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Dataset Title:  Stable isotopes in reactive silica pools of Mississippi River plume sediments
collected aboard the R/V Pelican in May 2017
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_786508)
Information:  Summary ? | License ? | ISO 19115 | Metadata | Background (external link) | Subset | Files | Make a graph
 
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Constraint #1 ?
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Constraint #2 ?
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   or a List of Values ?
   Maximum ?
 
 Cruise_Collected (dimensionless) ?      
   - +  ?
 MultiCore (number/identification) ?          "MC1"    "MC4"
 Station_Number (dimensionless) ?          "A7"    "D5"
 Bottom_Depth (meters) ?          20    47
 latitude (degrees_north) ?          28.49884    28.94688
  < slider >
 longitude (degrees_east) ?          -90.83464    -89.75004
  < slider >
 Date_Collected (unitless) ?          "05.05.2017"    "05.06.2017"
 Time_Collected (HHMM) ?          "18:40"    "20:40"
 Sample_Depth (centimeters) ?          "0-1"    "9-10"
 Nominal_Depth (centimeters) ?          0.5    9.5
 Porewater (uM) ?          39.76    274.4
 Vapor_Phase_Carbonate (%) ?          0.65    6.98
 POC (Particulate Organic Carbon, %) ?          0.77    1.7
 POC_2_Stdev (dimensionless) ?          0.01    0.16
 PON (%) ?          0.06    0.19
 PON_2_Stdev (dimensionless) ?          0.0    0.03
 Reactive_Pool_Treatment (unitless) ?          "Si-Alk"    "T-bSi"
 Avg_d30Si (0/00) ?          -3.32    2.32
 Avg_d30Si_2_Stdev (dimensionless) ?          0.0    0.79
 Avg_Si_Released (umol/g) ?          8.0    1294.3
 Avg_Si_Released_2_Stdev (dimensionless) ?          0.5    380.9
 Mg (ppm) ?          0.0    19791.34
 Al (ppm) ?          247.93    62795.01
 K (ppm) ?          0.0    91645.12
 Ti (ppm) ?          0.0    971.54
 V (ppm) ?          4.46    142.82
 Cr (ppm) ?          0.0    236.79
 Mn (ppm) ?          0.0    1899.04
 Fe (ppm) ?          135.75    39444.31
 Ni (ppm) ?          0.0    125.27
 Cu (ppm) ?          0.0    39.61
 time (ISO Date Time UTC, UTC) ?          2017-05-05T18:40Z    2017-05-06T20:40Z
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The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  Cruise_Collected {
    String bcodmo_name "Cruise Name";
    String description "local name chosen by project investigators for a research expedition on a vessel as opposed to the formal/official cruise ID";
    String long_name "Cruise Collected";
    String units "dimensionless";
  }
  MultiCore {
    String bcodmo_name "core_id";
    String description "core number/identification";
    String long_name "Multi Core";
    String units "number/identification";
  }
  Station_Number {
    String bcodmo_name "station";
    String description "station identifier";
    String long_name "Station Number";
    String units "dimensionless";
  }
  Bottom_Depth {
    Byte _FillValue 127;
    Byte actual_range 20, 47;
    String bcodmo_name "depth_bottom";
    String description "bottom depth in meters";
    String long_name "Bottom Depth";
    String units "meters";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 _FillValue NaN;
    Float64 actual_range 28.49884, 28.94688;
    String axis "Y";
    String bcodmo_name "latitude";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String description "latitude in decimal degrees";
    String ioos_category "Location";
    String long_name "Latitude";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/LATX/";
    String source_name "Latitude_N";
    String standard_name "latitude";
    String units "degrees_north";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float64 _FillValue NaN;
    Float64 actual_range -90.83464, -89.75004;
    String axis "X";
    String bcodmo_name "longitude";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String description "longitude in decimal degrees";
    String ioos_category "Location";
    String long_name "Longitude";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/LONX/";
    String source_name "Longitude_W";
    String standard_name "longitude";
    String units "degrees_east";
  }
  Date_Collected {
    String bcodmo_name "date";
    String description "date when core was collected in the format mmddyyyy";
    String long_name "Date Collected";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/ADATAA01/";
    String units "unitless";
  }
  Time_Collected {
    String bcodmo_name "time";
    String description "time GMT when core was collected";
    String long_name "Time Collected";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/AHMSAA01/";
    String units "HHMM";
  }
  Sample_Depth {
    String bcodmo_name "depth_r";
    String description "subsection used for analysis";
    String long_name "Sample Depth";
    String units "centimeters";
  }
  Nominal_Depth {
    Float32 _FillValue NaN;
    Float32 actual_range 0.5, 9.5;
    String bcodmo_name "depth_core";
    String description "depth used for data plots";
    String long_name "Nominal Depth";
    String units "centimeters";
  }
  Porewater {
    Float32 _FillValue NaN;
    Float32 actual_range 39.76, 274.4;
    String bcodmo_name "unknown";
    String description "concentration of dissolved silica acid Si(OH)4 in porewater collected";
    String long_name "Porewater";
    String units "uM";
  }
  Vapor_Phase_Carbonate {
    Float32 _FillValue NaN;
    Float32 actual_range 0.65, 6.98;
    String bcodmo_name "unknown";
    String description "% of carbonates present in the sediment sample via vapor phase acidification";
    String long_name "Vapor Phase Carbonate";
    String units "%";
  }
  POC {
    Float32 _FillValue NaN;
    Float32 actual_range 0.77, 1.7;
    String bcodmo_name "POC";
    String description "particular organic carbon";
    String long_name "Particulate Organic Carbon";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/CORGCAP1/";
    String units "%";
  }
  POC_2_Stdev {
    Float32 _FillValue NaN;
    Float32 actual_range 0.01, 0.16;
    String bcodmo_name "standard deviation";
    String description "2 standard deviations of sample variation";
    String long_name "POC 2 Stdev";
    String units "dimensionless";
  }
  PON {
    Float32 _FillValue NaN;
    Float32 actual_range 0.06, 0.19;
    String bcodmo_name "PON";
