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Dataset Title:  [Breviolum antillogorgium cell counts] - Cell counts of Breviolum
antillogorgium cultures isolated from the octocoral Antillogorgia bipinnata by
sample and treatment for cultures historically grown at 26C and 30C and
reciprocally grown at 26C and 30C, Oct - Dec 2018 (RUI: Collaborative Research:
Genetic variation as a driver of host and symbiont response to increased
temperature on coral reefs)
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_756510)
Information:  Summary ? | License ? | ISO 19115 | Metadata | Background (external link) | Data Access Form | Files
 
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Things You Can Do With Your Graphs

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The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  Date {
    String bcodmo_name "date";
    String description "date of count formatted as yyyy-mm-dd";
    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";
  }
  Day {
    Byte _FillValue 127;
    String _Unsigned "false";
    Byte actual_range 1, 83;
    String bcodmo_name "days";
    String description "Number of days since inoculation";
    String long_name "Day";
    String units "days";
  }
  Culture_ID {
    String bcodmo_name "sample";
    String description "Identification of sample given as culture name (16-0587; 16-0590F; 16-1631; etc.); treatment temperature (26 or 30 C) and replicate (1; 2; 3)";
    String long_name "Culture ID";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/ACYC/";
    String units "unitless";
  }
  Count_1 {
    Int16 _FillValue 32767;
    Int16 actual_range 0, 402;
    String bcodmo_name "cell_concentration";
    Float64 colorBarMaximum 100.0;
    Float64 colorBarMinimum 0.0;
    String description "First replicate of culture counted";
    String long_name "Count 1";
    String units "cells x 10^4/milliliter (cells x 10^4 ml-1)";
  }
  Count_2 {
    Int16 _FillValue 32767;
    Int16 actual_range 0, 369;
    String bcodmo_name "cell_concentration";
    Float64 colorBarMaximum 100.0;
    Float64 colorBarMinimum 0.0;
    String description "Second replicate of culture counted";
    String long_name "Count 2";
    String units "cells x 10^4/milliliter (cells x 10^4 ml-1)";
  }
  Count_3 {
    Int16 _FillValue 32767;
    Int16 actual_range 0, 335;
    String bcodmo_name "cell_concentration";
    Float64 colorBarMaximum 100.0;
    Float64 colorBarMinimum 0.0;
    String description "Third replicate of culture counted";
    String long_name "Count 3";
    String units "cells x 10^4/milliliter (cells x 10^4 ml-1)";
  }
  Count_4 {
    Int16 _FillValue 32767;
    Int16 actual_range 0, 332;
    String bcodmo_name "cell_concentration";
    Float64 colorBarMaximum 100.0;
    Float64 colorBarMinimum 0.0;
    String description "Fourth replicate of culture counted";
    String long_name "Count 4";
    String units "cells x 10^4/milliliter (cells x 10^4 ml-1)";
  }
  Count_5 {
    Int16 _FillValue 32767;
    Int16 actual_range 0, 370;
    String bcodmo_name "cell_concentration";
    Float64 colorBarMaximum 100.0;
    Float64 colorBarMinimum 0.0;
    String description "Fifth replicate of culture counted";
    String long_name "Count 5";
    String units "cells x 10^4/milliliter (cells x 10^4 ml-1)";
  }
  Count_6 {
    Int16 _FillValue 32767;
    Int16 actual_range 0, 318;
    String bcodmo_name "cell_concentration";
    Float64 colorBarMaximum 100.0;
    Float64 colorBarMinimum 0.0;
    String description "Sixth replicate of culture counted";
    String long_name "Count 6";
    String units "cells x 10^4/milliliter (cells x 10^4 ml-1)";
  }
  Mean {
    Float32 _FillValue NaN;
    Float32 actual_range 0.17, 279.5;
    String bcodmo_name "cell_concentration";
    String description "Mean of replicate counts";
    String long_name "Mean";
    String units "cells x 10^4/milliliter (cells x 10^4 ml-1)";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv";
    String acquisition_description 
"Breviolum antillogorgium cultures were initially isolated from Antillogorgia
bipinnata colonies collected at in the upper Florida Reef tract at Elbow Reef
(N 25 07.956 W 80 15.810) in September 2016.\\u00a0 Culture isolations and cell
growth experimentation occurred in the Coffroth lab, University at Buffalo.
 
A total of six Breviolum antillogorgium genotypes were used in this
experiment. Three cultures had been grown at 26 degrees C since isolation in
2016 (16-0590F, 16-0875 and 16-1631) and three had been grown at 30 degrees C
since isolation in 2016 (16-0587, 16-0763 and 16-0764). Three replicates of
each of the six Breviolum antillogorgium cultures were grown at 26 and 30 C
for a total of four treatments (26 degrees at 26 and 30 C and 30 degrees C at
26 and 30 C). A total of four to six replicate counts from each culture was
made every three to twelve days using light microscopy and a hemocytometer.
Mean symbiont density per ml was calculated.
 
