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Dataset Title:  Bleaching and environmental data for global coral reef sites from 1998-2017 Subscribe RSS
Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_773466)
Information:  Summary ? | License ? | ISO 19115 | Metadata | Background (external link) | Files | Make a graph
 
Variable ?   Optional
Constraint #1 ?
Optional
Constraint #2 ?
   Minimum ?
 
   Maximum ?
 
 ID (unitless) ?          97    13077
 latitude (degrees_north) ?          -28.8645    34.09805556
  < slider >
 longitude (degrees_east) ?          -179.8593611    179.9453333
  < slider >
 Ocean (unitless) ?          "Arabian Gulf"    "Red Sea"
 Realm (unitless) ?          "Central Indo-Pacific"    "Western Indo-Pacific"
 Ecoregion (unitless) ?          "Andaman Sea"    "Western Tuamotu Ar..."
 Country_Name (unitless) ?          "Antigua"    "Yemen"
 State_Island_Province (unitless) ?          "ABC Islands"    "Zanzibar"
 City_Town (unitless) ?          "Abricots"    "Zighy"
 City_Town_2 (unitless) ?          "500-1000m from NW ..."    "Zamboanguita"
 City_Town_3 (unitless) ?          "Ai Island"    "near Blue Ribbon E..."
 Date (unitless) ?          "1/1/2006"    "9/9/2017"
 Date2 (unitless) ?          19980823    20171220
 depth (m) ?          0.1    23.0
  < slider >
 Average_Bleaching (percent) ?          0.0    100.0
 ClimSST (Degrees Celsius) ?          262.15    305.91
 Temperature_Kelvin (Kelvin) ?          291.64    306.8
 Temperature_Mean (Degree Celsius) ?          294.3    303.52
 Temperature_Minimum (Degree Celsius) ?          284.54    300.35
 Temperature_Maximum (Degree Celsius) ?          301.25    313.14
 Temperature_Kelvin_Standard_Deviation (Kelvin) ?          0.79    5.82
 Windspeed (meters per hour) ?          0    14
 SSTA (Degree Celsius) ?          -4.26    4.61
 SSTA_Standard_Deviation (Degree Celsius) ?          0.0    2.79
 SSTA_Mean (Degree Celsius) ?          0    0
 SSTA_Minimum (Degree Celsius) ?          -7.31    0.0
 SSTA_Maximum (Degree Celsius) ?          0.0    13.19
 SSTA_Frequency (SSTA per time period) ?          0.0    36.0
 SSTA_Frequency_Standard_Deviation (SSTA per time period) ?          0.0    14.2
 SSTA_FrequencyMax (SSTA per time period) ?          0.0    52.0
 SSTA_FrequencyMean (SSTA per time period) ?          0.0    21.0
 SSTA_DHW (Weeks) ?          0.0    38.45
 SSTA_DHW_Standard_Deviation (Weeks) ?          0.0    21.38
 SSTA_DHWMax (Weeks) ?          0.0    107.22
 SSTA_DHWMean (Weeks) ?          0.0    13.12
 TSA (Degree Celsius) ?          -11.04    4.54
 TSA_Standard_Deviation (Degree Celsius) ?          0.0    5.82
 TSA_Minimum (Degree Celsius) ?          -18.85    0.0
 TSA_Maximum (Degree Celsius) ?          0.0    10.59
 TSA_Mean (Degree Celsius) ?          -7.46    0.0
 TSA_Frequency (TSA per time period) ?          0.0    25.0
 TSA_Frequency_Standard_Deviation (TSA per time period) ?          0.0    13.57
 TSA_FrequencyMax (TSA per time period) ?          0.0    52.0
 TSA_FrequencyMean (TSA per time period) ?          0.0    20.0
 TSA_DHW (Weeks) ?          0.0    37.68
 TSA_DHW_Standard_Deviation (Weeks) ?          0.0    15.21
 TSA_DHWMax (Weeks) ?          0.0    63.47
 TSA_DHWMean (Weeks) ?          0.0    12.66
 
Server-side Functions ?
