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Dataset Title:  Sediment cores (Wood Fall project) Subscribe RSS
Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_714506)
Range: depth = 1419.0 to 2180.0m
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 {
  rov_dive {
    String bcodmo_name "dive_id";
    String description "Number and letter designation of ROV and dive number for deployment.  GE refers to Oceaneering's Global Explorer.  NA designates no ROV used.";
    String long_name "Rov Dive";
    String units "dimensionless";
  }
  site {
    String bcodmo_name "site";
    String description "Number and letter designation of ROV and dive number for deployment.  GE refers to Oceaneering's Global Explorer.  NA designates no ROV used.";
    String long_name "Site";
    String units "dimensionless";
  }
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    Float64 _FillValue NaN;
    Float64 actual_range 1419.0, 2180.0;
    String axis "Z";
    String bcodmo_name "depth";
    Float64 colorBarMaximum 8000.0;
    Float64 colorBarMinimum -8000.0;
    String colorBarPalette "TopographyDepth";
    String description "Depth of coring site in meters";
    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";
  }
  core_no {
    String bcodmo_name "sample_descrip";
    String description "Number designation of core tube";
    String long_name "Core No";
    String units "dimensionless";
  }
  date {
    String bcodmo_name "date";
    String description "Date of core collection in the format YYYY-MM-DD";
    String long_name "Date";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/ADATAA01/";
    String source_name "date";
    String time_precision "1970-01-01";
    String units "unitless";
  }
  experiment {
    String bcodmo_name "exp_type";
    String description "Type of experiment the cores were taken for.  wf background is for wood-fall deployment background macrofaunal analysis.  patch mosaic is for analyzing fine-scale turnover in composition.  DWH impacts refers to cores taken around the Deep-Water Horizon well head and rig site.";
    String long_name "Experiment";
    String units "dimensionless";
  }
  sorter {
    String bcodmo_name "sample_descrip";
    String description "Sorter is the person who sorted macrofaunal from core sample.  Gholson is Sara Gholson an undergraduate REU student in the summer of 2017.  Landry is Chase Landry undergraduate researcher from Nicholls/Fletcher.";
    String long_name "Sorter";
    String units "dimensionless";
  }
  date_sorted {
    String bcodmo_name "date";
    String description "Date when macrofaunal sorting was finished from the core. in the format YYYY-MM-DD.";
    String long_name "Date Sorted";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/ADATAA01/";
    String units "unitless";
  }
  core_type {
    String bcodmo_name "sample_descrip";
    String description "Core type used from the ROV.  Okeanos cores were rented from Okeanus Science and Technology in Houma, LA and were 9.575 cm in diameter.";
    String long_name "Core Type";
    String units "dimensionless";
  }
  core_id {
    String bcodmo_name "sample_descrip";
    String description "Combination identifier of rov dive and core number. Used to link to other sheets.";
    String long_name "Core Id";
    String units "dimensionless";
  }
  group_number {
    Byte _FillValue 127;
    Byte actual_range 1, 3;
    String bcodmo_name "sample_descrip";
    Float64 colorBarMaximum 100.0;
    Float64 colorBarMinimum 0.0;
    String description "Designates which clusters the cores were taken in";
    String long_name "Group Number";
    String units "dimensionless";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv";
    String acquisition_description 
"See description of ROV coring method in the related publications.
 
\\u00a0";
    String awards_0_award_nid "713951";
    String awards_0_award_number "OCE-1634586";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1634586";
    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 "Michael E. Sieracki";
    String awards_0_program_manager_nid "50446";
    String cdm_data_type "Other";
    String comment 
"Information for sediment cores collected by ROV Global Explorer on PE17_22 (Wood Fall project) 
   PIs: Craig R. MCClain (LUMCON) and Seth D. Newsome (UNM) 
   Contact: Clifton C. Nunnally (LUMCON) 
   Version: 2017-09-15 
  
   All missing data denoted with nd.  NA refers to a data field that is not applicable.";
    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 "2017-09-08T19:44:02Z";
    String date_modified "2019-06-12T17:17:04Z";
    String defaultDataQuery "&time<now";
    String doi "10.1575/1912/bco-dmo.714506.1";
    Float64 geospatial_vertical_max 2180.0;
    Float64 geospatial_vertical_min 1419.0;
    String geospatial_vertical_positive "down";
    String geospatial_vertical_units "m";
    String history 
"2020-12-04T07:25:20Z (local files)
2020-12-04T07:25:20Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_714506.das";
    String infoUrl "https://www.bco-dmo.org/dataset/714506";
    String institution "BCO-DMO";
    String instruments_0_dataset_instrument_nid "714509";
    String instruments_0_instrument_name "ROV Global Explorer";
    String instruments_0_instrument_nid "714229";
    String instruments_1_dataset_instrument_description "Elevator used was a aluminum work basket suspended from the vessel’s winch. The elevator was special build for PI McClain by Theriot Machine Works (Chauvin, LA). The basket is rectangular in shape with an A-frame frame pick point and 2 independent doors on either side of A-frame.  Total length is 1.96 meters, width of basket is 1.33 meters and height of basket enclosure is 0.96 meters.  Maximum height at pick point is 1.85 meters.  The basket lids on either side of the a-frame swivel on dual hinges and open fully to touch the a-frame where they are held in place by attached magnetic strips.  Each lid has a width of 1.25 meters and a depth of 0.765 meters.";
    String instruments_1_dataset_instrument_nid "716633";
    String instruments_1_description "A platform used to carry equipment and sampled from the surface to the seafloor and back up again.";
    String instruments_1_instrument_name "Benthic elevator";
