Accessing BCO-DMO data
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| Dataset Title: | [T Lake 1200-yr Reconstruction] - Record of abundance and δ2H of dinosterol in down core lake sediments from T Lake, Palau collected in September 2013 (Do Parallel Patterns Arise from Parallel Processes?) 
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| Institution: | BCO-DMO (Dataset ID: bcodmo_dataset_771344) |
| Information: | Summary
| License
| ISO 19115
| Metadata
| Background
| Data Access Form
| Files
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![[The graph you specified. Please be patient.]](https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_771344.png?depth_cm,age_ybp&.draw=markers&.marker=5%7C5&.color=0x000000&.colorBar=%7C%7C%7C%7C%7C&.bgColor=0xffccccff)
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Attributes {
s {
depth_cm {
Int16 _FillValue 32767;
Int16 actual_range 85, 1240;
String bcodmo_name "depth_core";
Float64 colorBarMaximum 8000.0;
Float64 colorBarMinimum -8000.0;
String colorBarPalette "TopographyDepth";
String description "composite depth, top of 1cm sampling interval";
String long_name "Depth";
String standard_name "depth";
String units "centimeters (cm)";
}
age_ybp {
Int16 _FillValue 32767;
Int16 actual_range 177, 10432;
String bcodmo_name "age";
String description "linear interpolation of PTLN_PC1_chron via CLAM 2.2";
String long_name "Age Ybp";
String units "years before present (yr bp)";
}
conc_dino {
Float32 _FillValue NaN;
Float32 actual_range 0.4, 44.8;
String bcodmo_name "density";
String description "dry bulk sediment density";
String long_name "Conc Dino";
String units "grams per cubic centimeter (g cm-3)";
}
dbd {
Float32 _FillValue NaN;
Float32 actual_range 0.442, 1.906;
String bcodmo_name "Sed_dinosterol";
String description "dinosterol per gram dry sediment";
String long_name "DBD";
String units "micrograms (ug)";
}
flux_dino {
Float32 _FillValue NaN;
Float32 actual_range 0.1, 10.5;
String bcodmo_name "Sed_Lipids";
String description "dinosterol per square centimeter per year";
String long_name "Flux Dino";
String units "micrograms per square centimeter per year (ug cm-2 yr-1)";
}
dino_2H {
Int16 _FillValue 32767;
Int16 actual_range -325, 999;
String bcodmo_name "d2H";
String description "delta 2H (d2h) of dinosterol vs. SMOW";
String long_name "Dino 2 H";
String units "per mil (‰)";
}
dino_2H_1sig {
Float32 _FillValue NaN;
Float32 actual_range 0.6, 999.0;
String bcodmo_name "d2H";
String description "1 standard deviation of replicate analyses of 2H_dino";
String long_name "Dino 2 H 1sig";
String units "per mil (‰)";
}
}
NC_GLOBAL {
String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv";
String acquisition_description
"Methods are as per \\\"Southward Shift of the Pacific ITCZ During the Holocene\\\"
in Paleoceanography and Paleoclimatology, volume 33, pages 1383-1395 (Sachs et
al. 2018).
Sediment core PTLN\\u2010PC1 was collected September 2013 in sequential 1m
sections using a 5cm\\u2010diameter Colinvaux\\u2010Vohnout
Livingstone\\u2010type rod\\u2010operated piston corer (Geocore, Columbus,
Ohio). Each section was sealed in the field and refrigerated at 4 \\u00b0C
until core splitting and subsampling.
Sample ages were linearly interpolated from calibrated 14C dates (see dataset
\\\"T Lake PC1 Chronology\\\") using the Clam 2.2 (Blaauw, 2010) software package.