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The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  ID {
    Int16 _FillValue 32767;
    Int16 actual_range 97, 13077;
    String bcodmo_name "sample";
    String description "Unique identifier for each sampling event";
    String long_name "ID";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/ACYC/";
    String units "unitless";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 _FillValue NaN;
    Float64 actual_range -28.8645, 34.09805556;
    String axis "Y";
    String bcodmo_name "latitude";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String description "Latitude";
    String ioos_category "Location";
    String long_name "Latitude";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/LATX/";
    String source_name "Latitude_Degrees";
    String standard_name "latitude";
    String units "degrees_north";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float64 _FillValue NaN;
    Float64 actual_range -179.8593611, 179.9453333;
    String axis "X";
    String bcodmo_name "longitude";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String description "Longitude";
    String ioos_category "Location";
    String long_name "Longitude";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/LONX/";
    String source_name "Longitude_Degrees";
    String standard_name "longitude";
    String units "degrees_east";
  }
  Ocean {
    String bcodmo_name "site_descrip";
    String description "Name of ocean";
    String long_name "Ocean";
    String units "unitless";
  }
  Realm {
    String bcodmo_name "site_descrip";
    String description "Spalding et al. 2007 Marine Ecoregions of the world shapefiles";
    String long_name "Realm";
    String units "unitless";
  }
  Ecoregion {
    String bcodmo_name "site_descrip";
    String description "JEN Veron et al. 2015 shapefile of coral reef ecoregions";
    String long_name "Ecoregion";
    String units "unitless";
  }
  Country_Name {
    String bcodmo_name "site_descrip";
    String description "Name of country";
    String long_name "Country Name";
    String units "unitless";
  }
  State_Island_Province {
    String bcodmo_name "site_descrip";
    String description "State/island/province name";
    String long_name "State Island Province";
    String units "unitless";
  }
  City_Town {
    String bcodmo_name "site_descrip";
    String description "City/town infomration";
    String long_name "City Town";
    String units "unitless";
  }
  City_Town_2 {
    String bcodmo_name "site_descrip";
    String description "City/town infomration";
    String long_name "City Town 2";
    String units "unitless";
  }
  City_Town_3 {
    String bcodmo_name "site_descrip";
    String description "City/town infomration";
    String long_name "City Town 3";
    String units "unitless";
  }
  Date {
    String bcodmo_name "date";
    String description "Date; format: mm/dd/yyyy";
    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";
  }
  Date2 {
    Int32 _FillValue 2147483647;
    Int32 actual_range 19980823, 20171220;
    String bcodmo_name "date";
    String description "Date formatted as: yyyymmdd";
    String long_name "Date2";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/ADATAA01/";
    String units "unitless";
  }
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    Float64 _FillValue NaN;
    Float64 actual_range 0.1, 23.0;
    String axis "Z";
    String bcodmo_name "depth";
    Float64 colorBarMaximum 8000.0;
    Float64 colorBarMinimum -8000.0;
    String colorBarPalette "TopographyDepth";
    String description "distance from surface to study site";
    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";
  }
  Average_Bleaching {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 100.0;
