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

ERDDAP > tabledap > Data Access Form ?

Dataset Title:  Amino acid compound specific isotope values for particles from R/V Kilo Moana
KM1407 and KM1418 in the Central North Pacific, Station ALOHA, Tropical
Pacific, Feb and Sept. 2014
Subscribe RSS
Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_751313)
Information:  Summary ? | License ? | ISO 19115 | Metadata | Background (external link) | Files | Make a graph
Variable ?   Optional
Constraint #1 ?
Constraint #2 ?
   Minimum ?
   Maximum ?
 Particle_size (microns) ?          "0.7-53 um"    "> 53 um"
 Sample (unitless) ?          "1195L-PC004"    "850N-PC004"
 depth (m) ?          25.0    1195.0
  < slider >
 delta15N (permil) ?          -2.2    7.0
 delta15N_stdev (permil) ?          0.0    2.3
 comment (unitless) ?          "NaN"    "data available for..."
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 info)

(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 {
  Particle_size {
    String bcodmo_name "diameter";
    String description "particle size";
    String long_name "Particle Size";
    String units "microns";
  Sample {
    String bcodmo_name "sample";
    String description "sample identifier";
    String long_name "Sample";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/ACYC/";
    String units "unitless";
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    Float64 _FillValue NaN;
    Float64 actual_range 25.0, 1195.0;
    String axis "Z";
    String bcodmo_name "depth";
    Float64 colorBarMaximum 8000.0;
    Float64 colorBarMinimum -8000.0;
    String colorBarPalette "TopographyDepth";
    String description "sample depth";
    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";
  delta15N {
    Float32 _FillValue NaN;
    Float32 actual_range -2.2, 7.0;
    String bcodmo_name "d15N";
    String description "ratio of tissue 15N:14N isotopes";
    String long_name "Delta15 N";
    String units "permil";
  delta15N_stdev {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 2.3;
    String bcodmo_name "d15N";
    String description "standard deviation of ratio of tissue 15N:14N isotopes";
    String long_name "Delta15 N Stdev";
    String units "permil";
  comment {
    String bcodmo_name "comment";
    String description "comments";
    String long_name "Comment";
    String units "unitless";
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv";
    String acquisition_description 
"Amino acid-specific stable N isotope composition was determined on samples
that were hydrolyzed, derivatized, and analyzed according to Popp et al.
(2007) and Hannides et al. (2009).\\u00a0 Briefly, size-fractioned zooplankton
material and target zooplankton taxa were hydrolyzed using trace metal-grade 6
M HCl and the resulting AAs purified using cation exchange
chromatography.\\u00a0 The samples were then esterified using 4:1
isopropanol:acetyl chloride and derivatized using 3:1 methylene
chloride:trifluoroacetyl anhydride.\\u00a0 The resulting trifluoroacetyl and
isopropyl ester (TFA) derivatives were purified using chloroform extraction
and stored at -20\\u00b0C for up to 1 month before analysis.\\u00a0 This method
yielded information for the following AAs: alanine (Ala), glycine (Gly),
isoleucine (Ile), leucine (Leu), lysine (Lys), methionine (Met), phenylalanine
(Phe), proline (Pro), serine (Ser), threonine (Thr), tyrosine (Tyr), and
valine (Val).\\u00a0 During acid hydrolysis asparagine (Asn) is converted to
aspartic acid (Asp) and glutamine (Gln) is converted to glutamic acid (Glu),
thus we also report information on the combined pools, termed Asx (Asn+Asp)
and Glx (Gln+Glu), respectively.
TFA derivatives of AAs were analyzed for stable N isotope composition (d15NAA
values) following Hannides et al. (2013).\\u00a0 AAs were analyzed using a
Thermo Scientific Delta V Plus IRMS interfaced to a trace gas chromatograph
(GC) fitted with a 60 m BPx5 capillary column through a GC-C III combustion
furnace (980\\u00b0C), reduction furnace (680\\u00b0C) and liquid nitrogen cold
trap. d15NAA values were measured on 3 \\u2013 5 replicate injections with
norleucine and aminoadipic acid with known d15N values as internal reference
materials co-injected on each run.
A composite source d15NAA value was calculated by a weighted averaging a suite
of AAs (e.g., d15NSrc-AA = average of Gly, Lys, Phe, and Ser d15N values).
Weighting was based the analytical uncertainty calculated from at least
triplicate analysis of each sample.";
    String awards_0_award_nid "560590";
    String awards_0_award_number "OCE-1433846";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1433846";
    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 "Donald L. Rice";
    String awards_0_program_manager_nid "51467";
    String cdm_data_type "Other";
    String comment 
"Amino acids isotopes: Particle 15NsrcAA values from Station Aloha.    