Sediment subsamples were transferred to combusted glass vials, frozen, then
freeze dried. Lipids were extracted with 10% methanol in dichloromethane on an
accelerated solvent extractor (ASE 200; Dionex) at 100\\u00b0C and 1500 psi
with three 5\\u2010min static cycles. Lipid extracts were saponified using 2:1
1N KOH in methanol:water at 70\\u00b0C overnight. Saponified extracts were
acidified to pH ~1 with HCl, neutral lipids extracted from the water/methanol
phase with hexane, and the hexane extracts washed with water. Lipid extracts
were acetylated at 70\\u00b0C for 30 min in a mixture of 20 \\u03bcl acetic
anhydride of known isotopic composition and 20 \\u03bcl pyridine. Sterol
acetates were then isolated via preparative high\\u2010performance liquid
chromatography as per the methods in Nelson and Sachs (2013, 2014). Extracts
were taken up in 25 \\u03bcl of 2:1 dichloromethane:methanol and the complete
volume injected onto an Agilent 1100 high\\u2010performance liquid
chromatography system equipped with a Zorbax Eclipse XDB C18 column; after an
initial elution of polar compounds in 5:95 methanol:acetonitrile, sterol
acetates were eluted with an isocratic mobile phase of 5:10:85 methanol:ethyl
acetate:acetonitrile. Aliquots (5%) of each sample were injected on an Agilent
6890N GC with flame ionization detector and PTV inlet, equipped with an
Agilent VF\\u201017 ms column (60 m \\u00d7 0.32 mm \\u00d7 0.25 \\u03bcm), in
splitless mode at 300\\u00b0C using helium carrier gas at 1.5 ml/min. The
initial oven temperature was 110\\u00b0C, followed by a ramp to 320\\u00b0C at
5\\u00b0C/min, and was then held for 20 min. Detector response was determined
via an \\u03b1\\u2010cholestane internal standard. Dinosterol fluxes were
calculated from the product of dinosterol concentration per gram dry weight of
sediment, the linear sediment accumulation rate, and the dry bulk density of
sediment. Uncertainty in dinosterol fluxes is conservatively assumed to be
25%.
Hydrogen isotopes of dinosterol were measured via a modification of the
procedures outlined in Nelson and Sachs (2013). Gas chromatography was
conducted using a Thermo Trace GC Ultra equipped with a GC\\u2010TC interface.
Samples were injected into the 330\\u00b0C inlet in splitless mode, with a 1.1
ml/min helium carrier flow through a VF\\u201017 ms column (60 m \\u00d7 0.25 mm
\\u00d7 0.25 \\u03bcm). The oven temperature was held at 120\\u00b0C for the
2\\u2010min splitless time, increased to 260 \\u00b0C at 20 \\u00b0C/min,
increased to 325\\u00b0C at 1\\u00b0C/min, and held for 10 min. The pyrolysis
interface was operated at 1400\\u00b0C, and the sample hydrogen admitted to a
Thermo Delta V Plus isotope ratio mass spectrometer via open split.
Isotope measurements are given as \\u03b4\\u00b2>H values relative to Vienna
Standard Mean Ocean Water and calibrated via external isotope standards (Arndt
Schimmelmann, Indiana University). Secondary corrections were determined based
on time\\u2010in\\u2010sequence, retention time, and peak area, as necessary, on
a sequence\\u2010by\\u2010sequence basis. Each sample analyzed at least three
times. \\u03b4\\u00b2H values were corrected for added acetate hydrogen
(\\u2212124.4\\u2030 \\u00b1 8.1) via mass balance. Uncertainty is given as the
standard deviation of these replicate analyses and uncertainty in the value of
the known acetate, propagated through the mass balance calculation.";
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 awards_1_award_nid "55104";
String awards_1_award_number "OCE-1241247";
String awards_1_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1241247";
String awards_1_funder_name "NSF Division of Ocean Sciences";
String awards_1_funding_acronym "NSF OCE";
String awards_1_funding_source_nid "355";
String awards_1_program_manager "David L. Garrison";
String awards_1_program_manager_nid "50534";
String cdm_data_type "Other";
String comment
"Abundance and d2H of dinosterol in down core lake sediments from T Lake, Palau
PI: Julian P. Sachs (University of Washington)
Co-PI: Michael Dawson (UC Merced)
Version date: 19-June-2019";
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 "2019-06-19T19:31:14Z";
String date_modified "2019-06-24T17:25:13Z";
String defaultDataQuery "&time<now";
String doi "10.1575/1912/bco-dmo.771344.1";
String history
"2024-11-14T03:39:26Z (local files)
2024-11-14T03:39:26Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_771344.das";
String infoUrl "https://www.bco-dmo.org/dataset/771344";
String institution "BCO-DMO";
String instruments_0_acronym "IR Mass Spec";
String instruments_0_dataset_instrument_description "Delta V Plus IRMS (Thermo). Isotope ratio mass spectrometer with continuous flow inlet, interfaced to open split in GC-TC interface.";
String instruments_0_dataset_instrument_nid "771407";
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 "Delta V Plus IRMS (Thermo)";
String instruments_1_acronym "HPLC";
String instruments_1_dataset_instrument_description "1100 HPLC system (Agilent). High performance liquid chromatograph, equipped with fraction collector for preparative separations.";