    String bcodmo_name "bleach_percent";
    String description "an average of four transect segments";
    String long_name "Average Bleaching";
    String units "percent";
  }
  ClimSST {
    Float32 _FillValue NaN;
    Float32 actual_range 262.15, 305.91;
    String bcodmo_name "temp_ss";
    String description "Climatological sea surface temperature (SST) based on weekly SSTs for the study time frame, created using a harmonics approach";
    String long_name "Clim SST";
    String units "Degrees Celsius";
  }
  Temperature_Kelvin {
    Float64 _FillValue NaN;
    Float64 actual_range 291.64, 306.8;
    String bcodmo_name "unknown";
    String description "Temperature in Kelvin";
    String long_name "Temperature Kelvin";
    String units "Kelvin";
  }
  Temperature_Mean {
    Float64 _FillValue NaN;
    Float64 actual_range 294.3, 303.52;
    String bcodmo_name "temperature";
    String description "Mean Temperature";
    String long_name "Temperature Mean";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/TEMPP901/";
    String units "Degree Celsius";
  }
  Temperature_Minimum {
    Float64 _FillValue NaN;
    Float64 actual_range 284.54, 300.35;
    String bcodmo_name "temperature";
    String description "Minimum Temperture";
    String long_name "Temperature Minimum";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/TEMPP901/";
    String units "Degree Celsius";
  }
  Temperature_Maximum {
    Float64 _FillValue NaN;
    Float64 actual_range 301.25, 313.14;
    String bcodmo_name "temperature";
    String description "Maximum Temperature";
    String long_name "Temperature Maximum";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/TEMPP901/";
    String units "Degree Celsius";
  }
  Temperature_Kelvin_Standard_Deviation {
    Float64 _FillValue NaN;
    Float64 actual_range 0.79, 5.82;
    String bcodmo_name "unknown";
    Float64 colorBarMaximum 50.0;
    Float64 colorBarMinimum 0.0;
    String description "Standard deviation of temperature";
    String long_name "Temperature Kelvin Standard Deviation";
    String units "Kelvin";
  }
  Windspeed {
    Byte _FillValue 127;
    Byte actual_range 0, 14;
    String bcodmo_name "wind_speed";
    Float64 colorBarMaximum 15.0;
    Float64 colorBarMinimum 0.0;
    String description "Windspeed";
    String long_name "Wind Speed";
    String units "meters per hour";
  }
  SSTA {
    Float64 _FillValue NaN;
    Float64 actual_range -4.26, 4.61;
    String bcodmo_name "temp_ss";
    String description "Sea Surface Temperature Anomaly: weekly SST minus weekly climatological SST";
    String long_name "SSTA";
    String units "Degree Celsius";
  }
  SSTA_Standard_Deviation {
    Float64 _FillValue NaN;
    Float64 actual_range 0.0, 2.79;
    String bcodmo_name "temp_ss";
    Float64 colorBarMaximum 50.0;
    Float64 colorBarMinimum 0.0;
    String description "The Standard Deviation of weekly SST Anomalies over the entire time period";
    String long_name "SSTA Standard Deviation";
    String units "Degree Celsius";
  }
  SSTA_Mean {
    Byte _FillValue 127;
    Byte actual_range 0, 0;
    String bcodmo_name "temp_ss";
    String description "The mean SSTA over the entire time period";
    String long_name "SSTA Mean";
    String units "Degree Celsius";
  }
  SSTA_Minimum {
    Float64 _FillValue NaN;
    Float64 actual_range -7.31, 0.0;
    String bcodmo_name "temp_ss";
    String description "The minimum SSTA over the entire time period";
    String long_name "SSTA Minimum";
    String units "Degree Celsius";
  }
  SSTA_Maximum {
    Float64 _FillValue NaN;
    Float64 actual_range 0.0, 13.19;
    String bcodmo_name "temp_ss";
    String description "The maximum SSTA over the entire time period";
    String long_name "SSTA Maximum";
