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

ERDDAP > tabledap > Data Access Form ?

Dataset Title:  Annual calcification histories for corals from ten Palau reef sites
representing lagoon and barrier reef environments
Subscribe RSS
Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_707106)
Information:  Summary ? | License ? | ISO 19115 | Metadata | Background (external link) | Files | Make a graph
Variable ?   Optional
Constraint #1 ?
Constraint #2 ?
   Minimum ?
   Maximum ?
 site (unitless) ?          "Mecherchar"    "Uchelbeluu"
 reef_type (unitless) ?          "Barrier"    "Lagoon"
 latitude (degrees_north) ?          7.16    7.822
  < slider >
 longitude (degrees_east) ?          134.22    134.562
  < slider >
 coral_id (unitless) ?          0    978
 year (unitless) ?          1990    2013
 density (grams per square centimeter (g/cm2)) ?          0.668    1.69
 extension (centimeters per year (cm/yr)) ?          0.237    2.032
 calcification (grams per square centimeter per year (g/cm2/yr)) ?          0.22    2.795
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 {
  site {
    String bcodmo_name "site";
    String description "Name of reef site where cores were collected";
    String long_name "Site";
    String units "unitless";
  reef_type {
    String bcodmo_name "site_descrip";
    String description "Reef environment at core collection site (Barrier or Lagoon)";
    String long_name "Reef Type";
    String units "unitless";
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 _FillValue NaN;
    Float64 actual_range 7.16, 7.822;
    String axis "Y";
    String bcodmo_name "latitude";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String description "Latitude of the reef site; North = positive";
    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 134.22, 134.562;
    String axis "X";
    String bcodmo_name "longitude";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String description "Longitude of the reef site; East = positive";
    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";
  coral_id {
    Int16 _FillValue 32767;
    Int16 actual_range 0, 978;
    String bcodmo_name "sample";
    String description "Unique coral identification number";
    String long_name "Coral Id";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/ACYC/";
    String units "unitless";
  year {
    Int16 _FillValue 32767;
    Int16 actual_range 1990, 2013;
    String bcodmo_name "year";
    String description "Year of growth rate measured";
    String long_name "Year";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/YEARXXXX/";
    String units "unitless";
  density {
    Float32 _FillValue NaN;
    Float32 actual_range 0.668, 1.69;
    String bcodmo_name "density";
    String description "Coral skeletal density";
    String long_name "Density";
    String units "grams per square centimeter (g/cm2)";
  extension {
    Float32 _FillValue NaN;
    Float32 actual_range 0.237, 2.032;
    String bcodmo_name "growth";
    String description "Coral annual linear extension rate";
    String long_name "Extension";
    String units "centimeters per year (cm/yr)";
  calcification {
    Float32 _FillValue NaN;
    Float32 actual_range 0.22, 2.795;
    String bcodmo_name "calcification";
    String description "Coral annual calcification rate";
    String long_name "Calcification";
    String units "grams per square centimeter per year (g/cm2/yr)";
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson";
    String acquisition_description 
"Coral skeletal core collection:\\u00a0We collected 101 skeletal cores from
massive Porites coral colonies at ten reef sites representing two major reef
environments, barrier reef and lagoon, the latter including fringing reefs
around the uplifted karst Rock Islands. The two environments are broadly
distinguishable in both physical (flow, temperature, and light regimes) and
chemical (carbon system parameters, salinity) characteristics with generally
higher flow, light, pH, and salinity and lower SST on the barrier reefs
(Shamberger et al. 2014; Barkley et al. 2015).
Skeletal cores (20-40 cm in length) were collected in April 2011, September
2011, April 2012, August 2014, and January 2015 vertically from live coral
colonies at 1-6 m depth using pneumatic drills with 3.8 cm diameter diamond
drill bits. Core holes were filled with cement plugs hammered flush with the
colony surface and sealed with underwater epoxy. Visual inspections of
colonies 6-12 months after coring revealed significant overgrowth of plugs and
no long-term impacts to the corals. Coral cores were oven-dried and scanned
with a Siemens Volume Zoom Helical Computerized Tomography (CT) Scanner at
Woods Hole Oceanographic Institution. 3-D CT scans of coral cores were
analyzed using OsiriX freeware to visualize the 3-D image (Cantin et al. 2010;
Crook et al. 2013) and an automated MATLAB code to quantify skeletal growth
parameters and stress banding (DeCarlo et al. 2015).\\u00a0
Coral calcification histories:\\u00a0Annual calcification rates were calculated
as the product of annual linear extension and density following the automated
procedure described in DeCarlo et al. (2015), which traces density variations
along individual corallites identified within the entire 3-D core. Extension
rates (upward linear growth) were measured between the successive low-density
bands of annual high-low density couplets. Annual density banding was clearly
represented in all cores, with low density bands formed at the beginning of
each year (c. February) and high-density bands accreted toward the mid-to-late
months of the year (c. September). Band identifications were verified using
cross-dating, a dendrochronology technique in which shared years of lower
growth rates are identified and matched across core records (Fritts 1976;
Yamaguchi 1991). Annual skeletal densities were calculated from CT scan
intensities converted to calcium carbonate density values using nine coral
standards (0.81-1.54 g cm-3), where independent measurements of weight and
volume for each standard were used to derive a linear relationship between CT
scan intensity values (in Hounsfield units) and calcium carbonate density (in
g cm-3) (DeCarlo et al. 2015).";
    String awards_0_award_nid "560427";
    String awards_0_award_number "OCE-1031971";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1031971";
    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 
"Annual coral calcification histories 
 PI: Anne Cohen (WHOI) 
 Contact: Hannah Barkley (WHOI) 
 Version: 29 June 2017";
    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 "2017-06-29T19:29:41Z";
    String date_modified "2019-08-02T16:46:33Z";
    String defaultDataQuery "&amp;time&lt;now";