    String description "particular organic nitrogen";
    String long_name "PON";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/MDMAP013/";
    String units "%";
  }
  PON_2_Stdev {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 0.03;
    String bcodmo_name "standard deviation";
    String description "2 standard deviations of sample variation";
    String long_name "PON 2 Stdev";
    String units "dimensionless";
  }
  Reactive_Pool_Treatment {
    String bcodmo_name "treatment";
    String description "which reactive pool the following data is for";
    String long_name "Reactive Pool Treatment";
    String units "unitless";
  }
  Avg_d30Si {
    Float32 _FillValue NaN;
    Float32 actual_range -3.32, 2.32;
    String bcodmo_name "mean";
    String description "Average d30Si (n=3) for each corresponding reactive Si Pool (- per mille)";
    String long_name "Avg D30 Si";
    String units "0/00";
  }
  Avg_d30Si_2_Stdev {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 0.79;
    String bcodmo_name "standard deviation";
    String description "Average d30Si (n=3) for each corresponding reactive Si Pool including 2 standard deviations of sample variation";
    String long_name "Avg D30 Si 2 Stdev";
    String units "dimensionless";
  }
  Avg_Si_Released {
    Float32 _FillValue NaN;
    Float32 actual_range 8.0, 1294.3;
    String bcodmo_name "mean";
    String description "Average Si released (n=3) for each corresponding reactive Si Pool (- micromoles per gram dry sediment)";
    String long_name "Mass Concentration Of Silicate In Sea Water";
    String units "umol/g";
  }
  Avg_Si_Released_2_Stdev {
    Float32 _FillValue NaN;
    Float32 actual_range 0.5, 380.9;
    String bcodmo_name "standard deviation";
    String description "Average Si released (n=3) for each corresponding reactive Si Pool including 2 standard deviations of sample variation";
    String long_name "Mass Concentration Of Silicate In Sea Water";
    String units "dimensionless";
  }
  Mg {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 19791.34;
    String bcodmo_name "Mg";
    String description "magnesium concentration for each corresponding reactive Si pool";
    String long_name "MG";
    String units "ppm";
  }
  Al {
    Float32 _FillValue NaN;
    Float32 actual_range 247.93, 62795.01;
    String bcodmo_name "Al";
    String description "aluminum concentration for each corresponding reactive Si pool";
    String long_name "Al";
    String units "ppm";
  }
  K {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 91645.12;
    String bcodmo_name "K";
    String description "potassium concentration for each corresponding reactive Si pool";
    String long_name "K";
    String units "ppm";
  }
  Ti {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 971.54;
    String bcodmo_name "Ti";
    String description "titanium concentration for each corresponding reactive Si pool";
    String long_name "Ti";
    String units "ppm";
  }
  V {
    Float32 _FillValue NaN;
    Float32 actual_range 4.46, 142.82;
    String bcodmo_name "V";
    String description "vanadium concentration for each corresponding reactive Si pool";
    String long_name "V";
    String units "ppm";
  }
  Cr {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 236.79;
    String bcodmo_name "trace_metal_conc";
    String description "chromium concentration for each corresponding reactive Si pool";
    String long_name "CR";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P03/current/C035/";
    String units "ppm";
  }
  Mn {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 1899.04;
    String bcodmo_name "Mn";
    String description "manganese concentration for each corresponding reactive Si pool";
    String long_name "MN";
    String units "ppm";
  }
  Fe {
    Float32 _FillValue NaN;
    Float32 actual_range 135.75, 39444.31;
    String bcodmo_name "Fe";
    String description "iron concentration for each corresponding reactive Si pool";
    String long_name "Fe";
    String units "ppm";
  }
  Ni {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 125.27;
    String bcodmo_name "trace_metal_conc";
    String description "nickel concentration for each corresponding reactive Si pool";
    String long_name "Ni";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P03/current/C035/";
    String units "ppm";
  }
  Cu {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 39.61;
    String bcodmo_name "Cu";
    String description "copper concentration for each corresponding reactive Si pool";
    String long_name "Cu";
    String units "ppm";
  }
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 1.4940096e+9, 1.4941032e+9;
    String axis "T";
    String bcodmo_name "ISO_DateTime_UTC";
    String description "Date/Time (UTC) ISO formatted";
    String ioos_category "Time";
    String long_name "ISO Date Time UTC";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/DTUT8601/";
    String source_name "ISO_DateTime_UTC";
    String standard_name "time";
    String time_origin "01-JAN-1970 00:00:00";
    String time_precision "1970-01-01T00:00Z";
    String units "seconds since 1970-01-01T00:00:00Z";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson,.odvTxt";
    String acquisition_description 
"Stable silicon isotopes (e.g. \\u03b430Si) in sediment biogenic silica (bSi)
are widely used as a paleoproxy for marine silicic acid usage by pelagic
diatoms. Despite the growing body of work that uses bSi \\u03b430Si signals,
there are a lack of \\u03b430Si data on other reactive pools of Si in
sediments. This oversight misses valuable information on early diagenetic
products and potentially biases existing sedimentary bSi \\u03b430Si, which
only quantified bSi fractions not altered by diagenesis. For the first time,
we quantified \\u03b430Si among operationally defined reactive Si pools (using
a pre-leach of mild acid prior to alkaline digestion) in Mississippi River
plume sediments. We compared the \\u03b430Si signal within these reactive Si
pools to a traditional alkaline-only digestion of sedimentary bSi. These data
offer proof of concept that \\u03b430Si is a higher throughput approach for
quantifying isotopic properties among reactive Si pools marine sediments vs.
the more laborious (albeit powerful) examination of natural silicon
radioisotopes in these chemical leaches.
 