    String units "Degree Celsius";
  }
  SSTA_Frequency {
    Float64 _FillValue NaN;
    Float64 actual_range 0.0, 36.0;
    String bcodmo_name "unknown";
    String description "Sea Surface Temperature Anomaly Frequency: number of times over the previous 52 weeks that SSTA >=1 degree C";
    String long_name "SSTA Frequency";
    String units "SSTA per time period";
  }
  SSTA_Frequency_Standard_Deviation {
    Float64 _FillValue NaN;
    Float64 actual_range 0.0, 14.2;
    String bcodmo_name "unknown";
    Float64 colorBarMaximum 50.0;
    Float64 colorBarMinimum 0.0;
    String description "The standard deviation of SSTA_Frequency over the entire time period";
    String long_name "SSTA Frequency Standard Deviation";
    String units "SSTA per time period";
  }
  SSTA_FrequencyMax {
    Float64 _FillValue NaN;
    Float64 actual_range 0.0, 52.0;
    String bcodmo_name "unknown";
    String description "The maximum SSTA_Frequency over the entire time period";
    String long_name "SSTA Frequency Max";
    String units "SSTA per time period";
  }
  SSTA_FrequencyMean {
    Float64 _FillValue NaN;
    Float64 actual_range 0.0, 21.0;
    String bcodmo_name "unknown";
    String description "The mean SSTA_Frequency over the entire time period";
    String long_name "SSTA Frequency Mean";
    String units "SSTA per time period";
  }
  SSTA_DHW {
    Float64 _FillValue NaN;
    Float64 actual_range 0.0, 38.45;
    String bcodmo_name "unknown";
    String description "Sea Surface Temperature Degree Heating Weeks: sum of previous 12 weeks when SSTA>=1 degree C";
    String long_name "SSTA DHW";
    String units "Weeks";
  }
  SSTA_DHW_Standard_Deviation {
    Float64 _FillValue NaN;
    Float64 actual_range 0.0, 21.38;
    String bcodmo_name "unknown";
    Float64 colorBarMaximum 50.0;
    Float64 colorBarMinimum 0.0;
    String description "The standard deviation SSTA_DHW over the entire time period";
    String long_name "SSTA DHW Standard Deviation";
    String units "Weeks";
  }
  SSTA_DHWMax {
    Float64 _FillValue NaN;
    Float64 actual_range 0.0, 107.22;
    String bcodmo_name "unknown";
    String description "The maximum SSTA_DHW over the entire time period";
    String long_name "SSTA DHWMax";
    String units "Weeks";
  }
  SSTA_DHWMean {
    Float64 _FillValue NaN;
    Float64 actual_range 0.0, 13.12;
    String bcodmo_name "unknown";
    String description "The mean SSTA_DHW over the entire time period";
    String long_name "SSTA DHWMean";
    String units "Weeks";
  }
  TSA {
    Float64 _FillValue NaN;
    Float64 actual_range -11.04, 4.54;
    String bcodmo_name "unknown";
    String description "Thermal Stress Anomaly: Weekly sea surface temperature minus the maximum of weekly climatological sea surface temperature";
    String long_name "TSA";
    String units "Degree Celsius";
  }
  TSA_Standard_Deviation {
    Float64 _FillValue NaN;
    Float64 actual_range 0.0, 5.82;
    String bcodmo_name "unknown";
    Float64 colorBarMaximum 50.0;
    Float64 colorBarMinimum 0.0;
    String description "The standard deviation of TSA over the entire time period";
    String long_name "TSA Standard Deviation";
    String units "Degree Celsius";
  }
  TSA_Minimum {
    Float64 _FillValue NaN;
    Float64 actual_range -18.85, 0.0;
    String bcodmo_name "unknown";
    String description "The minimum TSA over the entire time period";
    String long_name "TSA Minimum";
    String units "Degree Celsius";
  }
  TSA_Maximum {
    Float64 _FillValue NaN;
    Float64 actual_range 0.0, 10.59;
    String bcodmo_name "unknown";
    String description "The maximum TSA over the entire time period";
    String long_name "TSA Maximum";
    String units "Degree Celsius";
  }
  TSA_Mean {
    Float64 _FillValue NaN;
