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Dataset Title:  Trajectories of fifty-five biodegradable drifters in the Belizean Barrier Reef. Subscribe RSS
Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_729896)
Information:  Summary ? | License ? | ISO 19115 | Metadata | Background (external link) | Files | Make a graph
 
Variable ?   Optional
Constraint #1 ?
Optional
Constraint #2 ?
   Minimum ?
 
   Maximum ?
 
 orig_file_name (unitless) ?          "GPSUSER1_103200757..."    "GPSUSER4_123200147..."
 GPS_dataType (unitless) ?          "GPGGA"    "NaN"
 date (unitless) ?          20130530    20130701
 UTC_time (unitless) ?          141906    235905
 latitude (degrees_north) ?          16.62419667    16.84848333
  < slider >
 longitude (degrees_east) ?          88.03578833    88.07614
  < slider >
 fix_quality (unitless) ?          0    1
 satellite_number (count) ?          0    12
 HDOP (unitless) ?          0.8    9.9
 altitude_ (meters) ?          -79.32    59.5
 altitude_units (Altitude, M) ?          "M"    "NaN"
 geoid (meters) ?          -8.0    0.0
 geoid_units (M) ?          "A"    "V"
 checksum_data (unitless) ?          "0000*40"    "NaN"
 time (ISO Date Time UTC, UTC) ?          2013-05-31T16:14:50Z    
  < slider >
 
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)

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The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  orig_file_name {
    String bcodmo_name "file_name";
    String description "Original file name in which data were submitted";
    String long_name "Orig File Name";
    String units "unitless";
  }
  GPS_dataType {
    String bcodmo_name "datatype";
    String description "GPS data type [GPGGA =  Global Positioning System Fix Data; GPGLL = Lat, Lon, time data only]";
    String long_name "GPS Data Type";
    String units "unitless";
  }
  date {
    Int32 _FillValue 2147483647;
    Int32 actual_range 20130530, 20130701;
    String bcodmo_name "date";
    String description "UTC date; yyyymmdd";
    String long_name "Date";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/ADATAA01/";
    String units "unitless";
  }
  UTC_time {
    Int32 _FillValue 2147483647;
    Int32 actual_range 141906, 235905;
    String bcodmo_name "time";
    String description "UTC time; HHMMSS";
    String long_name "UTC Time";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/AHMSAA01/";
    String units "unitless";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 _FillValue NaN;
    Float64 actual_range 16.62419667, 16.84848333;
    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 standard_name "latitude";
    String units "degrees_north";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float64 _FillValue NaN;
    Float64 actual_range 88.03578833, 88.07614;
    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 standard_name "longitude";
    String units "degrees_east";
  }
  fix_quality {
    Byte _FillValue 127;
    Byte actual_range 0, 1;
    String bcodmo_name "unknown";
    Float64 colorBarMaximum 150.0;
    Float64 colorBarMinimum 0.0;
    String description "Fix quality [0 = invalid; 1 = valid]";
    String long_name "Fix Quality";
    String units "unitless";
  }
  satellite_number {
    Byte _FillValue 127;
    Byte actual_range 0, 12;
    String bcodmo_name "count";
    Float64 colorBarMaximum 100.0;
    Float64 colorBarMinimum 0.0;
    String description "Number of satellites being used";
    String long_name "Satellite Number";
    String units "count";
  }
  HDOP {
    Float32 _FillValue NaN;
    Float32 actual_range 0.8, 9.9;
    String bcodmo_name "unknown";
    String description "HDOP [Horizontal dilution of precision;";
    String long_name "HDOP";
    String units "unitless";
  }
  altitude_ {
    Float32 _FillValue NaN;
    Float32 actual_range -79.32, 59.5;
    String bcodmo_name "altitude";
    String description "Altitude in meters above sea level";
    String long_name "Altitude";
    String units "meters";
  }
  altitude_units {
    String bcodmo_name "unknown";
    String long_name "Altitude";
    String units "M";
  }
  geoid {
    Float32 _FillValue NaN;
    Float32 actual_range -8.0, 0.0;
    String bcodmo_name "unknown";
    String description "Geoid in meters above WGS84 ellipsoid";
    String long_name "Geoid";
    String units "meters";
  }
  geoid_units {
    String bcodmo_name "unknown";
    String long_name "Geoid Units";
    String units "M";
  }
  checksum_data {
    String bcodmo_name "unknown";
    String description "Checksum data; internal GPS field required to continue recording";
    String long_name "Checksum Data";
    String units "unitless";
  }
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 1.37001689e+9, NaN;
    String axis "T";
    String bcodmo_name "ISO_DateTime_UTC";
    String description "DateTime ISO UTC formatted";
    String ioos_category "Time";
    String long_name "ISO Date Time UTC";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/DTUT8601/";
    String standard_name "time";
    String time_origin "01-JAN-1970 00:00:00";
    String units "seconds since 1970-01-01T00:00:00Z";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson,.odvTxt";
    String acquisition_description 
"Methodology:
 
