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Dataset Title:  [Illumina Sequences] - Illumina sequencing data from sediment strata collected
from the cold seeps of Hydrate Ridge, metalliferous sediments of Juan de Fuca
Ridge, and organic-rich hydrothermal sediments of Guaymas Basin (Collaborative
Research: The Role of Iron-oxidizing Bacteria in the Sedimentary Iron Cycle:
Ecological, Physiological and Biogeochemical Implications)
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_747948)
Range: longitude = -128.7086 to -111.4078°E, latitude = 27.0078 to 48.45722°N
Information:  Summary ? | License ? | FGDC | 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 {
  sequence_accession_number {
    String bcodmo_name "accession number";
    String description "NCBI accession number";
    String long_name "Sequence Accession Number";
    String units "unitless";
  }
  link {
    String bcodmo_name "external_link";
    String description "URL to NCBI accession";
    String long_name "Link";
    String units "unitless";
  }
  Species_Names {
    String bcodmo_name "taxon";
    String description "Description/name of species";
    String long_name "Species Names";
    String units "unitless";
  }
  description_of_the_types_of_sequences {
    String bcodmo_name "sample_descrip";
    String description "Description of the type of sequence";
    String long_name "Description Of The Types Of Sequences";
    String units "unitless";
  }
  locations_where_species_were_collected {
    String bcodmo_name "site";
    String description "Location of sample collection";
    String long_name "Locations Where Species Were Collected";
    String units "unitless";
  }
  latitude_dms {
    String bcodmo_name "latitude";
    String description "Latitude of sample collection in degrees, minutes, and seconds";
    String long_name "Latitude";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/LATX/";
    String standard_name "latitude";
    String units "unitless";
  }
  longitude_dms {
    String bcodmo_name "longitude";
    String description "Longitude of sample collection in degrees, minutes, and seconds";
    String long_name "Longitude";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/LONX/";
    String standard_name "longitude";
    String units "unitless";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 _FillValue NaN;
    Float64 actual_range 27.0078, 48.45722;
    String axis "Y";
    String bcodmo_name "latitude";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String description "Latitude of sample collection in decimal degrees; North = positive values";
    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 -128.70861, -111.4078;
    String axis "X";
    String bcodmo_name "longitude";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String description "Longitude of sample collection in degrees, minutes, and seconds; East = positive values";
    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";
  }
  Vessel {
    String bcodmo_name "instrument";
    String description "Name of collection vehicle";
    String long_name "Vessel";
    String units "unitless";
  }
  Dive_number {
    Int16 _FillValue 32767;
    Int16 actual_range 1458, 4625;
    String bcodmo_name "dive_id";
    Float64 colorBarMaximum 100.0;
    Float64 colorBarMinimum 0.0;
    String description "Dive ID number";
    String long_name "Dive Number";
    String units "unitless";
  }
  sequencing_and_analysis_methods {
    String bcodmo_name "sampling_method";
    String description "Description of sequencing and analysis methods";
    String long_name "Sequencing And Analysis Methods";
    String units "unitless";
  }
  instrument_and_model {
    String bcodmo_name "instrument";
    String description "Name of sequencing instruments";
    String long_name "Instrument And Model";
    String units "unitless";
  }
  Analysis_methods {
    String bcodmo_name "sampling_method";
    String description "Description of analysis methods";
    String long_name "Analysis Methods";
    String units "unitless";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson";
    String acquisition_description 
"This study included cold seep and hydrothermal vent sediments from along the
Pacific coast of North America. Sediments were collected via 30 cm long
polycarbonate pushcores from a cold methane seep at Hydrate Ridge
(44\\u00b034'10. 20\\\"N, 125\\u00b0 8'48. 48\\\"W) at 777 m water depth with the
ROV Ropos (Dive 1458); hydrothermal vents at Guaymas Basin, Gulf of California
(27\\u00b00'27.84\\\"N, 111\\u00b024'27.84\\\"W) at 2000 m with the DSV Alvin (Dive
4486); and hydrothermal vents at Middle Valley, Juna de Fuca Ridge
(48\\u00b027'26.40\\\"N, 128\\u00b042'30.60\\\"W) at 2413 m with the DSV Alvin (Dive
4625). For this study, a total of three pushcores were collected from Hydrate
Ridge at 4\\u00b0C, one from Guaymas Basin at 30-35\\u00b0C, and one from Middle
Valley at 5\\u201357\\u00b0C (Table 4.1). Total genomic DNA was extracted using
a phenol-chloroform protocol modified to prevent nucleic acid loss and
eliminate potential inhibitors of downstream PCR, and which has been very