Data Processing: Mean x 10000 were calculated from the counts.";
    String awards_0_award_nid "658940";
    String awards_0_award_number "OCE-1559286";
    String awards_0_data_url "https://www.nsf.gov/awardsearch/showAward?AWD_ID=1559286";
    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 
"Breviolum antillogorgium cell counts for growth rate: Oct - Dec 2018 
   PI's: C. terHorst (CSU),  M.A. Coffroth (UBuffalo) 
   version: 2019-02-20";
    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 "2019-02-21T13:58:43Z";
    String date_modified "2019-03-04T19:24:58Z";
    String defaultDataQuery "&time<now";
    String doi "10.1575/1912/bco-dmo.756510.1";
    String history 
"2024-11-08T06:18:54Z (local files)
2024-11-08T06:18:54Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_756510.das";
    String infoUrl "https://www.bco-dmo.org/dataset/756510";
    String institution "BCO-DMO";
    String instruments_0_acronym "Hemocytometer";
    String instruments_0_dataset_instrument_description "Used to make cell counts.";
    String instruments_0_dataset_instrument_nid "756520";
    String instruments_0_description 
"A hemocytometer is a small glass chamber, resembling a thick microscope slide, used for determining the number of cells per unit volume of a suspension. Originally used for performing blood cell counts, a hemocytometer can be used to count a variety of cell types in the laboratory. Also spelled as \"haemocytometer\". Description from:
http://hlsweb.dmu.ac.uk/ahs/elearning/RITA/Haem1/Haem1.html.";
    String instruments_0_instrument_name "Hemocytometer";
    String instruments_0_instrument_nid "704";
    String instruments_0_supplied_name "Reichert Brightline hemocytometer";
    String instruments_1_dataset_instrument_nid "756519";
    String instruments_1_description "Instruments that generate enlarged images of samples using the phenomena of reflection and absorption of visible light. Includes conventional and inverted instruments. Also called a \"light microscope\".";
    String instruments_1_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/LAB05/";
    String instruments_1_instrument_name "Microscope-Optical";
    String instruments_1_instrument_nid "708";
    String instruments_1_supplied_name "Zeiss";
    String keywords "bco, bco-dmo, biological, chemical, count, Count_1, Count_2, Count_3, Count_4, Count_5, Count_6, culture, Culture_ID, data, dataset, date, day, dmo, erddap, management, mean, oceanography, office, preliminary, time";
    String license "https://www.bco-dmo.org/dataset/756510/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/756510";
    String param_mapping "{'756510': {}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/756510/parameters";
    String people_0_affiliation "State University of New York at Buffalo";
    String people_0_affiliation_acronym "SUNY Buffalo";
    String people_0_person_name "Mary Alice Coffroth";
    String people_0_person_nid "472488";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "California State University Northridge";
    String people_1_affiliation_acronym "CSU-Northridge";
    String people_1_person_name "Casey terHorst";
    String people_1_person_nid "632541";
    String people_1_role "Co-Principal Investigator";
    String people_1_role_type "originator";
    String people_2_affiliation "Woods Hole Oceanographic Institution";
    String people_2_affiliation_acronym "WHOI BCO-DMO";
    String people_2_person_name "Nancy Copley";
    String people_2_person_nid "50396";
    String people_2_role "BCO-DMO Data Manager";
    String people_2_role_type "related";
    String project "Host Symbiont Temp Response";
    String projects_0_acronym "Host Symbiont Temp Response";
    String projects_0_description 
"Description from NSF award abstract:
On coral reefs, mutualisms with single celled algae (Symbiodinium) and reef species literally and figuratively form the foundation of reef ecosystems. Coral reefs are among the most threatened ecosystems under a changing climate and are rapidly declining due to increasing levels of environmental stress, namely increased temperatures. Climate change is resulting in even warmer ocean temperatures that threaten associations between Symbiodinium and their hosts. In this project the investigators examine the genetic diversity of Symbiodinium and the potential for this important species to evolve in response to temperature. The project will also address whether the ecological and evolutionary dynamics of the Symbiodinium population affect the performance of their host. If so, this suggests that the evolution of microscopic organisms with short generation times could confer adaptation to longer-lived host species on ecologically and economically vital coral reefs. Given that diversity is already being lost on many reefs, considering how evolutionary changes in Symbiodinium will affect reef species is crucial for predicting the responses of reefs to future climate change. This project provides training for two graduate students and several undergraduates at a Hispanic-serving institution. This work includes outreach to the students and the general public through the Aquarium of Niagara, local K-12 schools, and web-based education modules.
The effects of evolution on contemporary ecological processes are at the forefront of research in evolutionary ecology. This project will answer the call for experiments elucidating the effects of genetic variation in Symbiodinium performance and the effect on the response of the holobiont (host and symbiont) to increased temperature. These experiments examine the effects of temperature through both ecological and evolutionary mechanisms and will determine the relative importance of adaptation and acclimatization in replicated experimental populations. The investigators will examine how genetic variation within a species (Symbiodinium antillogorgium) affects symbiont performance in culture and in the host and how this affects the response of the holobiont to increased temperature. Further, the project examines whether holobiont response to increased temperature associated with climate change depends on particular GxG host-symbiont combinations. Moreover, the investigators will examine the effects of symbiont history on mutualist hosts, which have been largely ignored in eco-evolutionary studies. These experiments provide a first step in predicting whether invertebrate hosts on coral reefs will respond to global change via adaptation of their symbionts.";
    String projects_0_end_date "2020-03";
    String projects_0_geolocation "Florida Keys, Caribbean";
    String projects_0_name "RUI: Collaborative Research: Genetic variation as a driver of host and symbiont response to increased temperature on coral reefs";
    String projects_0_project_nid "632538";
    String projects_0_start_date "2016-04";
    String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
    String publisher_type "institution";
    String sourceUrl "(local files)";
    String standard_name_vocabulary "CF Standard Name Table v55";
    String summary "Cell counts of Breviolum antillogorgium cultures isolated from the octocoral Antillogorgia bipinnata by sample and treatment for cultures historically grown at 26 and 30 degrees C and reciprocally grown at 26 and 30 degrees C";
    String title "[Breviolum antillogorgium cell counts] - Cell counts of Breviolum antillogorgium cultures isolated from the octocoral Antillogorgia bipinnata by sample and treatment for cultures historically grown at 26C and 30C and reciprocally grown at 26C and 30C, Oct - Dec 2018 (RUI: Collaborative Research: Genetic variation as a driver of host and symbiont response to increased temperature on coral reefs)";
    String version "1";
    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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