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Dataset Title:  [Goby data geolocations] - UTM coordinates for waypoint locations used to
generate Elori raw data in 2006. (An Integrative Investigation of Population
Connectivity Using a Coral Reef Fish)
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_704783)
Range: longitude = -88.07962 to -88.076775°E, latitude = 16.803158 to 16.80436°N
Information:  Summary ? | License ? | FGDC | 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 {
  waypoint_ID {
    Int16 _FillValue 32767;
    Int16 actual_range 92, 795;
    String bcodmo_name "site";
    String description "PI issued location ID";
    String long_name "Waypoint ID";
    String units "unitless";
  }
  UTM_zone {
    Byte _FillValue 127;
    String _Unsigned "false";
    Byte actual_range 16, 16;
    String bcodmo_name "unknown";
    String description "UTM zone for northing and easting coordinates";
    String long_name "UTM Zone";
    String units "unitless";
  }
  hempisphere {
    String bcodmo_name "unknown";
    String description "Hemisphere for northing and easting coordinates";
    String long_name "Hempisphere";
    String units "unitless";
  }
  easting {
    Int32 _FillValue 2147483647;
    Int32 actual_range 384957, 385260;
    String bcodmo_name "UTM Coordinates";
    String description "Easting coordinate";
    String long_name "Easting";
    String units "Universal Transverse Mercator coordinate system";
  }
  northing {
    Int32 _FillValue 2147483647;
    Int32 actual_range 1858092, 1858225;
    String bcodmo_name "UTM Coordinates";
    String description "Northing coordinate";
    String long_name "Northing";
    String units "Universal Transverse Mercator coordinate system";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 _FillValue NaN;
    Float64 actual_range 16.80315844, 16.80435978;
    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 -88.07961832, -88.07677626;
    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";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson";
    String acquisition_description "Coordinates for waypoint locations.";
    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 
"Sampling Locations 
  P. Buston and C. D'Aloia, PIs 
  Version 14 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 "2017-06-14T19:24:14Z";
    String date_modified "2019-03-27T20:37:26Z";
    String defaultDataQuery "&time<now";
    String doi "10.1575/1912/bco-dmo.704783.1";
    Float64 Easternmost_Easting -88.07677626;
    Float64 geospatial_lat_max 16.80435978;
    Float64 geospatial_lat_min 16.80315844;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -88.07677626;
    Float64 geospatial_lon_min -88.07961832;
    String geospatial_lon_units "degrees_east";
    String history 
"2024-11-08T06:13:46Z (local files)
2024-11-08T06:13:46Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_704783.das";
    String infoUrl "https://www.bco-dmo.org/dataset/704783";
    String institution "BCO-DMO";
    String keywords "bco, bco-dmo, biological, chemical, data, dataset, dmo, easting, erddap, hempisphere, latitude, longitude, management, northing, oceanography, office, preliminary, utm, UTM_zone, waypoint, waypoint_ID, zone";
    String license "https://www.bco-dmo.org/dataset/704783/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/704783";
    Float64 Northernmost_Northing 16.80435978;
    String param_mapping "{'704783': {'lat': 'master - latitude', 'lon': 'master - longitude'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/704783/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 "Woods Hole Oceanographic Institution";
    String people_1_affiliation_acronym "WHOI";
    String people_1_person_name "Dr Cassidy C. D'Aloia";
    String people_1_person_nid "704789";
    String people_1_role "Co-Principal Investigator";
    String people_1_role_type "originator";
    String people_2_affiliation "Boston University";
    String people_2_affiliation_acronym "BU";
    String people_2_person_name "Dr Peter Buston";
    String people_2_person_nid "544437";
    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 "Hannah Ake";
    String people_3_person_nid "650173";
    String people_3_role "BCO-DMO Data Manager";
    String people_3_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 16.80315844;
    String standard_name_vocabulary "CF Standard Name Table v55";
    String subsetVariables "UTM_zone,hempisphere";
    String summary "UTM coordinates for waypoint locations used to generate Elori raw data in 2006.";
    String title "[Goby data geolocations] - UTM coordinates for waypoint locations used to generate Elori raw data in 2006. (An Integrative Investigation of Population Connectivity Using a Coral Reef Fish)";
    String version "1";
    Float64 Westernmost_Easting -88.07961832;
    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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