Core Sampling
 
Briefly, samples were acquired from the study area using an Ocean Instruments
MC-900 Multi-corer, which preserved the sediment-water interface during
recovery. Overlying bottom water was removed, cores were sectioned into 1cm
slices, homogenized, packed under N2 gas and frozen at -20o C for further
analysis.
 
Operational Definitions
 
Operational reactive Si pools have previously been defined by Rahman et al.
(2016) but for consistency and clarity with previous literature (DeMaster,
1981; Michalopoulos and Aller, 2004; Qin et al., 2012; Wang et al., 2015;
Rahman et al., 2016; Krause et al., 2017) it has been restated here. Therefore
we use the following nomenclature;
 
1\\. Si-HCl: Mild acid-leachable pre-treatment; Highly reactive silica
associated with authigenic clays and metal oxide coatings (Michalopoulos and
Aller, 2004).  
 2. Si-Alk: Mild alkaline-leachable digestion completed after acid
pretreatment; Frees reactive silica associated with the biogenic silica pool
(Michalopoulos and Aller, 2004).  
 3. Si-NaOH: Harsh NaOH digestion done after Si-HCl and Si-Alk (Rahman et
al., 2016; Rahman et al., 2017); Associated with the reactive lithogenic Si
(LSi) pool and the comparatively refractory \\u201cdark bSiO2\\u201d (e.g.
sponge spicules and Rhizaria, Maldonado et al., 2019).  
 4. T-bSi: Following the traditional definition of biogenic silica (DeMaster,
1981), with no acid pre-treatment.
 