Methodology\\u00a0is explained in\\u00a0[Lindo-Atichati et al.
(2016)](\\\\\"https://www.sciencedirect.com/science/article/pii/S1463500316300993?via%3Dihub\\\\\").
As a brief summary, we constructed a hierarchy of four ocean-atmosphere models
operating at multiple scales within a 1 \\u00d7 1 deg domain of the Belizean
Barrier Reef. The four models are: 1) A Low-resolution Ocean model and Low-
resolution Atmospheric model (LOLA); (2) A High-resolution Ocean model and
Low-resolution Atmospheric model (HOLA); (3) A High-resolution Ocean model and
High-resolution Atmospheric model (HOHA); (4) A High-resolution Ocean model
and High-resolution Atmospheric model with Tidal forcing (HOHAT). The ocean
models are based on the HYbrid Coordinate Ocean Model (HYCOM, Bleck, 2002;
Chassignet et al., 2003; Wallcraft et al., 2009). The atmospheric models are
based on the non-hydrostatic Weather Research and Forecasting (WRF) and on the
Navy Operational Global Atmospheric Prediction System (NOGAPS). The drifter
data was from surface drifters provided by the Consortium for Advanced
Research on Transport of Hydrocarbon in the Environment
([CARTHE](\\\\\"http://carthe.org/\\\\\")).
 
Sampling and analytical procedures:
 
From May 30 to July 2 of 2013, 55 drifter deployments were made at 1\\u20135 km
off a 40 km stretch of the BBR centered on South Water Caye (16.82 deg N,
87.97 deg W) (Fig. 2 b and c of\\u00a0[Lindo-Atichati et al
(2016)](\\\\\"https://www.sciencedirect.com/science/article/pii/S1463500316300993?via%3Dihub\\\\\")).
The hierarchy of four ocean-atmosphere models were used for the larger area
from 16.35 to 17.30 deg N, and from 87.48 to 88.47 deg W (Fig. 1 of\\u00a0
[Lindo-Atichati et al
(2016)](\\\\\"https://www.sciencedirect.com/science/article/pii/S1463500316300993?via%3Dihub\\\\\")).
 
Instruments:
 
