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Dataset Title:  Sponge volume at Virgin Islands Territorial Coral Reef Monitoring Program\
u2019s (TCRMP) permanent monitoring sites, 2015-2017
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_814490)
Range: longitude = -65.0823 to -64.8602°E, latitude = 18.2786 to 18.3743°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 {
  year {
    Int16 _FillValue 32767;
    Int16 actual_range 2015, 2017;
    String bcodmo_name "year";
    String description "sampling year";
    String long_name "Year";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/YEARXXXX/";
    String units "unitless";
  }
  site {
    String bcodmo_name "site";
    String description "sampling site identifier";
    String long_name "Site";
    String units "unitless";
  }
  site_name {
    String bcodmo_name "site";
    String description "name of sampling site";
    String long_name "Site Name";
    String units "unitless";
  }
  site_description {
    String bcodmo_name "site_descrip";
    String description "description of relative human development of site";
    String long_name "Site Description";
    String units "unitless";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 _FillValue NaN;
    Float64 actual_range 18.2786, 18.3743;
    String axis "Y";
    String bcodmo_name "latitude";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String description "latitude; north is 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 -65.0823, -64.8602;
    String axis "X";
    String bcodmo_name "longitude";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String description "longitude; east is 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";
  }
  quadrat {
    String bcodmo_name "sample";
    String description "quadrat identifier";
    String long_name "Quadrat";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/ACYC/";
    String units "unitless";
  }
  sponge_volume {
    Float32 _FillValue NaN;
    Float32 actual_range 37.8, 11334.17;
    String bcodmo_name "volume";
    String description "estimated volume of all sponges In quadrat";
    String long_name "Sponge Volume";
    String units "centimeters^3 of sponge/meter^2 (cm3/m2)";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson";
    String acquisition_description 
"Prior to the 2017 hurricanes, six shallow (8-15 m depth) reef sites had been
selected from the Virgin Islands Territorial Coral Reef Monitoring
Program\\u2019s (TCRMP) permanent monitoring sites to study variation in sponge
communities in St. Thomas. These sites included Black Point
(N18\\u00b0\\u00a020.665\\u2019, W64\\u00b0\\u00a059.107\\u2019), Coculus Rock
(N18\\u00b0\\u00a018.734\\u2019, W64\\u00b0\\u00a051.613\\u2019), and Magens Bay
(N18\\u00b0 22.459\\u2019, W64\\u00b0 56.077\\u2019), which are in embayments with
heavily developed watersheds. Buck Island (N18\\u00b0 16.717\\u2019, W64\\u00b0
53.925\\u2019) and Savana Island (N18\\u00b0\\u00a020.437\\u2019,
W65\\u00b0\\u00a004.939\\u2019) are located near undeveloped offshore cays.
Botany Bay (N18\\u00b0\\u00a021.433\\u2019, W65\\u00b0\\u00a002.071\\u2019) is a
nearshore site in a bay with a low level of watershed development. For this
study, we used three randomly selected transects out of the six permanently
established 10 m TCRMP transects at each site. The same three transects at
each site were re-surveyed repeatedly in August 2015, August 2016 (pre-
hurricanes) and December 2017 (10 weeks post-hurricanes).\\u00a0
 
