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Dataset Title:  Record of d2H of dinosterol variability in down core lake sediments from Clear
Lake, Palau
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_699469)
Range: longitude = 134.3594 to 134.3594°E, latitude = 7.153167 to 7.153167°N
Information:  Summary ? | License ? | ISO 19115 | Metadata | Background (external link) | Subset | 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 {
  location {
    String bcodmo_name "site";
    String description "Name of the sampling location";
    String long_name "Location";
    String units "unitless";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 _FillValue NaN;
    Float64 actual_range 7.153166667, 7.153166667;
    String axis "Y";
    String bcodmo_name "latitude";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String description "Latitude of the location";
    String ioos_category "Location";
    String long_name "Latitude";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/LATX/";
    String standard_name "latitude";
    String units "degrees_north";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float64 _FillValue NaN;
    Float64 actual_range 134.3594, 134.3594;
    String axis "X";
    String bcodmo_name "longitude";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String description "Longitude of the location";
    String ioos_category "Location";
    String long_name "Longitude";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/LONX/";
    String standard_name "longitude";
    String units "degrees_east";
  }
  core_depth {
    Float64 _FillValue NaN;
    Float64 actual_range 0.5, 87.5;
    String bcodmo_name "depth_bsf";
    String description "Depth below sediment-water interface";
    String long_name "Core Depth";
    String units "centimeters (cm)";
  }
  age {
    Int16 _FillValue 32767;
    Int16 actual_range 1284, 2002;
    String bcodmo_name "age";
    String description "Calendar age of sample in year A.D.";
    String long_name "Age";
    String units "unitless";
  }
  dDdino {
    Float32 _FillValue NaN;
    Float32 actual_range -317.9, -266.9;
    String bcodmo_name "unknown";
    String description "d2Hdino: hydrogen isotopic composition of dinosterol";
    String long_name "D Ddino";
    String units "per mil";
  }
  dDdino_stdev {
    Float32 _FillValue NaN;
    Float32 actual_range 0.2, 10.7;
    String bcodmo_name "unknown";
    String description "1 sigma standard deviation on  d2Hdino";
    String long_name "D Ddino Stdev";
    String units "per mil";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson";
    String acquisition_description 
"Sampling and analytical procedures:  
 Clear Lake sediments were extracted using a Dionex Accelerated Solvent
Extractor (ASE 200), and the resulting total lipid extract was separated into
neutral and polar fractions using column chromatography with aminopropyl gel
as the stationary phase. The neutral fraction was then separated into
hydrocarbon, wax ester, sterol and polar fractions via a silica gel column
chromatography. Dinosterol was isolated then from the sterol fraction via
reverse phase (RP)- high-performance liquid chromatography (HPLC)\\u2028.
 
Instruments:  
 Dinosterol was isolated from the sterol fraction via reverse phase (RP)-
high performance liquid chromatography (HPLC). An Agilent 1100 HPLC with an
integrated autoinjector, quaternary pump, and fraction collector was coupled
to an Agilent 1100 LC/MSD SL mass spectrometer with a multimode source that
was operated in positive atmospheric pressure chemical ionization (APCI+)
mode. The HPLC method used is outlined in Nelson and Sachs
(2013).\\u00a0Subsequently to HPLC separation the fraction containing
dinosterol was analyzed via GC-MSD to verify sufficient baseline separation.
Adjacent HPLC fractions were also analyzed to ensure that no dinosterol eluted
into those fractions.
 
After the dinosterol was sufficiently isolated from co-eluting compounds, the
sample was injected onto a GC-irms for determination of the d2H of
dinosterol.\\u00a0 Hydrogen isotope determinations were made using a Finnigan
Delta V Plus Isotope Ratio Mass Spectrometer (irMS) coupled to a Thermo Trace
GC Ultra with a Varian VF-17ms FactorFour capillary column (60 m x 0.32 mm x
0.25 m) and a pyrolysis reactor. Samples were injected into a split/splitless
inlet in splitless mode at 310 C. The oven temperature was ramped from 100 C
to 220 C at a rate of 20 C/min, then at 2 C /min up to 325 C where it was held
for 17 min. The carrier gas, He, was held constant at 2.6 mL/min. The
pyroloysis reactor was maintained at 1400 C. Isotope values, expressed as D
values, were calculated in Isodat software relative to VSMOW using a co-
injection standard containing nC28 nC32, nC40, and nC44 of known \\u22022H
values (obtained from Arndt Schimmelmann, Indiana University, Bloomington, IN,
USA). The measured isotope values of dinosterol were corrected for the
addition of hydrogen atoms (of known D value) that occurred during
acetylation. Each sample was analyzed in at least duplicate, and error bars
represent standard deviations of replicate measurements.";
    String awards_0_award_nid "55104";
    String awards_0_award_number "OCE-1241247";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1241247";
    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 
"Clear Lake 800-yr reconstruction 
  Record of d2H of dinosterol variability in down core lake sediments 
 PI: Julian P. Sachs (University of Washington) 
 Co-PI: Julie N. Richey (University of Washington) 
 Version: 04 May 2017";
    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 "2017-05-04T19:36:35Z";
    String date_modified "2019-08-02T19:07:33Z";
    String defaultDataQuery "&time<now";
    String doi "10.1575/1912/bco-dmo.699469.1";
    Float64 Easternmost_Easting 134.3594;
    Float64 geospatial_lat_max 7.153166667;