Reactive Silica Pools
 
Frozen sediment samples were thawed to room temperature (22o C) and triplicate
~50-100 mg subsamples were immediately weighed into 50 mL polyethylene
centrifuge tubes. Samples were never dried or ground before/during
extractions. Procedural blanks were also prepared in triplicate. Additional
subsamples of sediment were dried at 60o C to obtain correction for water
content.
 
Sequential Extractions
 
The sequential extraction methodology separates silica into operationally
defined pools based on kinetics, reaction conditions and reaction sequence
(DeMaster, 1981; Michalopoulos and Aller, 2004; Rahman et al., 2016).
 
Acid Leachable Silica (Si-HCl)
 
Sediment extractions occurred at room temperature (22o C) using Honeywell
Fluka Trace SELECT 0.1 N HCl for 12 hrs, while keeping particles suspended via
constant motion. Following centrifugation, the Si-HCl leachate was removed and
neutralized. Remaining sediment was rinsed in triplicate with Milli-Q water to
remove any residual acid (Michalopoulos and Aller, 2004). As it had previously
been demonstrated by Rahman et al. (2016) that the rinses contained minor
amounts of Si these rinses were discarded. A weak HCl molarity was purposely
chosen to remove metal coatings, authigenic phases, and activate bSi surfaces
while not affecting the sequential Si-Alk digestion (Michalopoulos and Aller,
2004).
 
Mild Alkaline Leachable Si (Si-Alk)
 
The remaining sediment from the acid pre-treatment was subsequently digested
with 0.1 M Na2CO3 (Fisher Scientific Certified ACS) for 20 mins in a 85o C
water bath. Following the 20 min timepoint, samples were placed on ice and
neutralized to stop the digestion. Following centrifugation, the Si-Alk
leachate was removed and stored for further use. The process was stopped after
20 mins to ensure the absence of lithogenic material (DeMaster, 1981;
Michalopoulos and Aller, 2004) and certify that the clear majority of
solubilized silica present is biogenic. Fresh 0.1 M Na2CO3 was added to the
samples and the digestions were continued for a total of 5 hrs (DeMaster,
1981) to completely remove the bSi phase. Concluding after 5 hrs, samples were
placed on ice and neutralized to stop the digestion. Following centrifugation,
the leachate was removed and discarded. Remaining sediment was rinsed in
triplicate with Milli-Q water to remove any residual Na2CO3 and again the
rinses were discarded.
 
Harsh NaOH Digestion (Si-NaOH)
 
The remaining sediment from the Si-Alk treatment was subsequently digested
with Honeywell Fluka 4 M NaOH for 2 hrs in a 85o C water bath. After 2 hrs,
samples were placed on ice and neutralized to stop the digestion. Following
centrifugation, the Si- NaOH leachate was removed, the remaining sediment was
rinsed with Milli-Q water to remove any residual leachate and this rinse was
added to the Si-NaOH leachate and stored for further analysis (Rahman et al.,
2016).
 
Traditional bSi Digestion (T-bSi)
 
Additionally, a second treatment following the traditional definition of
biogenic silica (DeMaster, 1981), with no acid pre-treatment was used to
derive \\u03b430Si from traditional bSi measurements. New subsamples of
sediment were weighed out. 0.1 M Na2CO3 was added to samples and heated in a
85o C water bath for 20 mins to remove the bSi phase. Following the 20 min
timepoint, samples were placed on ice and neutralized to stop the digestion.
Following centrifugation, leachate was removed and stored for further use.
Similar to the Si-Alk digestions, the process was stopped after 20 mins to
ensure the absence of lithogenic material.
 
A 1 ml aliquot of each resulting liquid (Si-HCl, Si-Alk, Si-NaOH and T-bSi)
was analyzed for dissolved SiOH4 concentration (dSi) as described by
Brzezinski and Nelson (Brzezinski and Nelson, 1986) using the molybdate-blue
method on a Genesys 10S UV-Vis Spectrophotometer. The remaining supernatants
were concentrated via evaporation at 100o C and stored following DeMaster
(1980) in preparation for stable isotope analysis.
 