At each site, sponge volume was calculated within permanent 1 m2\\u00a0quadrats
centered on the transect line within the initial and/or final meter of the
transect. Sponge volume was calculated for 3-5 quadrats per site. As there
were over 80 species of sponges within our survey areas, representing a wide
diversity of morphologies, we chose to use a standardized measurement approach
for all sponges, rather than calculating the true volumetric measurement for
each sponge based on its actual morphology. Thus, sponges were essentially
treated as cuboids. We used a flexible sewing tape to measure the longest
dimension of the sponge, then one to several width measurements perpendicular
to the initial length measurement, and one to several height measurements, as
needed to represent the shape and dimensions of each sponge. Multiple
measurements for each dimension were averaged and length x width x height was
calculated. For large tubes, of which there were relatively few, we subtracted
the dimensions of the interior cavity from the exterior dimensions of the
sponge. Generated data were in cm3 of sponge/m2 (Gochfeld et al. 2020).";
    String awards_0_award_nid "749383";
    String awards_0_award_number "OCE-1807807";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1807807";
    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 
"Sponge volume 
      at Virgin Islands Territorial Coral Reef Monitoring Program (TCRMP) permanent monitoring sites, 2015-2017 
   PI's: D. Gochfeld (U Miss), J. Olson (U.AL), M. Brandt (UVI) 
   version date: 2020-06-08";
    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 dataset_current_state "Final and no updates";
    String date_created "2020-06-08T18:54:00Z";
    String date_modified "2020-07-08T21:22:35Z";
    String defaultDataQuery "&time<now";
    String doi "10.26008/1912/bco-dmo.814490.1";
    Float64 Easternmost_Easting -64.8602;
    Float64 geospatial_lat_max 18.3743;
    Float64 geospatial_lat_min 18.2786;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -64.8602;
    Float64 geospatial_lon_min -65.0823;
    String geospatial_lon_units "degrees_east";
    String history 
"2024-03-28T18:22:28Z (local files)
2024-03-28T18:22:28Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_814490.das";
    String infoUrl "https://www.bco-dmo.org/dataset/814490";
    String institution "BCO-DMO";
    String keywords "bco, bco-dmo, biological, chemical, data, dataset, description, dmo, erddap, latitude, longitude, management, name, oceanography, office, preliminary, quadrat, site, site_description, site_name, sponge, sponge_volume, volume, year";
    String license "https://www.bco-dmo.org/dataset/814490/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/814490";
    Float64 Northernmost_Northing 18.3743;
    String param_mapping "{'814490': {'lat': 'master - latitude', 'lon': 'master - longitude'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/814490/parameters";
    String people_0_affiliation "University of Mississippi";
    String people_0_affiliation_acronym "UM-NCNPR";
    String people_0_person_name "Deborah J Gochfeld";
    String people_0_person_nid "51458";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "University of the Virgin Islands Center for Marine and Environmental Studies";
    String people_1_person_name "Marilyn Brandt";
    String people_1_person_nid "559376";
    String people_1_role "Co-Principal Investigator";
    String people_1_role_type "originator";
    String people_2_affiliation "University of Alabama-Tuscaloosa";
    String people_2_affiliation_acronym "UA/Tuscaloosa";
    String people_2_person_name "Julie Olson";
    String people_2_person_nid "51454";
    String people_2_role "Co-Principal Investigator";
    String people_2_role_type "originator";
    String people_3_affiliation "Woods Hole Oceanographic Institution";
    String people_3_affiliation_acronym "WHOI BCO-DMO";
    String people_3_person_name "Nancy Copley";
    String people_3_person_nid "50396";
    String people_3_role "BCO-DMO Data Manager";
    String people_3_role_type "related";
    String project "Sponge resilience";
    String projects_0_acronym "Sponge resilience";
    String projects_0_description 
"NSF Award Abstract:
Over the past several decades, coral reefs worldwide have undergone a transition from being dominated by the corals themselves to being dominated by sponges or algae. The causes of these changes are complex, but they include both natural stressors, such as diseases and hurricanes, and impacts from human activities, such as coastal development and climate change. There are over 600 species of sponges on Caribbean coral reefs, and they serve many important ecological roles, including nutrient cycling, providing food and shelter for other reef animals, and producing a tremendous diversity of chemical compounds that are important for controlling species interactions on the reef, and may serve as potential new drugs. In spite of their importance on coral reefs, there are many aspects of sponge biology that remain unknown, including how they respond to different types of stressors. Coral reefs in St. Thomas, in the U.S. Virgin Islands, are exposed to different levels of man-made stressors, depending upon their proximity to coastal development, and the sponge assemblages on these reefs also vary with levels of human impacts. In September 2017, St. Thomas was devastated by two Category 5 hurricanes in a row. Since, unlike corals, virtually nothing is known about what happens to sponge communities in the aftermath of hurricanes, the research team will use a combination of field ecology and population genetics approaches to determine how sponge communities respond and recover from these devastating storms and whether prior exposure to land-based stressors affects their recovery. Researchers at the Universities of Mississippi, Alabama and the Virgin Islands will participate in this RAPID project, and will provide training opportunities for students and postdoctoral researchers, especially from underrepresented groups. Information will be provided to resource managers in the Virgin Islands, along with outreach programs to community groups in St. Thomas.
The goal of this project is to assess the impacts of single (e.g., hurricanes) versus multiple (e.g., hurricanes and land-based sources of pollution) stressors on the resilience, recovery, and recruitment of sponge communities in St. Thomas, U.S.V.I. Given the growing dominance of sponges on coral reefs worldwide, understanding the responses of sponges to natural and anthropogenic stressors is increasingly important. The investigators will leverage multiple years of data on sponge assemblages from several sites around the island of St. Thomas that varied in their levels of exposure to local land-based stressors prior to Hurricanes Irma and Maria, and evaluate changes to these diverse assemblages over time, beginning within 3 months of these devastating storms. Using a combination of natural and experimentally cleared plots, the investigators will assess the progress of sponge succession and whether the presence of algae interferes with sponge recruitment and recovery. Subsamples of recruits and nearby conspecifics will be collected to evaluate population genetic diversity and potential sources of new individuals. The data resulting from this project will provide critical insights into sponge resilience in response to hurricanes at sites previously exposed to land-based stressors, the initiation of succession within sponge communities, potential predictors of successional trajectory, and genetic diversity within sponge populations following a storm event. This information will help identify factors that inhibit coral recovery and potential approaches to enhance resilience of coral reefs.";
    String projects_0_end_date "2019-11";
    String projects_0_geolocation "St. Thomas, U.S. Virgin Islands";
    String projects_0_name "RAPID:  Collaborative Research:  Sponge resilience in the face of multiple stressors";
    String projects_0_project_nid "749384";
    String projects_0_start_date "2017-12";
    String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
    String publisher_type "institution";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 18.2786;
    String standard_name_vocabulary "CF Standard Name Table v55";
    String summary "Sponge volume at Virgin Islands Territorial Coral Reef Monitoring Program\\u2019s (TCRMP) permanent monitoring sites, 2015-2017.";
    String title "Sponge volume at Virgin Islands Territorial Coral Reef Monitoring Program\\u2019s (TCRMP) permanent monitoring sites, 2015-2017";
    String version "1";
    Float64 Westernmost_Easting -65.0823;
    String xml_source "osprey2erddap.update_xml() v1.5";
  }
}

 

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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