    Float64 geospatial_lat_min 7.153166667;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max 134.3594;
    Float64 geospatial_lon_min 134.3594;
    String geospatial_lon_units "degrees_east";
    String history 
"2024-03-29T00:25:57Z (local files)
2024-03-29T00:25:57Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_699469.das";
    String infoUrl "https://www.bco-dmo.org/dataset/699469";
    String institution "BCO-DMO";
    String instruments_0_acronym "IR Mass Spec";
    String instruments_0_dataset_instrument_description "Hydrogen isotope determinations were made using a Finnigan Delta V Plus Isotope Ratio Mass Spectrometer (irMS) coupled to a Thermo Trace GC Ultra with a Varian VF-17ms FactorFour capillary column (60 m x 0.32 mm x 0.25 m) and a pyrolysis reactor.";
    String instruments_0_dataset_instrument_nid "699743";
    String instruments_0_description "The Isotope-ratio Mass Spectrometer is a particular type of mass spectrometer used to measure the relative abundance of isotopes in a given sample (e.g. VG Prism II Isotope Ratio Mass-Spectrometer).";
    String instruments_0_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/LAB16/";
    String instruments_0_instrument_name "Isotope-ratio Mass Spectrometer";
    String instruments_0_instrument_nid "469";
    String instruments_0_supplied_name "Finnigan Delta V Plus Isotope Ratio Mass Spectrometer (irMS)";
    String instruments_1_acronym "HPLC";
    String instruments_1_dataset_instrument_description "Dinosterol was isolated from the sterol fraction via reverse phase (RP)- high performance liquid chromatography (HPLC). An Agilent 1100 HPLC with an integrated autoinjector, quaternary pump, and fraction collector was coupled to an Agilent 1100 LC/MSD SL mass spectrometer with a multimode source that was operated in positive atmospheric pressure chemical ionization (APCI+) mode.";
    String instruments_1_dataset_instrument_nid "699741";
    String instruments_1_description "A High-performance liquid chromatograph (HPLC) is a type of liquid chromatography used to separate compounds that are dissolved in solution. HPLC instruments consist of a reservoir of the mobile phase, a pump, an injector, a separation column, and a detector. Compounds are separated by high pressure pumping of the sample mixture onto a column packed with microspheres coated with the stationary phase. The different components in the mixture pass through the column at different rates due to differences in their partitioning behavior between the mobile liquid phase and the stationary phase.";
    String instruments_1_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/LAB11/";
    String instruments_1_instrument_name "High Performance Liquid Chromatograph";
    String instruments_1_instrument_nid "506";
    String instruments_1_supplied_name "high-performance liquid chromatography";
    String instruments_2_acronym "Mass Spec";
    String instruments_2_dataset_instrument_description "Dinosterol was isolated from the sterol fraction via reverse phase (RP)- high performance liquid chromatography (HPLC). An Agilent 1100 HPLC with an integrated autoinjector, quaternary pump, and fraction collector was coupled to an Agilent 1100 LC/MSD SL mass spectrometer with a multimode source that was operated in positive atmospheric pressure chemical ionization (APCI+) mode.";
    String instruments_2_dataset_instrument_nid "699742";
    String instruments_2_description "General term for instruments used to measure the mass-to-charge ratio of ions; generally used to find the composition of a sample by generating a mass spectrum representing the masses of sample components.";
    String instruments_2_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/LAB16/";
    String instruments_2_instrument_name "Mass Spectrometer";
    String instruments_2_instrument_nid "685";
    String instruments_2_supplied_name "Agilent 1100 LC/MSD SL mass spectrometer";
    String keywords "age, bco, bco-dmo, biological, chemical, core, core_depth, data, dataset, dDdino, dDdino_stdev, ddino, depth, deviation, dmo, erddap, latitude, longitude, management, oceanography, office, preliminary, standard, standard deviation, stdev";
    String license "https://www.bco-dmo.org/dataset/699469/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/699469";
    Float64 Northernmost_Northing 7.153166667;
    String param_mapping "{'699469': {'lat': 'master - latitude', 'lon': 'master - longitude', 'core_depth': 'flag - depth'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/699469/parameters";
    String people_0_affiliation "University of Washington";
    String people_0_affiliation_acronym "UW";
    String people_0_person_name "Julian P. Sachs";
    String people_0_person_nid "51578";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "University of Washington";
    String people_1_affiliation_acronym "UW";
    String people_1_person_name "Julie N. Richey";
    String people_1_person_nid "699725";
    String people_1_role "Co-Principal Investigator";
    String people_1_role_type "originator";
    String people_2_affiliation "Woods Hole Oceanographic Institution";
    String people_2_affiliation_acronym "WHOI BCO-DMO";
    String people_2_person_name "Shannon Rauch";
    String people_2_person_nid "51498";
    String people_2_role "BCO-DMO Data Manager";
    String people_2_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)";
    Float64 Southernmost_Northing 7.153166667;
    String standard_name_vocabulary "CF Standard Name Table v55";
    String subsetVariables "location,latitude,longitude";
    String summary "Record of d2H of dinosterol variability in down core lake sediments from Clear Lake, Palau.";
    String title "Record of d2H of dinosterol variability in down core lake sediments from Clear Lake, Palau";
    String version "1";
    Float64 Westernmost_Easting 134.3594;
    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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