Stable Isotope Analysis
 
Sample purification and isotope analysis were carried out at the University of
Bristol Isotope Group laboratories. Concentrated sample fluids were purified
via cation ion exchange chromatography (Bio-Rad AG50W-X12, 200-400 mesh cation
exchange resin in H+ form). Purified solutions were analyzed in duplicate for
Si isotopes (28Si, 29Si, 30Si) using a multi collector-inductively coupled
plasma-mass spectrometer (MC-ICP-MS, Finnigan Neptune s/n 1002), equipped with
CETAC PFA spray chamber and PFA nebulizer (100ul/min). A standard-sample-
standard bracketing procedure with Mg doping following Cardinal et al., (2003)
was used to correct for both instrumental mass bias and matrix effects.
Additionally, sample and standard solutions were both doped with 0.1 M H2SO4
(ROMIL UpA) and 1 M HCl (in-house distilled) to reduce any matrix effects from
anion loading and guarantee matrix matching between sample and standard
(Hughes et al., 2011). All isotopic composition results are expressed as
\\u03b430Si, corresponding to the silicon isotopic abundances in samples
relative to the international reference standard NBS-28 (NIST RM8546, purified
quartz sand). Reference standards Diatomite (Reynolds et al., 2007) and LMG08
(sponge) (Hendry et al., 2011) were run in tandem with samples to assess long-
term reproducibility. Average measured values are reported as +1.27 \\u00b1
0.09\\u2030 (n=75) and -3.47 \\u00b1 0.16\\u2030 (n=27) (\\u00b1SD) respectively,
which are well within agreement with published values (Reynolds et al., 2007;
Hendry et al., 2011). All samples and standards are consistent with the
kinetic mass fractionation law (Reynolds et al., 2007) with the \\u03b429Si =
0.518x\\u03b430Si. Procedural blanks were lower than the detection limit and
thus considered negligible on \\u03b430Si of the samples.
 
Major Metal Compositions and Corrections
 
Additional thawed/wet sediment subsamples were used for duplicate sequential
extractions and digestions (Si-HCl, Si-Alk, Si-NaOH and T-bSi) run as
previously described. Supernatants were concentrated via evaporation at 100o C
and fluids were reconstituted in 2% HNO3 (in-house distilled) to determine
major ion concentrations on an Agilent 7700 Series ICP-MS. The instrument was
calibrated using a blank and seven matrix-matched, mixed standards. Internal
standardization during analysis was monitored via the addition of (50 \\u03bcl,
10,000 ppb) 115In and 4Be to all standards and samples. Using Aluminum (Al):Si
corrections (Kamatani and Oku, 2000; Ragueneau et al., 2005), both Si-Alk and
T-bSi \\u03b430Si signals (\\u2030) and mass of Si released (\\u03bcmol/g) were
adjusted for bias from lithogenic material (however, this was more important
for the mass of Si, as isotopic content was derived from 30-minute digestions,
opposed to 5 hour digestions for the former).
 