    String doi "10.1575/1912/bco-dmo.707106.1";
    Float64 Easternmost_Easting 134.562;
    Float64 geospatial_lat_max 7.822;
    Float64 geospatial_lat_min 7.16;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max 134.562;
    Float64 geospatial_lon_min 134.22;
    String geospatial_lon_units "degrees_east";
    String history 
"2024-07-19T19:06:52Z (local files)
2024-07-19T19:06:52Z https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_707106.html";
    String infoUrl "https://www.bco-dmo.org/dataset/707106";
    String institution "BCO-DMO";
    String instruments_0_acronym "CT Scanner";
    String instruments_0_dataset_instrument_description "Siemens Volume Zoom Helical Computerized Tomography (CT) Scanner";
    String instruments_0_dataset_instrument_nid "707114";
    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 instruments_0_supplied_name "Siemens Volume Zoom Helical Computerized Tomography (CT) Scanner";
    String keywords "bco, bco-dmo, biological, calcification, chemical, coral, coral_id, data, dataset, density, dmo, erddap, extension, latitude, longitude, management, oceanography, office, preliminary, reef, reef_type, site, type, year";
    String license "https://www.bco-dmo.org/dataset/707106/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/707106";
    Float64 Northernmost_Northing 7.822;
    String param_mapping "{'707106': {'lat': 'master - latitude', 'lon': 'master - longitude'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/707106/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 "Hannah Barkley";
    String people_1_person_nid "560803";
    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 "Thermal Thresholds and Projections";
    String projects_0_acronym "Thermal Thresholds and Projections";
    String projects_0_description 
"Description from NSF award abstract:
Sea surface temperature (SST) across much of the global tropics has increased by 0.5-1 degrees C in the past 4 decades and, with it, the frequency and geographic extent of coral bleaching events and reef mortality. As levels of atmospheric CO2 continue to rise, there is mounting concern that CO2-induced climate change will pose the single greatest threat to the survival of coral reefs. Averaged output of 21 IPCC climate models for a mid-range CO2 emissions scenario predicts that tropical SSTs will increase another 1.5-3 degrees C by the end of this century. Combined with current estimates of thermal thresholds for coral bleaching, the outlook for the future of coral-reef ecosystems, worldwide, appears bleak. There are several key issues that limit accurate predictions of the full and lasting impact of rising SSTs. These include (1) level of confidence in the spatial and temporal patterns of the predicted warming, (2) knowledge of thermal thresholds of different reef-building coral species, and (3) the potential for corals to increase resistance to thermal stress through repeated exposure to high temperature events.
New skeletal markers have been developed that constrain the thermal thresholds and adaptive potential of multiple, individual coral colonies across 3-D space and through time. The method, based on 3-D CAT scan reconstructions of coral skeletons, has generated initial data from two coral species in the Red Sea, Great Barrier Reef and Phoenix Islands. Results showed that large, abrupt declines in skeletal growth occur at thresholds of accumulated heat stress defined by NOAA's Degree Heating Weeks Index (DHWs). In addition, there was a significant correlation between host lipid reserve, an independent measure of stress and mortality risk, and rates of skeletal growth. Because the coral skeleton archives the history of each coral's response to and recovery from successive, documented thermal anomalies, this approach pinpoints the thermal thresholds for sub-lethal impacts, the recovery time (if any) following a return to normal oceanographic conditions, and tests for a dampened response following successive events, indicative of acclimation.
This research program builds on initial work, focusing on method refinement and application to corals on two central Pacific reefs. With contrasting thermal histories, these reefs are considered at greatest risk from future ocean warming. In parallel, new experiments will be run on an ocean general-circulation model (OGCM) that is well suited to the tropical Pacific and of sufficiently high resolution, both horizontal and vertical, to maximize projections of thermal stress on specific central Pacific Reef sites over the next few decades. The OGCM output will also be of sufficient temporal resolution to compute DHWs, thus addressing a major limitation of the direct application of global climate model output (as archived for the IPCC AR4) toward coral-reef studies. Specifically, this study will: (1) collect multiple new, medium-length (15-30 yrs) cores and branches from two dominant reef-building species at 1-30m depth in the Gilbert and Jarvis Islands, central tropical Pacific; (2) apply 3-D CAT scanning and image analysis techniques to quantify systematically thermal thresholds, rates of recovery and resilience for each species, at each reef site and with depth; (3) quantify energetic reserve and symbiont genotype amongst thermally more- and less- resilient colonies, establishing a quantitative link between calcification stress and mortality risk, and determining the physiological basis for calcification responses to thermal stress; (4) use an OGCM specifically tailored to the tropical Pacific to produce a dynamically consistent set of forecasts for near-term climate change at the target reef sites; and (5) combine coral data with model output and refine the projected thermal stress forecast, in degree heating weeks, for corals in this central Pacific Island group over the 21st century.";
    String projects_0_end_date "2014-09";
    String projects_0_name "Constraining Thermal Thresholds and Projections of Temperature Stress on Pacific Coral Reefs Over the 21st Century: Method Refinement and Application";
    String projects_0_project_nid "560428";
    String projects_0_start_date "2010-10";
    String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
    String publisher_type "institution";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 7.16;
    String standard_name_vocabulary "CF Standard Name Table v55";
    String summary "Annual calcification histories for corals from ten Palau reef sites representing lagoon and barrier reef environments.";
    String title "Annual calcification histories for corals from ten Palau reef sites representing lagoon and barrier reef environments";
    String version "1";
    Float64 Westernmost_Easting 134.22;
    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