   Published as Table S2 in Gloeckler et al (2018) L&O, doi: 10.1002/lno.10762 
   PI: B. Popp (UH) 
   version: 2018-12-05 
     NOTE: Delta15N values are averages weighted by error for glycine, serine, lysine and phenyalanine";
    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 "2018-12-19T21:17:53Z";
    String date_modified "2019-03-18T13:39:15Z";
    String defaultDataQuery "&amp;time&lt;now";
    String doi "10.1575/1912/bco-dmo.751313.1";
    Float64 geospatial_vertical_max 1195.0;
    Float64 geospatial_vertical_min 25.0;
    String geospatial_vertical_positive "down";
    String geospatial_vertical_units "m";
    String history 
"2024-07-19T17:39:07Z (local files)
2024-07-19T17:39:07Z https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_751313.html";
    String infoUrl "https://www.bco-dmo.org/dataset/751313";
    String institution "BCO-DMO";
    String instruments_0_acronym "MLVPump";
    String instruments_0_dataset_instrument_description "Particles were collected using in situ filtration.";
    String instruments_0_dataset_instrument_nid "751336";
    String instruments_0_description "The Large Volume Pumping System-WTS-LV can be one of several different models of Water Transfer Systems (WTS) Large Volume (LV) pumping systems designed and manufactured by McLane Research Labs (Falmouth, MA, USA). The WTS-LV systems are large volume in-situ filtration systems designed to collect sinking particulates. WTS-LV systems are individual in situ, battery-powered, pumping/filtration units that can be deployed at multiple depths per cast to provide information on how particle flux changes with depth. The McLane WTS-LV series of oceanographic pumps draw ambient water through filters and can pump large volumes of seawater during a single cast. The WTS-LV pumps are designed for use from a hydro-wire and employ advanced control algorithms to dynamically optimize flow rates as material accumulates on a filter.";
    String instruments_0_instrument_name "Large Volume Pumping System-WTS-LV";
    String instruments_0_instrument_nid "512";
    String instruments_1_acronym "Gas Chromatograph";
    String instruments_1_dataset_instrument_description "Used to analyze amino acids.";
    String instruments_1_dataset_instrument_nid "751338";
    String instruments_1_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_1_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/LAB02/";
    String instruments_1_instrument_name "Gas Chromatograph";
    String instruments_1_instrument_nid "661";
    String instruments_1_supplied_name "Thermo Scientific Delta V Plus IRMS";
    String instruments_2_acronym "Ion Chromatograph";
    String instruments_2_dataset_instrument_description "Amino acids were purified using cation exchange chromatography.";
    String instruments_2_dataset_instrument_nid "751337";
    String instruments_2_description "Ion chromatography is a form of liquid chromatography that measures concentrations of ionic species by separating them based on their interaction with a resin. Ionic species separate differently depending on species type and size. Ion chromatographs are able to measure concentrations of major anions, such as fluoride, chloride, nitrate, nitrite, and sulfate, as well as major cations such as lithium, sodium, ammonium, potassium, calcium, and magnesium in the parts-per-billion (ppb) range. (from http://serc.carleton.edu/microbelife/research_methods/biogeochemical/ic.html)";
    String instruments_2_instrument_name "Ion Chromatograph";
    String instruments_2_instrument_nid "662";
    String keywords "bco, bco-dmo, biological, chemical, comment, data, dataset, delta15, delta15N, delta15N_stdev, depth, deviation, dmo, erddap, management, oceanography, office, particle, Particle_size, preliminary, sample, size, standard, standard deviation, stdev";
    String license "https://www.bco-dmo.org/dataset/751313/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/751313";
    String param_mapping "{'751313': {'Depth': 'master - depth'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/751313/parameters";
    String people_0_affiliation "University of Hawaii at Manoa";
    String people_0_affiliation_acronym "SOEST";
    String people_0_person_name "Brian N. Popp";
    String people_0_person_nid "51093";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "University of South Carolina at Columbia";
    String people_1_person_name "Claudia R. Benitez-Nelson";
    String people_1_person_nid "51092";
    String people_1_role "Co-Principal Investigator";
    String people_1_role_type "originator";
    String people_2_affiliation "University of Michigan";
    String people_2_person_name "Joel D. Blum";
    String people_2_person_nid "560587";
    String people_2_role "Co-Principal Investigator";
    String people_2_role_type "originator";
    String people_3_affiliation "University of Hawaii at Manoa";
    String people_3_affiliation_acronym "SOEST";
    String people_3_person_name "Jeffrey C. Drazen";
    String people_3_person_nid "491313";