Organic Matter
 
Sediment total organic carbon (TOC) and total organic nitrogen (TON) content
were analyzed at the Dauphin Island Sea Lab using a Costech elemental
combustion system (4010 ECS) following vapor phase acidification to remove
carbonates. Briefly, dried sediment samples were placed in a glass desiccator
and reacted with reagent-grade 12N HCl vapor for 24 hrs at room temperature.
Samples were then dried at 60o C overnight to remove remaining HCl and water
content before TOC/TON analyses (Yamamuro and Kayanne, 1995).";
    String awards_0_award_nid "712666";
    String awards_0_award_number "OCE-1558957";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1558957";
    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 "Dr Simone Metz";
    String awards_0_program_manager_nid "51479";
    String cdm_data_type "Other";
    String comment 
"Isotope 
  Jeffery W. Krause  
  Data Version 1: 2020-02-04";
    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 "2020-01-08T17:06:48Z";
    String date_modified "2020-03-02T20:28:24Z";
    String defaultDataQuery "&amp;time&lt;now";
    String doi "10.1575/1912/bco-dmo.786508.1";
    Float64 Easternmost_Easting -89.75004;
    Float64 geospatial_lat_max 28.94688;
    Float64 geospatial_lat_min 28.49884;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -89.75004;
    Float64 geospatial_lon_min -90.83464;
    String geospatial_lon_units "degrees_east";
    String history 
"2024-02-28T12:58:26Z (local files)
2024-02-28T12:58:26Z https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_786508.html";
    String infoUrl "https://www.bco-dmo.org/dataset/786508";
    String institution "BCO-DMO";
    String instruments_0_acronym "ICP Mass Spec";
    String instruments_0_dataset_instrument_nid "786513";
    String instruments_0_description "An ICP Mass Spec is an instrument that passes nebulized samples into an inductively-coupled gas plasma (8-10000 K) where they are atomized and ionized. Ions of specific mass-to-charge ratios are quantified in a quadrupole mass spectrometer.";
    String instruments_0_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/LAB15/";
    String instruments_0_instrument_name "Inductively Coupled Plasma Mass Spectrometer";
    String instruments_0_instrument_nid "530";
    String instruments_0_supplied_name "Finnigan Neptune s/n 1002 multi collector-inductively coupled plasma-mass spectrometer";
    String instruments_1_acronym "Spectrophotometer";
    String instruments_1_dataset_instrument_nid "786512";
    String instruments_1_description "An instrument used to measure the relative absorption of electromagnetic radiation of different wavelengths in the near infra-red, visible and ultraviolet wavebands by samples.";
    String instruments_1_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/LAB20/";
    String instruments_1_instrument_name "Spectrophotometer";
    String instruments_1_instrument_nid "707";
    String instruments_1_supplied_name "Genesys 10S UV-Vis Spectrophotometer";
    String instruments_2_acronym "Costech ECS 4010";
    String instruments_2_dataset_instrument_nid "793025";
    String instruments_2_description "The ECS 4010 Nitrogen / Protein Analyzer is an elemental combustion analyser for CHNSO elemental analysis and Nitrogen / Protein determination. The GC oven and separation column have a temperature range of 30-110 degC, with control of +/- 0.1 degC.";
    String instruments_2_instrument_name "Costech International Elemental Combustion System (ECS) 4010";
    String instruments_2_instrument_nid "793023";
    String keywords "average, Avg_d30Si, Avg_d30Si_2_Stdev, Avg_Si_Released, Avg_Si_Released_2_Stdev, bco, bco-dmo, biological, bottom, Bottom_Depth, carbon, carbonate, chemical, chemistry, co3, collected, concentration, core, cruise, Cruise_Collected, d30, data, dataset, date, Date_Collected, depth, deviation, dmo, earth, Earth Science > Oceans > Ocean Chemistry > Silicate, erddap, iso, latitude, longitude, management, mass, mass_concentration_of_silicate_in_sea_water, multi, MultiCore, nominal, Nominal_Depth, number, ocean, oceanography, oceans, office, organic, particulate, phase, poc, POC_2_Stdev, pon, PON_2_Stdev, pool, porewater, preliminary, reactive, Reactive_Pool_Treatment, sample, Sample_Depth, science, sea, seawater, silicate, standard, standard deviation, station, Station_Number, stdev, time, Time_Collected, treatment, v, vapor, Vapor_Phase_Carbonate, water";
    String keywords_vocabulary "GCMD Science Keywords";
    String license "https://www.bco-dmo.org/dataset/786508/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/786508";
    Float64 Northernmost_Northing 28.94688;
    String param_mapping "{'786508': {'Latitude_N': 'master - latitude', 'Longitude_W': 'master - longitude', 'ISO_DateTime_UTC': 'flag - time'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/786508/parameters";
    String people_0_affiliation "Dauphin Island Sea Lab";
    String people_0_affiliation_acronym "DISL";
    String people_0_person_name "Rebecca A. Pickering";
    String people_0_person_nid "786518";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "Dauphin Island Sea Lab";
    String people_1_affiliation_acronym "DISL";
    String people_1_person_name "Jeffrey W Krause";
    String people_1_person_nid "544582";
    String people_1_role "Co-Principal Investigator";
