    String acquisition_description 
"The sonde with sensors was deployed manually from a raft or other floating
craft (e.g. Caddis Fly inflatable seat). The sonde was lowered at one meter
intervals and, at each depth interval, the reading was allowed to stabilize
before readings were transcribed from the handheld meter to a dive slate in
the field. Following return to the laboratory, data on the dive slate were
entered into a spreadsheet, a preliminary plot made, and any apparent
erroneous data (e.g. density inversions) were double-checked for accuracy of
transcription and corrected as necessary.";
    String awards_0_award_nid "55103";
    String awards_0_award_number "OCE-1241255";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1241255";
    String awards_0_funder_name "NSF Division of Ocean Sciences";
    String awards_0_funding_acronym "NSF OCE";
    String awards_0_funding_source_nid "355";
    String awards_0_program_manager "David L. Garrison";
    String awards_0_program_manager_nid "50534";
    String cdm_data_type "Other";
    String comment 
"Lake environmental data 
   Palau marine lake environmental sensor data, 2011-2015 
   M. Dawson (UC-Merced) 
   version date: 2019-05-13";
    String Conventions "COARDS, CF-1.6, ACDD-1.3";
    String creator_email "info@bco-dmo.org";
    String creator_name "BCO-DMO";
    String creator_type "institution";
    String creator_url "https://www.bco-dmo.org/";
    String data_source "extract_data_as_tsv version 2.3  19 Dec 2019";
    String date_created "2019-05-15T16:33:12Z";
    String date_modified "2019-07-08T12:59:20Z";
    String defaultDataQuery "&time<now";
    String doi "10.1575/1912/bco-dmo.768037.1";
    Float64 geospatial_vertical_max 34.0;
    Float64 geospatial_vertical_min 0.0;
    String geospatial_vertical_positive "down";
    String geospatial_vertical_units "m";
    String history 
"2020-12-01T18:03:14Z (local files)
2020-12-01T18:03:14Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_768037.das";
    String infoUrl "https://www.bco-dmo.org/dataset/768037";
    String institution "BCO-DMO";
    String instruments_0_acronym "unknown";
    String instruments_0_dataset_instrument_description "Multiparameter water quality sonde measuring Temperature, Conductivity, Depth, pH, Oxygen Reduction Potential (ORP), Dissolved Oxygen (Clark Cell), Turbidity.";
    String instruments_0_dataset_instrument_nid "768108";
    String instruments_0_description "No relevant match in BCO-DMO instrument vocabulary.";
    String instruments_0_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/999/";
    String instruments_0_instrument_name "unknown";
    String instruments_0_instrument_nid "575";
    String instruments_0_supplied_name "Hydrolab Quanta Multi-Probe Meter multiparameter water quality sonde";
    String instruments_1_dataset_instrument_nid "768063";
    String instruments_1_description "Acquires satellite signals and tracks your location.";
    String instruments_1_instrument_name "GPS receiver";
    String instruments_1_instrument_nid "706037";
    String instruments_1_supplied_name "Garmin GPSMAP 60CSx handheld GPS unit";
    String instruments_2_acronym "HydroLab DS5";
    String instruments_2_dataset_instrument_description "Dissolved oxygen, temperature, pH, chlorophyll fluorescence and salinity/conductivity were measured using a HydroLab DS5 Multiparameter Data Sonde (Hach Company, Loveland, CO, USA).";
    String instruments_2_dataset_instrument_nid "768062";
    String instruments_2_description "Multi-parameter probes that can measure from 12 (MS5) to 16 (DS5 and DS5X) parameters simultaneously. Measurements include temperature, depth, conductivity, salinity, specific conductance, TDS, pH, ORP, dissolved oxygen, turbidity, chlorophyll a, blue-green algae, Rhodamine WT, ammonium, nitrate, chloride, PAR and total dissolved gases. These probes can be deployed at depths up to 200 m and can be used in continuous monitoring programs.";
    String instruments_2_instrument_name "Hydrolab Series 5 probes";
    String instruments_2_instrument_nid "768060";
    String instruments_2_supplied_name "Hydrolab DS5";
