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Dataset Title:  Stress band counts from coral cores taken in the central equatorial Pacific Subscribe RSS
Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_773896)
Range: longitude = -176.6183 to 172.9952°E, latitude = -4.6779 to 6.4°N
Information:  Summary ? | License ? | ISO 19115 | Metadata | Background (external link) | 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 {
  Island {
    String bcodmo_name "site";
    String description "Island of coral sampling";
    String long_name "Island";
    String units "unitless";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 _FillValue NaN;
    Float64 actual_range -4.6779, 6.4;
    String axis "Y";
    String bcodmo_name "latitude";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String description "Latitude - south is negative";
    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 -176.6183, 172.9952;
    String axis "X";
    String bcodmo_name "longitude";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String description "Longitude - west is negative";
    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";
  }
  Stress_Bands {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 88.2;
    String bcodmo_name "unknown";
    String description "Stress bands";
    String long_name "Stress Bands";
    String units "percentage (%)";
  }
  Number_of_Cores {
    Byte _FillValue 127;
    Byte actual_range 2, 17;
    String bcodmo_name "count";
    Float64 colorBarMaximum 100.0;
    Float64 colorBarMinimum 0.0;
    String description "Number of cores";
    String long_name "Number Of Cores";
    String units "unitless";
  }
  Year_Month {
    String bcodmo_name "unknown";
    String description "Year and month of samples  (format: yyyy-mm)";
    String long_name "Year Month";
    String source_name "Year_Month";
    String time_precision "1970-01";
    String units "unitless";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson";
    String acquisition_description 
"These data were published in Mollica\\u00a0et al., 2019
 
All cores were collected and analyzed using the same methods. Only live
colonies were cored, establishing the top age, vertically i.e., parallel to
the upward growth axis, and using either a pneumatic drill fitted with 3-cm
diameter diamond tip coring bit or an hydraulic drill fitted with an 8-cm
diameter bit. Core holes were sealed with a cement cap and underwater epoxy,
secured flush with the colony surface to facilitate overgrowth of tissue and
wound closure (e.g. Matson 2011), a 6 to 36-month process depending on the
rate of coral growth and diameter of core. All cores were first air dried in
the field, then oven dried at 60 \\u00b0C, and CT scanned intact, together with
density standards, on the Siemens Volume Zoom Helical Computerized Tomography
(CT) Scanner at Woods Hole Oceanographic Institution or the Siemens Biograph
mCT scanner at the Biomedical Research Imaging Center (BRIC) at the University
of North Carolina (protocol as per Barkley et al. 2015; DeCarlo et al. 2015).
 
Location: Central Pacific Coral reefs, -5 to 5 latitude, Dongsha Atoll,
Curacao, Barbados, Martinique coral reefs.";
    String awards_0_award_nid "768533";
    String awards_0_award_number "OCE-1737311";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1737311";
    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 "Daniel Thornhill";
    String awards_0_program_manager_nid "722161";
    String cdm_data_type "Other";
    String comment 
"Stress bands 
  PI: Anne Cohen  
  Data Version 1: 2019-08-20";
    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 "2019-07-31T16:33:40Z";
    String date_modified "2019-08-23T21:09:36Z";
    String defaultDataQuery "&time<now";
    String doi "10.1575/1912/bco-dmo.773896.1";
    Float64 Easternmost_Easting 172.9952;
    Float64 geospatial_lat_max 6.4;
    Float64 geospatial_lat_min -4.6779;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max 172.9952;
    Float64 geospatial_lon_min -176.6183;
    String geospatial_lon_units "degrees_east";
    String history 
"2020-10-21T13:38:44Z (local files)
2020-10-21T13:38:44Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_773896.das";
    String infoUrl "https://www.bco-dmo.org/dataset/773896";
    String institution "BCO-DMO";
    String instruments_0_acronym "CT Scanner";
    String instruments_0_dataset_instrument_nid "775731";
    String instruments_0_description "A CT scan makes use of computer-processed combinations of many X-ray measurements taken from different angles to produce cross-sectional (tomographic) images (virtual \"slices\") of specific areas of a scanned object.";
    String instruments_0_instrument_name "Computerized Tomography (CT) Scanner";
    String instruments_0_instrument_nid "707113";