The drifters are drogued at 40 cm and designed to sample the near-surface
current while minimizing windage. They are tracked using Global Positioning
System (GPS) every second with 5 m accuracy. The GT-31 GPS receivers are set
in a waterproof housing attached to the drifter.";
    String awards_0_award_nid "544434";
    String awards_0_award_number "OCE-1260424";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1260424";
    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 
"Drifter data 
  P. Buston, C. Paris, and D. Lindo-Atichati, PIs 
  Version 14 March 2018 
  	Column \"orig_file_name\" contains UTC start date and time";
    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 "2018-03-08T17:48:35Z";
    String date_modified "2019-04-10T15:23:53Z";
    String defaultDataQuery "&amp;time&lt;now";
    String doi "10.1575/1912/bco-dmo.729896.1";
    Float64 Easternmost_Easting 88.07614;
    Float64 geospatial_lat_max 16.84848333;
    Float64 geospatial_lat_min 16.62419667;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max 88.07614;
    Float64 geospatial_lon_min 88.03578833;
    String geospatial_lon_units "degrees_east";
    String history 
"2022-09-28T20:13:40Z (local files)
2022-09-28T20:13:40Z https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_729896.html";
    String infoUrl "https://www.bco-dmo.org/dataset/729896";
    String institution "BCO-DMO";
    String instruments_0_dataset_instrument_description "Used to collect GPS data";
    String instruments_0_dataset_instrument_nid "729904";
    String instruments_0_description "Acquires satellite signals and tracks your location.";
    String instruments_0_instrument_name "GPS receiver";
    String instruments_0_instrument_nid "706037";
    String instruments_0_supplied_name "GPSMAP 76Cx (Garmin)";
    String keywords "altitude, altitude_units, atmosphere, bco, bco-dmo, biological, checksum, checksum_data, chemical, data, dataset, date, dmo, earth, Earth Science > Atmosphere > Altitude > Station Height, erddap, file, fix, fix_quality, geoid, geoid_units, global, gps, GPS_dataType, hdop, height, iso, ISO_DateTime_UTC, latitude, longitude, management, name, number, oceanography, office, orig, orig_file_name, positioning, preliminary, quality, satellite, satellite_number, science, station, system, time, type, units, UTC_time";
    String keywords_vocabulary "GCMD Science Keywords";
    String license "https://www.bco-dmo.org/dataset/729896/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/729896";
    Float64 Northernmost_Northing 16.84848333;
    String param_mapping "{'729896': {'lat': 'master - latitude', 'lon': 'master - longitude', 'ISO_DateTime_UTC': 'master - time'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/729896/parameters";
    String people_0_affiliation "Boston University";
    String people_0_affiliation_acronym "BU";
    String people_0_person_name "Dr Peter Buston";
    String people_0_person_nid "544437";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "University of Miami Rosenstiel School of Marine and Atmospheric Science";
    String people_1_affiliation_acronym "UM-RSMAS";
    String people_1_person_name "Dr David Lindo-Atichati";
    String people_1_person_nid "729908";
    String people_1_role "Co-Principal Investigator";
    String people_1_role_type "originator";
    String people_2_affiliation "University of Miami Rosenstiel School of Marine and Atmospheric Science";
    String people_2_affiliation_acronym "UM-RSMAS";
    String people_2_person_name "Dr Claire  B Paris";
    String people_2_person_nid "472643";
    String people_2_role "Co-Principal Investigator";
    String people_2_role_type "originator";
    String people_3_affiliation "Boston University";
    String people_3_affiliation_acronym "BU";
    String people_3_person_name "Dr Peter Buston";
    String people_3_person_nid "544437";
    String people_3_role "Contact";
    String people_3_role_type "related";
    String people_4_affiliation "City University of New York, Graduate Center";
    String people_4_affiliation_acronym "GC CUNY";
    String people_4_person_name "Dr David Lindo-Atichati";
    String people_4_person_nid "729908";
    String people_4_role "Contact";
    String people_4_role_type "related";
    String people_5_affiliation "Woods Hole Oceanographic Institution";
    String people_5_affiliation_acronym "WHOI BCO-DMO";
    String people_5_person_name "Hannah Ake";
    String people_5_person_nid "650173";
    String people_5_role "BCO-DMO Data Manager";
    String people_5_role_type "related";
    String project "Elacatinus Dispersal I";
    String projects_0_acronym "Elacatinus Dispersal I";
    String projects_0_description 
"Understanding the patterns, causes and consequences of larval dispersal is a major goal of 21st century marine ecology. Patterns of dispersal determine the rates of larval exchange, or connectivity, between populations. Both physical factors (e.g., water movement) and biological factors (e.g., larval behavior) cause variation in population connectivity. Population connectivity, in turn, has major consequences for all aspects of an organism's biology, from individual behavior to metapopulation dynamics, and from evolution within metapopulations to the origin and extinction of species. Further, understanding population connectivity is critical for the design of effective networks of marine reserves, creation of vital tools in conservation, and the development of sustainable fisheries.
Over the last decade, three methods, each of which tells something slightly different, have emerged as leading contenders to provide the greatest insights into population connectivity. First, coupled biophysical models make assumptions regarding water flow, larval behavior and ecology, to predict population connectivity. Second, indirect genetic methods use spatial distributions of allele frequencies to infer population connectivity. Third, direct genetic methods use parentage analyses, tracing recruits to specific adults, to measure population connectivity. Despite advances, lack of integration means that we do not know the predictive skill of biophysical models, or the extent to which patterns of dispersal predict spatial genetic structure. The overall objective of this proposal is to conduct an integrated investigation of population connectivity, using all three methods in one tractable system: the neon goby, Elacatinus lori, on the Belizean Barrier Reef. There are three motives for this choice of study system: i) fourteen highly polymorphic microsatellite loci have been developed, facilitating the assignment of recruits to parents using parentage analyses and the measurement of dispersal; ii) the physical oceanography of the Belizean Barrier Reef is well-studied, facilitating the development and testing of coupled biophysical models; and, iii) E. lori has a relatively small biogeographic range, facilitating analysis of the spatial distribution of allele frequencies throughout its range.
Broader Impacts. The grant will support one postdoc and two graduate students who will be trained in scientific diving, marine fieldwork, population genetics, biophysical modeling, and mathematical modeling, and will gain collaborative research experience. PIs will incorporate research findings in their courses, which cover all these topics. The grant will also broaden participation of under-represented groups by supporting six undergraduates from groups traditionally underrepresented in STEM fields. In each year of the project there will be an All Participants meeting to reinforce the network of participants. A project website will be developed, in English and Spanish, on the theme of larval dispersal and population connectivity. This will include a resource for K-12 marine science educators developed in collaboration with a marine science educator. All PIs will ensure that results are broadly disseminated to the scientific community and general public via appropriate forms of media.";
    String projects_0_end_date "2017-02";
    String projects_0_geolocation "Belizean Barrier Reef System (16.803 degrees North  88.096 degrees West)";
    String projects_0_name "An Integrative Investigation of Population Connectivity Using a Coral Reef Fish";
    String projects_0_project_nid "544435";
    String projects_0_project_website "http://people.bu.edu/buston/lab/Welcome.html";
    String projects_0_start_date "2013-03";
    String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
    String publisher_type "institution";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 16.62419667;
    String standard_name_vocabulary "CF Standard Name Table v55";
    String summary "Trajectories of fifty-five biodegradable drifters in the Belizean Barrier Reef.";
    String time_coverage_start "2013-05-31T16:14:50Z";
    String title "Trajectories of fifty-five biodegradable drifters in the Belizean Barrier Reef.";
    String version "1";
    Float64 Westernmost_Easting 88.03578833;
    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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