String instruments_1_dataset_instrument_nid "771404";
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 "1100 HPLC system (Agilent)";
String instruments_2_acronym "Piston Corer";
String instruments_2_dataset_instrument_description "Colinvaux‐Vohnout Livingstone‐type rod‐operated piston corer (Geocore, Columbus, Ohio). Hand-operated sediment coring device.";
String instruments_2_dataset_instrument_nid "771403";
String instruments_2_description "The piston corer is a type of bottom sediment sampling device. A long, heavy tube is plunged into the seafloor to extract samples of mud sediment. A piston corer uses a \"free fall\" of the coring rig to achieve a greater initial force on impact than gravity coring. A sliding piston inside the core barrel reduces inside wall friction with the sediment and helps to evacuate displaced water from the top of the corer. A piston corer is capable of extracting core samples up to 90 feet in length.";
String instruments_2_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/51/";
String instruments_2_instrument_name "Piston Corer";
String instruments_2_instrument_nid "519";
String instruments_2_supplied_name "Colinvaux‐Vohnout Livingstone‐type rod‐operated piston corer";
String instruments_3_acronym "Gas Chromatograph";
String instruments_3_dataset_instrument_description "6890N GC (Agilent). Gas chromatograph equipped with flame ionization detector and PTV (programmable temperature volatilization) inlet.";
String instruments_3_dataset_instrument_nid "771405";
String instruments_3_description "Instrument separating gases, volatile substances, or substances dissolved in a volatile solvent by transporting an inert gas through a column packed with a sorbent to a detector for assay. (from SeaDataNet, BODC)";
String instruments_3_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/LAB02/";
String instruments_3_instrument_name "Gas Chromatograph";
String instruments_3_instrument_nid "661";
String instruments_3_supplied_name "6890N GC (Agilent)";
String instruments_4_acronym "Gas Chromatograph";
String instruments_4_dataset_instrument_description "Trace GC Ultra (Thermo). Gas chromatograph equipped with pyrolysis interface (GC-TC II) and split/splitless inlet.";
String instruments_4_dataset_instrument_nid "771406";
String instruments_4_description "Instrument separating gases, volatile substances, or substances dissolved in a volatile solvent by transporting an inert gas through a column packed with a sorbent to a detector for assay. (from SeaDataNet, BODC)";
String instruments_4_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/LAB02/";
String instruments_4_instrument_name "Gas Chromatograph";
String instruments_4_instrument_nid "661";
String instruments_4_supplied_name "Trace GC Ultra (Thermo)";
String instruments_5_acronym "ASE";
String instruments_5_dataset_instrument_description "ASE 200 Accelerated Solvent Extractor (Dionex). High pressure/temperature solvent extractor.";
String instruments_5_dataset_instrument_nid "771409";
String instruments_5_description "Accelerated solvent extraction (ASE) is a method for extracting various chemicals from a complex solid or semisolid sample matrix. The process uses high temperature and pressure, which results in the extraction taking less time and requiring less solvent, and possibly also giving better analyte recovery, than traditional methods that use less extreme conditions.";
String instruments_5_instrument_name "Accelerated Solvent Extractor";
String instruments_5_instrument_nid "771408";
String instruments_5_supplied_name "ASE 200 Accelerated Solvent Extractor (Dionex)";
String keywords "1sig, age, age_ybp, bco, bco-dmo, biological, chemical, conc, conc_dino, data, dataset, dbd, depth, depth_cm, dino, dino_2H, dino_2H_1sig, dmo, erddap, flux, flux_dino, management, oceanography, office, preliminary, ybp";
String license "https://www.bco-dmo.org/dataset/771344/license";
String metadata_source "https://www.bco-dmo.org/api/dataset/771344";
String param_mapping "{'771344': {}}";
String parameter_source "https://www.bco-dmo.org/mapserver/dataset/771344/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 California-Merced";
String people_1_affiliation_acronym "UC Merced";
String people_1_person_name "Michael N Dawson";
String people_1_person_nid "51577";
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)";
String standard_name_vocabulary "CF Standard Name Table v55";
String summary "Record of abundance and \\u03b42H of dinosterol in down core lake sediments from T Lake, Palau collected in September 2013 using a 5cm\\u2010diameter Colinvaux\\u2010Vohnout Livingstone\\u2010type rod\\u2010operated piston corer.";
String title "[T Lake 1200-yr Reconstruction] - Record of abundance and δ2H of dinosterol in down core lake sediments from T Lake, Palau collected in September 2013 (Do Parallel Patterns Arise from Parallel Processes?)";
String version "1";
String xml_source "osprey2erddap.update_xml() v1.3";
}
}
Data Access Protocol (DAP) and its
selection constraints.
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.