    String keywords "bands, bco, bco-dmo, biological, chemical, cores, data, dataset, dmo, erddap, island, latitude, longitude, management, month, number, Number_of_Cores, oceanography, office, preliminary, stress, Stress_Bands, time, year";
    String license "https://www.bco-dmo.org/dataset/773896/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/773896";
    Float64 Northernmost_Northing 6.4;
    String param_mapping "{'773896': {'Latitude': 'flag - latitude', 'Longitude': 'flag - longitude'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/773896/parameters";
    String people_0_affiliation "Woods Hole Oceanographic Institution";
    String people_0_affiliation_acronym "WHOI";
    String people_0_person_name "Anne L Cohen";
    String people_0_person_nid "51428";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "Woods Hole Oceanographic Institution";
    String people_1_affiliation_acronym "WHOI";
    String people_1_person_name "Nathaniel Mollica";
    String people_1_person_nid "773912";
    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 "Karen Soenen";
    String people_2_person_nid "748773";
    String people_2_role "BCO-DMO Data Manager";
    String people_2_role_type "related";
    String project "Coral Bleaching Skeletal Records";
    String projects_0_acronym "Coral Bleaching Skeletal Records";
    String projects_0_description 
"NSF abstract:
Ocean warming kills corals and efforts are underway to identify and protect coral reefs that may withstand the projected 21st century rise in tropical ocean temperatures. Coral reefs in the central equatorial Pacific (CEP) have been exposed to episodes of extreme warmth every 3-7 years for centuries, if not millennia, yet remain highly productive ecosystems. Initial data obtained by the investigator from stress signatures archived in the skeletons of long lived coral species, suggests that CEP reefs lose their symbiotic algae or bleach, sometimes severely, during warm episodes. The observation that CEP reefs bleach repetitively yet remain productive implies uncommon resilience to ocean warming. The investigator will use laboratory experiments and field observations to validate skeletal records of historical bleaching. A successful outcome will provide novel and valuable insights into the resilience of the CEP reefs and a new tool with which to identify thermally tolerant coral reef ecosystems across the tropics. Additionally, this project includes mentorship of a postdoc and six undergraduate or high school students, outreach through presentations and media, and expansion of publically available software for coral stress band analysis.
Ocean warming projections indicate severe impacts to coral reefs will occur on an annual basis within the next few decades. Consequently, a coordinated effort is underway to identify reefs that might survive these changes. The investigator will test the hypothesis that such reefs exist at the epicenter of influence of the El Niño-Southern Oscillation (ENSO), where strong inter-annual temperature variability creates conditions conducive for the development of thermal resilience. The project uses laboratory-based bleaching experiments and actual stress signatures accreted by wild corals during the 2015 El Niño to validate signatures of historical bleaching archived in the skeletons of massive reef building corals. In addition the investigator will use new, long cores from the CEP to build a robust dataset of historical bleaching back to the 1800's. A successful outcome will increase confidence in the interpretation of skeletal stress bands as quantitative bleaching proxies and enable the reconstruction of the history of coral reef bleaching and recovery in the CEP.";
    String projects_0_end_date "2020-07";
    String projects_0_geolocation "Central Equatorial Pacific";
    String projects_0_name "Skeletal Records of Coral Reef Bleaching in the Central Equatorial Pacific";
    String projects_0_project_nid "768534";
    String projects_0_start_date "2017-08";
    String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
    String publisher_type "institution";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing -4.6779;
    String standard_name_vocabulary "CF Standard Name Table v55";
    String summary "Coral cores were collected in the central equatorial Pacific (Central Pacific Coral reefs, -5 to 5 latitude, Dongsha Atoll, Curacao, Barbados, Martinique coral reefs) between March 1982 and June 2015. Stress bands were identified in the CT scan images of each core and quantified.";
    String title "Stress band counts from coral cores taken in the central equatorial Pacific";
    String version "1";
    Float64 Westernmost_Easting -176.6183;
    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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