successful in studies of low biomass sediments (Adams et al. 2013). PCR
amplification was performed with primers designed to be universal to both
archaea and bacteria (515F/806R) (Caporaso et al., 2012), containing attached
Illumina adaptors and barcodes (Kozich et al., 2013). All DNA extracts were
amplified in duplicate with OmniTaq (Taq mutant) polymerase according to the
manufacturer\\u2019s instructions (DNA Polymerase Technologies, St. Louis, MO,
USA), with a final concentration of 0.2 \\u03bcM for each primer. For each PCR,
1 \\u03bcL template DNA was added to the final reaction mixture for a final
volume of 50 \\u03bcl. Amplification conditions were as follows: 94\\u00b0C for
3 min to denature DNA; 30 cycles at 94\\u00b0C for 45 s, 50\\u00b0C for 60 s,
and 72\\u00b0C for 60 s; and a final extension of 10 min at 72 \\u00b0C.";
    String awards_0_award_nid "626092";
    String awards_0_award_number "OCE-1459252";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward?AWD_ID=1459252";
    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 
"Illumina Sequencing From Deep Sea Sediments 
  PI: Peter Girguis (Harvard) 
  Contributor: Melissa Adams 
  Version date: 12 October 2018";
    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 "2018-10-12T18:57:48Z";
    String date_modified "2019-03-15T18:04:04Z";
    String defaultDataQuery "&time<now";
    String doi "10.1575/1912/bco-dmo.747948.1";
    Float64 Easternmost_Easting -111.4078;
    Float64 geospatial_lat_max 48.45722;
    Float64 geospatial_lat_min 27.0078;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -111.4078;
    Float64 geospatial_lon_min -128.70861;
    String geospatial_lon_units "degrees_east";
    String history 
"2024-11-08T06:13:21Z (local files)
2024-11-08T06:13:21Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_747948.das";
    String infoUrl "https://www.bco-dmo.org/dataset/747948";
    String institution "BCO-DMO";
    String instruments_0_acronym "Thermal Cycler";
    String instruments_0_dataset_instrument_nid "747953";
    String instruments_0_description 
"General term for a laboratory apparatus commonly used for performing polymerase chain reaction (PCR). The device has a thermal block with holes where tubes with the PCR reaction mixtures can be inserted. The cycler then raises and lowers the temperature of the block in discrete, pre-programmed steps.

(adapted from http://serc.carleton.edu/microbelife/research_methods/genomics/pcr.html)";
    String instruments_0_instrument_name "PCR Thermal Cycler";
    String instruments_0_instrument_nid "471582";
    String keywords "accession, analysis, Analysis_methods, bco, bco-dmo, biological, chemical, collected, data, dataset, description, description_of_the_types_of_sequences, dive, Dive_number, dmo, erddap, instrument, instrument_and_model, latitude, latitude_dms, link, locations, locations_where_species_were_collected, longitude, longitude_dms, management, methods, model, names, number, oceanography, office, preliminary, sequence, sequence_accession_number, sequences, sequencing, sequencing_and_analysis_methods, species, Species_Names, types, vessel, where";
    String license "https://www.bco-dmo.org/dataset/747948/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/747948";
    Float64 Northernmost_Northing 48.45722;
    String param_mapping "{'747948': {'latitude': 'flag - latitude', 'longitude': 'flag - longitude'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/747948/parameters";
    String people_0_affiliation "Harvard University";
    String people_0_person_name "Peter Girguis";
    String people_0_person_nid "544586";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "Harvard University";
    String people_1_person_name "Melissa Adams";
    String people_1_person_nid "747964";
    String people_1_role "Contact";
    String people_1_role_type "related";
    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 "SedimentaryIronCycle";
    String projects_0_acronym "SedimentaryIronCycle";
    String projects_0_description 
"Iron is a critical element for life that serves as an essential trace element for eukaryotic organisms. It is also able to support the growth of a cohort of microbes that can either gain energy for growth via oxidation of ferrous (Fe(II)) to ferric (Fe(III)) iron, or by utilizing Fe(III) for anaerobic respiration coupled to oxidation of simple organic matter or H2. This coupled process is referred to as the microbial iron cycle. One of the primary sources of iron to the ocean comes from dissolved iron (dFe) that is produced through oxidation and reduction processes in the sediment where iron is abundant. The dFe is transported into the overlaying water where it is an essential nutrient for phytoplankton responsible for primary production in the world’s oceans. In fact, iron limitation significantly impacts production in as much as a third of the world’s open oceans. The basic geochemistry of this process is understood; however important gaps exist in our knowledge about the details of how the iron cycle works, and how critical a role bacteria play in it.