    String people_1_role_type "originator";
    String people_2_affiliation "Louisiana State University";
    String people_2_affiliation_acronym "LSU-DOCS";
    String people_2_person_name "Kanchan Maiti";
    String people_2_person_nid "712671";
    String people_2_role "Co-Principal Investigator";
    String people_2_role_type "originator";
    String people_3_affiliation "Dauphin Island Sea Lab";
    String people_3_affiliation_acronym "DISL";
    String people_3_person_name "Rebecca A. Pickering";
    String people_3_person_nid "786518";
    String people_3_role "Contact";
    String people_3_role_type "related";
    String people_4_affiliation "Woods Hole Oceanographic Institution";
    String people_4_affiliation_acronym "WHOI BCO-DMO";
    String people_4_person_name "Christina Haskins";
    String people_4_person_nid "746212";
    String people_4_role "BCO-DMO Data Manager";
    String people_4_role_type "related";
    String project "CLASiC";
    String projects_0_acronym "CLASiC";
    String projects_0_description 
"NSF Award Abstract:
The Louisiana Shelf system in the northern Gulf of Mexico is fed by the Mississippi River and its many tributaries which contribute large quantities of nutrients from agricultural fertilizer to the region. Input of these nutrients, especially nitrogen, has led to eutrophication. Eutrophication is the process wherein a body of water such as the Louisiana Shelf becomes enriched in dissolved nutrients that increase phytoplankton growth which eventually leads to decreased oxygen levels in bottom waters. This has certainly been observed in this area, and diatoms, a phytoplankton which represents the base of the food chain, have shown variable silicon/nitrogen (Si/N) ratios. Because diatoms create their shells from silicon, their growth is controlled not only by nitrogen inputs but the availability of silicon. Lower Si/N ratios are showing that silicon may be playing an increasingly important role in regulating diatom production in the system. For this reason, a scientist from the University of South Alabama will determine the biogeochemical processes controlling changes in Si/N ratios in the Louisiana Shelf system. One graduate student on their way to a doctorate degree and three undergraduate students will be supported and trained as part of this project. Also, four scholarships for low-income, high school students from Title 1 schools will get to participate in a month-long summer Marine Science course at the Dauphin Island Sea Laboratory and be included in the research project. The study has significant societal benefits given this is an area where $2.4 trillion gross domestic product revenue is tied up in coastal resources. Since diatoms are at the base of the food chain that is the biotic control on said coastal resources, the growth of diatoms in response to eutrophication is important to study.
Eutrophication of the Mississippi River and its tributaries has the potential to alter the biological landscape of the Louisiana Shelf system in the northern Gulf of Mexico by influencing the Si/N ratios below those that are optimal for diatom growth. A scientist from the University of South Alabama believes the observed changes in the Si/N ratio may indicate silicon now plays an important role in regulating diatom production in the system. As such, understanding the biotic and abiotic processes controlling the silicon cycle is crucial because diatoms dominate at the base of the food chain in this highly productive region. The study will focus on following issues: (1) the importance of recycled silicon sources on diatom production; (2) can heavily-silicified diatoms adapt to changing Si/N ratios more effectively than lightly-silicified diatoms; and (3) the role of reverse weathering in sequestering silicon thereby reducing diffusive pore-water transport. To attain these goals, a new analytical approach, the PDMPO method (compound 2-(4-pyridyl)-5-((4-(2-dimethylaminoethylamino-carbamoyl)methoxy)phenyl)oxazole) that quantitatively measures taxa-specific silica production would be used.";
    String projects_0_end_date "2019-03";
    String projects_0_geolocation "Northern Gulf of Mexico, specifically the Louisiana Shelf region dominated by the discharge of the Mississippi River on the western side of the delta";
    String projects_0_name "The biotic and abiotic controls on the Silicon cycle in the northern Gulf of Mexico";
    String projects_0_project_nid "712667";
    String projects_0_start_date "2016-04";
    String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
    String publisher_type "institution";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 28.49884;
    String standard_name_vocabulary "CF Standard Name Table v55";
    String subsetVariables "Cruise_Collected";
    String summary "Stable isotopes in reactive silica pools of Mississippi River plume sediments collected aboard the R/V Pelican in May 2017";
    String time_coverage_end "2017-05-06T20:40Z";
    String time_coverage_start "2017-05-05T18:40Z";
    String title "Stable isotopes in reactive silica pools of Mississippi River plume sediments collected aboard the R/V Pelican in May 2017";
    String version "1";
    Float64 Westernmost_Easting -90.83464;
    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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