    String instruments_1_instrument_nid "714940";
    String instruments_1_supplied_name "McClain benthic elevator";
    String keywords "bco, bco-dmo, biological, chemical, core, core_id, core_no, core_type, data, dataset, date, date_sorted, depth, dive, dmo, erddap, experiment, group, group_number, management, number, oceanography, office, operated, preliminary, remotely, rov, rov_dive, site, sorted, sorter, time, type, vessel";
    String license "https://www.bco-dmo.org/dataset/714506/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/714506";
    String param_mapping "{'714506': {'depth': 'master - depth'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/714506/parameters";
    String people_0_affiliation "Louisiana Universities Marine Consortium";
    String people_0_affiliation_acronym "LUMCON";
    String people_0_person_name "Dr Craig McClain";
    String people_0_person_nid "713955";
    String people_0_role "Lead Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "University of New Mexico";
    String people_1_affiliation_acronym "UNM";
    String people_1_person_name "Dr Seth D. Newsome";
    String people_1_person_nid "713957";
    String people_1_role "Co-Principal Investigator";
    String people_1_role_type "originator";
    String people_2_affiliation "Louisiana Universities Marine Consortium";
    String people_2_affiliation_acronym "LUMCON";
    String people_2_person_name "Dr Clifton C. Nunnally";
    String people_2_person_nid "713960";
    String people_2_role "Contact";
    String people_2_role_type "related";
    String people_3_affiliation "Woods Hole Oceanographic Institution";
    String people_3_affiliation_acronym "WHOI BCO-DMO";
    String people_3_person_name "Megan Switzer";
    String people_3_person_nid "708683";
    String people_3_role "BCO-DMO Data Manager";
    String people_3_role_type "related";
    String project "Wood Fall";
    String projects_0_acronym "Wood Fall";
    String projects_0_description 
"Changes in both terrestrial and marine carbon production under climate change necessitate an understanding of how ecological communities are structured by carbon availability, which has long been recognized as a predictor of biodiversity. Recent research indicates global marine phytoplankton production may have declined at a rate of ~1% of the global median per year. Regional-scale changes have been more heterogeneous; with the equatorial Pacific Ocean experiencing overall declines of over 50% the last decade and Polar Regions experiencing increases of comparable magnitude. Clearly, there is a strong need for a more complete understanding of the relationship between biodiversity and carbon availability to better predict the consequences of current and forthcoming climate change on marine ecosystems. One challenge is that determinants of available carbon in natural systems are diverse and often unidentifiable. Wood-fall communities in the deep sea are an ideal experimental system for testing many theories about carbon availability and biodiversity. First, the amount of carbon available to the community can be precisely manipulated in the form of wood mass. Second, flows of carbon from wood through the community can be easily tracked because animals supported by wood have distinct chemical signatures that can be traced with stable isotope analysis. Finally, the entire community associated with a wood fall can be sampled, allowing for accurate estimates of biodiversity, biomass, and energy flow. For these reasons, study of deep-sea wood falls provides accurate and simultaneous quantification of standing stock, diversity, and trophic structure as a function of energy availability. Through the use of ROV/submersible-deployed wood falls, the project will test how changes in carbon availability impact marine biodiversity. The results of this project will be beneficial to science in several ways. First, the project contributes significantly to climate change and biodiversity research and specifically to knowledge of the underexplored deep oceans. The project also creates abundant opportunities for public outreach. The multifaceted approach includes: employing web podcasts and blogs; sharing results through photographic exhibitions; and actively recruiting from minority-serving institutions while also providing visiting lectureships. Further, the project will recruit and train young scientists in underrepresented groups, and impact multiple audiences from primary education students, science instructors, and the general public.
The goal of this project is to identify the interactions in energetic processes that regulate community structure, using ROV/submersible-deployed wood falls. Wood will be deployed in varying sizes to control the amount of chemical energy added to the community, and of different wood densities to examine assembly rules while examining total quantity and concentration of resources. This approach will allow the investigators to examining energetic tradeoffs is that multiple impacts, hypotheses, and theories of varying carbon availability on biodiversity can be evaluated simultaneously. The amount of carbon in the community can be precisely manipulated, an improvement over prior studies. The impact of the rate of carbon uptake on ecological processes will also be examined here, but has been rarely evaluated. This research will also reveal much about wood-fall biomes in the deep sea, one of the least studied systems in the ocean. For example, the project will reveal the relative importance different carbon pathways in exporting wood energy and controlling biodiversity.";
    String projects_0_end_date "2017-08";
    String projects_0_geolocation "Northern Gulf of Mexico Continental Slope";
    String projects_0_name "The energetic assembly of biological communities: a test with deep-sea woodfalls";
    String projects_0_project_nid "713952";
    String projects_0_start_date "2016-10";
    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 subsetVariables "core_type";
    String summary "Sediment cores (Wood Fall project)";
    String title "Sediment cores (Wood Fall project)";
    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
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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