    Float64 actual_range -7.46, 0.0;
    String bcodmo_name "unknown";
    String description "The mean TSA over the entire times period";
    String long_name "TSA Mean";
    String units "Degree Celsius";
  }
  TSA_Frequency {
    Float64 _FillValue NaN;
    Float64 actual_range 0.0, 25.0;
    String bcodmo_name "unknown";
    String description "Thermal Stress Anomaly Frequency: number of times over previous 52 weeks that TSA >=1 degree C";
    String long_name "TSA Frequency";
    String units "TSA per time period";
  }
  TSA_Frequency_Standard_Deviation {
    Float64 _FillValue NaN;
    Float64 actual_range 0.0, 13.57;
    String bcodmo_name "unknown";
    Float64 colorBarMaximum 50.0;
    Float64 colorBarMinimum 0.0;
    String description "The standard deviation of frequency of thermal stress anomalies over the entire time period";
    String long_name "TSA Frequency Standard Deviation";
    String units "TSA per time period";
  }
  TSA_FrequencyMax {
    Float64 _FillValue NaN;
    Float64 actual_range 0.0, 52.0;
    String bcodmo_name "unknown";
    String description "The maximum TSA_Frequency over the entire time period";
    String long_name "TSA Frequency Max";
    String units "TSA per time period";
  }
  TSA_FrequencyMean {
    Float64 _FillValue NaN;
    Float64 actual_range 0.0, 20.0;
    String bcodmo_name "unknown";
    String description "The mean TSA_Frequency over the entire time period";
    String long_name "TSA Frequency Mean";
    String units "TSA per time period";
  }
  TSA_DHW {
    Float64 _FillValue NaN;
    Float64 actual_range 0.0, 37.68;
    String bcodmo_name "unknown";
    String description "Thermal Stress Anomaly (TSA) Degree Heating Week (DHW): Sum of previous 12 weeks when TSA >=1 degree C";
    String long_name "TSA DHW";
    String units "Weeks";
  }
  TSA_DHW_Standard_Deviation {
    Float64 _FillValue NaN;
    Float64 actual_range 0.0, 15.21;
    String bcodmo_name "unknown";
    Float64 colorBarMaximum 50.0;
    Float64 colorBarMinimum 0.0;
    String description "The standard deviation of TSA_DHW over the entire time period";
    String long_name "TSA DHW Standard Deviation";
    String units "Weeks";
  }
  TSA_DHWMax {
    Float64 _FillValue NaN;
    Float64 actual_range 0.0, 63.47;
    String bcodmo_name "unknown";
    String description "The maximum TSA_DHW over the entire time period";
    String long_name "TSA DHWMax";
    String units "Weeks";
  }
  TSA_DHWMean {
    Float64 _FillValue NaN;
    Float64 actual_range 0.0, 12.66;
    String bcodmo_name "unknown";
    String description "The mean TSA_DHW over the entire time period";
    String long_name "TSA DHWMean";
    String units "Weeks";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson";
    String acquisition_description 
"The coral bleaching data were composed of the Reef Check dataset
([reefcheck.org](\\\\\"https://reefcheck.org/\\\\\")), collected by a mixture of
professional scientists (56%) and trained and certi\\ufb01ed citizen-scientists
(44%) using a standardized transect protocol. The dataset includes counts of
the number of coral colonies showing bleaching (i.e., the percent of reef
corals that were recorded as bleached), which was classi\\ufb01ed as site-wide
bleaching. We also examined the prevalence of coral bleaching per coral
ecoregion (as de\\ufb01ned by Veron et al. 2015). We used the global Coral Reef
Temperature Anomaly Database (CoRTAD Version 6) from the National Oceanic and
Atmospheric Administration
([www.nodc.noaa.gov/sog/cortad/](\\\\\"https://www.nodc.noaa.gov/sog/cortad/\\\\\"))
to predict coral bleaching prevalence and intensity across reefs worldwide.
All CoRTAD variables were weekly data provided on a grid cell basis, of ~4km
resolution, from 1982 to 2017(Sully 2019).