    String people_3_role "Co-Principal Investigator";
    String people_3_role_type "originator";
    String people_4_affiliation "University of Hawaii at Manoa";
    String people_4_affiliation_acronym "SOEST";
    String people_4_person_name "Cecelia Hannides";
    String people_4_person_nid "537126";
    String people_4_role "Co-Principal Investigator";
    String people_4_role_type "originator";
    String people_5_affiliation "University of Hawaii at Manoa";
    String people_5_affiliation_acronym "SOEST";
    String people_5_person_name "Kanesa Seraphin";
    String people_5_person_nid "537131";
    String people_5_role "Co-Principal Investigator";
    String people_5_role_type "originator";
    String people_6_affiliation "Woods Hole Oceanographic Institution";
    String people_6_affiliation_acronym "WHOI BCO-DMO";
    String people_6_person_name "Nancy Copley";
    String people_6_person_nid "50396";
    String people_6_role "BCO-DMO Data Manager";
    String people_6_role_type "related";
    String project "Hg_Biogeochemistry";
    String projects_0_acronym "Hg_Biogeochemistry";
    String projects_0_description 
"NSF award abstract:
Mercury is a pervasive trace element that exists in several states in the marine environment, including monomethylmercury (MMHg), a neurotoxin that bioaccumulates in marine organisms and poses a human health threat. Understanding the fate of mercury in the ocean and resulting impacts on ocean food webs requires understanding the mechanisms controlling the depths at which mercury chemical transformations occur. Preliminary mercury analyses on nine species of marine fish from the North Pacific Ocean indicated that intermediate waters are an important entry point for MMHg into open ocean food webs. To elucidate the process controlling this, researchers will examine mercury dynamics in regions with differing vertical dissolved oxygen profiles, which should influence depths of mercury transformation. Results of the study will aid in a better understanding of the pathways by which mercury enters the marine food chain and can ultimately impact humans. This project will provide training for graduate and undergraduate students, and spread awareness on oceanic mercury through public outreach and informal science programs.
Mercury isotopic variations can provide insight into a wide variety of environmental processes. Isotopic compositions of mercury display mass-dependent fractionation (MDF) during most biotic and abiotic chemical reactions and mass-independent fractionation (MIF) during photochemical radical pair reactions. The unusual combination of MDF and MIF can provide information on reaction pathways and the biogeochemical history of mercury. Results from preliminary research provide strong evidence that net MMHg formation occurred below the surface mixed layer in the pycnocline and suggested that MMHg in low oxygen intermediate waters is an important entry point for mercury into open ocean food webs. These findings highlight the critical need to understand how MMHg levels in marine biota will respond to changes in atmospheric mercury emissions, deposition of inorganic mercury to the surface ocean, and hypothesized future expansion of oxygen minimum zones. Using field collections across ecosystems with contrasting biogeochemistry and mercury isotope fractionation experiments researchers will fill key knowledge gaps in mercury biogeochemistry. Results of the proposed research will enable scientists to assess the biogeochemical controls on where in the water column mercury methylation and demethylation likely occur.
Related background publication with supplemental data section:
Joel D. Blum, Brian N. Popp, Jeffrey C. Drazen, C. Anela Choy & Marcus W. Johnson. 2013. Methylmercury production below the mixed layer in the North Pacific Ocean. Nature Geoscience 6, 879–884. doi:10.1038/ngeo1918";
    String projects_0_end_date "2017-07";
    String projects_0_geolocation "Pacific Subtropical Gyre, Station ALOHA 22.75N 158W; equatorial Pacific (10N 155W, 5N 155W)";
    String projects_0_name "Collaborative Research: Isotopic insights to mercury in marine food webs and how it varies with ocean biogeochemistry";
    String projects_0_project_nid "560580";
    String projects_0_start_date "2014-08";
    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 "This dataset contains amino acid compound specific nitrogen isotope ratios in particles collected during R/V Kilo Moana cruises around Station ALOHA (KM1407 and KM1418). For more information about the ALOHA observatory see: http://aco-ssds.soest.hawaii.edu/. These data were published in Gloeckler et al (2018), Supporting Information file lno10762-sup-0002-suppinfo2.xlsx";
    String title "Amino acid compound specific isotope values for particles from R/V Kilo Moana KM1407 and KM1418 in the Central North Pacific, Station ALOHA, Tropical Pacific, Feb and Sept. 2014";
    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
For example,
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 2.02
Disclaimers | Privacy Policy | Contact