Intellectual Merit. Conventional wisdom holds that most of the iron oxidation in sediments is abiological, as a result of the rapid kinetics of chemical iron oxidation in the presence of oxygen. This proposal aims to question this conventional view and enhance our understanding of the microbes involved in the sedimentary iron cycle, with an emphasis on the bacteria that catalyze the oxidation of iron. These Fe-oxidizing bacteria (FeOB) utilize iron as a sole energy source for growth, and are autotrophic.  They were only discovered in the ocean about forty-five years ago, and are now known to be abundant at hydrothermal vents that emanate ferrous-rich fluids. More recently, the first evidence was published that they could inhabit coastal sediments, albeit at reduced numbers, and even be abundant in some continental shelf sediments. These habitats are far removed from hydrothermal vents, and reveal the sediments may be an important habitat for FeOB that live on ferrous iron generated in the sediment. This begs the question: are FeOB playing an important role in the oxidative part of the sedimentary Fe-cycle? One important attribute of FeOB is their ability to grow at very low levels of O2, an essential strategy for them to outcompete chemical iron oxidation. How low a level of O2 can sustain them, and how this might affect their distribution in sediments is unknown. In part, this is due to the technical challenges of measuring O2 concentrations and dynamics at very low levels; yet these concentrations could be where FeOB flourish. The central hypothesis of this proposal is that FeOB are more common in marine sedimentary environments than previously recognized, and play a substantive role in governing the iron flux from the sediments into the water column by constraining the release of dFe from sediments. A set of experimental objectives are proposed to test this. A survey of near shore regions in the Gulf of Maine, and a transect along the Monterey Canyon off the coast of California will obtain cores of sedimentary muds and look at the vertical distribution of FeOB and putative Fe-reducing bacteria using sensitive techniques to detect their presence and relative abundance. Some of these same sediments will be used in a novel reactor system that will allow for precise control of O2 levels and iron concentration to measure the dynamics of the iron cycle under different oxygen regimens. Finally pure cultures of FeOB with different O2 affinities will be tested in a bioreactor coupled to a highly sensitive mass spectrometer to determine the lower limits of O2 utilization for different FeOB growing on iron, thus providing mechanistic insight into their activity and distribution in low oxygen environments.
Broader Impacts. An important impact of climate change on marine environments is a predicted increase in low O2 or hypoxic zones in the ocean. Hypoxia in association with marine sediments will have a profound influence on the sedimentary iron cycle, and is likely to lead to greater inputs of dFe into the ocean. In the longer term, this increase in dFe flux could alleviate iron-limitation in some regions of the ocean, thereby enhancing the rate of CO2-fixation and draw down of CO2 from the atmosphere. This is one important reason for developing a better understanding of microbial control of sedimentary iron cycle. This project will also provide training to a postdoctoral scientist, graduate students and undergraduates. This project will contribute to a student initiated exhibit, entitled ‘Iron and the evolution of life on Earth’ at the Harvard Museum of Natural History providing a unique opportunity for undergraduate training and outreach.";
    String projects_0_geolocation "Intertidal coastal river and coastal shelf sediments, mid-coast, Maine, USA; Monteray Bay Canyon, sediments, CA, USA";
    String projects_0_name "Collaborative Research: The Role of Iron-oxidizing Bacteria in the Sedimentary Iron Cycle: Ecological, Physiological and Biogeochemical Implications";
    String projects_0_project_nid "544584";
    String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
    String publisher_type "institution";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 27.0078;
    String standard_name_vocabulary "CF Standard Name Table v55";
    String subsetVariables "Species_Names,description_of_the_types_of_sequences,sequencing_and_analysis_methods,instrument_and_model,Analysis_methods";
    String summary "Illumina sequencing data (NCBI accession numbers) from sediment strata collected from the cold seeps of Hydrate Ridge, metalliferous sediments of Juan de Fuca Ridge, and organic-rich hydrothermal sediments of Guaymas Basin.";
    String title "[Illumina Sequences] - Illumina sequencing data from sediment strata collected from the cold seeps of Hydrate Ridge, metalliferous sediments of Juan de Fuca Ridge, and organic-rich hydrothermal sediments of Guaymas Basin (Collaborative Research: The Role of Iron-oxidizing Bacteria in the Sedimentary Iron Cycle: Ecological, Physiological and Biogeochemical Implications)";
    String version "1";
    Float64 Westernmost_Easting -128.70861;
    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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