 
A Pair-wise Pearson's correlation of coef\\ufb01cients was used to determine
which covariates were highly collinear. We used generalized linear mixed
models, within a Bayesian framework, to examine the in\\ufb02uence of the
covariates on coral bleaching. Some sites were repeatedly surveyed and
therefore site was treated as a random effect. Covariates were modeled with
\\ufb02at normal priors. The Bayesian model was implemented in R34 and run
through the rjags package that calls JAGS35, with 3 chains, a burn-in of 4000,
and 5000 iterations (Sully 2019).";
    String awards_0_award_nid "762951";
    String awards_0_award_number "OCE-1829393";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1829393";
    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 
"Bleaching and environmental data for global coral reef sites 
  PI: Robert van Woesik (Florida Institute of Technology) 
  Co-PI: Deron Burkepile (UC Santa Barbara) 
  Version date: 18-July-2019";
    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 "2019-07-18T15:36:50Z";
    String date_modified "2019-12-09T16:11:36Z";
    String defaultDataQuery "&amp;time&lt;now";
    String doi "10.1575/1912/bco-dmo.773466.1";
    Float64 Easternmost_Easting 179.9453333;
    Float64 geospatial_lat_max 34.09805556;
    Float64 geospatial_lat_min -28.8645;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max 179.9453333;
    Float64 geospatial_lon_min -179.8593611;
    String geospatial_lon_units "degrees_east";
    Float64 geospatial_vertical_max 23.0;
    Float64 geospatial_vertical_min 0.1;
    String geospatial_vertical_positive "down";
    String geospatial_vertical_units "m";
    String history 
"2020-07-06T05:31:42Z (local files)
2020-07-06T05:31:42Z https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_773466.html";
    String infoUrl "https://www.bco-dmo.org/dataset/773466";
    String institution "BCO-DMO";
    String keywords "anomaly, atmosphere, atmospheric, average, Average_Bleaching, bco, bco-dmo, biological, bleaching, chemical, city, City_Town, City_Town_2, City_Town_3, clim, ClimSST, country, Country_Name, data, dataset, date, date2, depth, deviation, dhw, dhwmax, dhwmean, dmo, earth, Earth Science > Atmosphere > Atmospheric Winds > Surface Winds, ecoregion, erddap, frequency, island, kelvin, latitude, longitude, management, max, maximum, mean, minimum, name, ocean, oceanography, office, preliminary, province, realm, science, sea, speed, sst, ssta, SSTA_DHW, SSTA_DHW_Standard_Deviation, SSTA_DHWMax, SSTA_DHWMean, SSTA_Frequency, SSTA_Frequency_Standard_Deviation, SSTA_FrequencyMax, SSTA_FrequencyMean, SSTA_Maximum, SSTA_Mean, SSTA_Minimum, SSTA_Standard_Deviation, standard, state, State_Island_Province, surface, temperature, Temperature_Kelvin, Temperature_Kelvin_Standard_Deviation, Temperature_Maximum, Temperature_Mean, Temperature_Minimum, time, town, tsa, TSA_DHW, TSA_DHW_Standard_Deviation, TSA_DHWMax, TSA_DHWMean, TSA_Frequency, TSA_Frequency_Standard_Deviation, TSA_FrequencyMax, TSA_FrequencyMean, TSA_Maximum, TSA_Mean, TSA_Minimum, TSA_Standard_Deviation, wind, wind_speed, winds, Windspeed";
    String keywords_vocabulary "GCMD Science Keywords";
    String license "https://www.bco-dmo.org/dataset/773466/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/773466";
    Float64 Northernmost_Northing 34.09805556;
    String param_mapping "{'773466': {'Depth': 'master - depth', 'Longitude_Degrees': 'flag - longitude', 'Latitude_Degrees': 'flag - latitude'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/773466/parameters";
    String people_0_affiliation "Florida Institute of Technology";
    String people_0_affiliation_acronym "FIT";
    String people_0_person_name "Robert van Woesik";
    String people_0_person_nid "562565";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "University of California-Santa Barbara";
    String people_1_affiliation_acronym "UCSB";
    String people_1_person_name "Deron Burkepile";
    String people_1_person_nid "529592";
    String people_1_role "Co-Principal Investigator";
    String people_1_role_type "originator";
    String people_2_affiliation "Florida Institute of Technology";
    String people_2_affiliation_acronym "FIT";
    String people_2_person_name "Robert van Woesik";
    String people_2_person_nid "562565";
    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 "Shannon Rauch";
    String people_3_person_nid "51498";
    String people_3_role "BCO-DMO Data Manager";
    String people_3_role_type "related";
    String project "Coral Reef Brightspots";
    String projects_0_acronym "Coral Reef Brightspots";
    String projects_0_description 
"NSF Award Abstract:
Coral reefs are one of the world's most diverse ecosystems that provide goods and services, such as fisheries and storm protection, for inhabitants of tropical and subtropical regions. However, the current rapid rate of climate change threatens the existence of coral reefs as they degrade because of thermal-stress events. Consequently, the coverage and coral composition of many coral reefs is changing. Most global models suggest that few if any reef corals will survive beyond the 2.5 degree Celsius temperature rise predicted for the tropical oceans within the next hundred years. Such predictions differ from recent field studies on coral reefs that show pockets where corals do not bleach and die. The disagreement between the global models and field assessments is a consequence of ignoring climate-change refuges; it is critical to locate the climate-change refuges and determine what circumstances are conducive for coral survival. The investigators will examine the global response of coral reefs to thermal stresses over the last two decades, and focus on the 2015-2017 El Nino event, which caused considerable thermal stress and coral bleaching. The investigators ask the question: Where are the coral reef 'bright spots' from the thermal-stress events? 'Bright spots' are considered as places with less than expected bleaching. The team will also assess why some localities are potential 'bright spots'. Identifying coral reef bright spots will help guide future conservation decisions by enabling managers to target reefs with specific characteristics, which could be protected from human encroachment and be designated as potential refuges from coral bleaching as climate change progresses. This project includes training of a post-doctoral fellow and a Ph.D student, and host a coral-bleaching workshop. This study will be of relevance to all persons that live and work near coral reefs. What happens to reef corals has cascading consequences on other reef-associated organisms, and also influences whether reefs can keep up with sea-level rise.
The current rapid rate of climate change threatens the existence of coral reefs as they degrade by thermal-stress events. A glimmer of optimism lies in the observation that thermal stresses vary spatially and temporally across the oceans, with the consequence that coral communities in different geographic regions, and under different local conditions, are likely to inherently differ in their capacity to tolerate thermal stress. One of the most transformative aspects of this work is in analyzing the extent to which the bleaching patterns differed from model predictions. This work will capitalize on the recent progress on Bright-Spots Analysis to assess unexpected outcomes. The investigators will take two approaches. First, the project will use a machine-learning algorithm, boosted regression trees to examine the relationships between coral bleaching and the environmental predictor variables of interest. Second, a series of generalized mixed effects models, within a hierarchical Bayesian framework, will be used to identify where geographically 'bright spots' from thermal stress are located and why some coral reefs are more susceptible to thermal stresses than others.";
    String projects_0_end_date "2021-08";
    String projects_0_geolocation "Global";
    String projects_0_name "Identifying coral reef 'bright spots' from the global 2015-2017 thermal-stress event";
    String projects_0_project_nid "762952";
    String projects_0_start_date "2018-09";
    String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
    String publisher_type "institution";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing -28.8645;
    String standard_name_vocabulary "CF Standard Name Table v55";
    String summary "The coral bleaching data were composed of the Reef Check dataset (reefcheck.org), collected by a mixture of professional scientists (56%) and trained and certi\\ufb01ed citizen-scientists (44%) using a standardized transect protocol. The dataset includes counts of the number of coral colonies showing bleaching (i.e., the percent of reef corals that were recorded as bleached), which was classi\\ufb01ed as site-wide bleaching. We also examined the prevalence of coral bleaching per coral ecoregion (as de\\ufb01ned by Veron et al. 2015). We used the global Coral Reef Temperature Anomaly Database (CoRTAD Version 6) from the National Oceanic and Atmospheric Administration (www.nodc.noaa.gov/sog/cortad/) to predict coral bleaching prevalence and intensity across reefs worldwide. All CoRTAD variables were weekly data provided on a grid cell basis, of ~4km resolution, from 1982 to 2017(Sully 2019).";
    String title "Bleaching and environmental data for global coral reef sites from 1998-2017";
    String version "1";
    Float64 Westernmost_Easting -179.8593611;
    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.


 
ERDDAP, Version 2.02
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