    String keywords "active, available, bco, bco-dmo, biological, chemical, chemistry, chl, chlorophyll, code, conductivity, data, dataset, date, density, depth, dmo, downwelling, downwelling_photosynthetic_photon_radiance_in_sea_water, earth, Earth Science > Oceans > Ocean Chemistry > pH, Earth Science > Oceans > Ocean Optics > Photosynthetically Active Radiation, Earth Science > Oceans > Ocean Optics > Radiance, Earth Science > Oceans > Salinity/Density > Conductivity, Earth Science > Oceans > Salinity/Density > Salinity, electrical, erddap, face, iso, lake, lake_code, management, method, O2, ocean, oceanography, oceans, office, optics, oxygen, PAR, photon, photosynthetic, photosynthetically, practical, preliminary, radiance, radiation, reported, salinity, scale, science, sea, sea_water_electrical_conductivity, sea_water_ph_reported_on_total_scale, sea_water_practical_salinity, seawater, temperature, time, total, water, year";
    String keywords_vocabulary "GCMD Science Keywords";
    String license "https://www.bco-dmo.org/dataset/768037/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/768037";
    String param_mapping "{'768037': {'depth': 'master - depth'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/768037/parameters";
    String people_0_affiliation "University of California-Merced";
    String people_0_affiliation_acronym "UC Merced";
    String people_0_person_name "Michael N Dawson";
    String people_0_person_nid "51577";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "Woods Hole Oceanographic Institution";
    String people_1_affiliation_acronym "WHOI BCO-DMO";
    String people_1_person_name "Nancy Copley";
    String people_1_person_nid "50396";
    String people_1_role "BCO-DMO Data Manager";
    String people_1_role_type "related";
    String project "PaPaPro";
    String projects_0_acronym "PaPaPro";
    String projects_0_description 
"This project will survey the taxonomic, genetic, and functional diversity of the organisms found in marine lakes, and investigate the processes that cause gains and losses in this biodiversity. Marine lakes formed as melting ice sheets raised sea level after the last glacial maximum and flooded hundreds of inland valleys around the world. Inoculated with marine life from the surrounding sea and then isolated to varying degrees for the next 6,000 to 15,000 years, these marine lakes provide multiple, independent examples of how environments and interactions between species can drive extinction and speciation. Researchers will survey the microbes, algae, invertebrates, and fishes present in 40 marine lakes in Palau and Papua, and study how diversity has changed over time by retrieving the remains of organisms preserved in sediments on the lake bottoms. The project will test whether the number of species, the diversity of functional roles played by organisms, and the genetic diversity within species increase and decrease in parallel; whether certain species can greatly curtail diversity by changing the environment; whether the size of a lake determines its biodiversity; and whether the processes that control diversity in marine organisms are similar to those that operate on land.
Because biodiversity underlies the ecosystem services on which society depends, society has a great interest in understanding the processes that generate and retain biodiversity in nature. This project will also help conserve areas of economic importance. Marine lakes in the study region are important for tourism, and researchers will work closely with governmental and non-governmental conservation and education groups and with diving and tourism businesses to raise awareness of the value and threats to marine lakes in Indonesia and Palau.";
    String projects_0_end_date "2017-12";
    String projects_0_geolocation "Western Pacific; Palau; Indonesia (West Papua)";
    String projects_0_name "Do Parallel Patterns Arise from Parallel Processes?";
    String projects_0_project_nid "2238";
    String projects_0_project_website "http://marinelakes.ucmerced.edu/";
    String projects_0_start_date "2013-01";
    String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
    String publisher_type "institution";
    String sourceUrl "(local files)";
    String standard_name_vocabulary "CF Standard Name Table v55";
    String summary "Environmental sensor data describing Palau lake environments, 2011-2015. Reported parameters include depth, temperature, conductivity, salinity, oxygen, pH, light, and chlorophyll.";
    String title "Environmental sensor data collected in Palau marine lakes from small boats, 2011-2015";
    String version "1";
    String xml_source "osprey2erddap.update_xml() v1.3";
  }
}

 

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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