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| Dataset Title: | [Flow Cytometry Results] - Results of the quantification of symbiont cell numbers from 400 Acropora hyacinthus colonies subjected to experimental bleaching in the summer of 2018 in Palau. (Predicting the global location of heat tolerant corals: Palau patch reefs as a general model) 
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| Institution: | BCO-DMO (Dataset ID: bcodmo_dataset_813210) |
| Information: | Summary
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| ISO 19115
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Attributes {
s {
Sample {
Int16 _FillValue 32767;
Int16 actual_range 1, 400;
String bcodmo_name "sample";
String description "Colony Number";
String long_name "Sample";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/ACYC/";
String units "dimensionless";
}
Treatment {
String bcodmo_name "treatment";
String description "Treatment (C1 and C2 are control), all others are heat stress";
String long_name "Treatment";
String units "unitless";
}
Temperature {
Float32 _FillValue NaN;
Float32 actual_range 30.0, 35.0;
String bcodmo_name "temperature";
String description "Specific Temperature treatment";
String long_name "Temperature";
String units "degrees Celsius";
}
Sample_ID {
Int16 _FillValue 32767;
Int16 actual_range 1, 1684;
String bcodmo_name "sample";
String description "Unique sample ID (technical replicates have the same SampleID)";
String long_name "Sample ID";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/ACYC/";
String units "dimensionless";
}
ALLEVENTS_Conc {
Float64 _FillValue NaN;
Float64 actual_range 2096.96, 2541437.63;
String bcodmo_name "cell_concentration";
String description "Concentration (cells/ml) of events above gating threshold";
String long_name "ALLEVENTS Conc";
String units "cells/ml";
}
SYMBIODINIUM_Conc {
Float64 _FillValue NaN;
Float64 actual_range 0.0, 396300.22;
String bcodmo_name "cell_concentration";
String description "Concentration (cells/ml) of events above gating threshold that are also above the symbiodinium gating threshold";
String long_name "SYMBIODINIUM Conc";
String units "cells/ml";
}
Number_of_Events {
Int16 _FillValue 32767;
Int16 actual_range 30, 5000;
String bcodmo_name "count";
Float64 colorBarMaximum 100.0;
Float64 colorBarMinimum 0.0;
String description "Number of events counted (max 5000)";
String long_name "Number Of Events";
String units "unitless";
}
Cell_Count {
Float32 _FillValue NaN;
Float32 actual_range 2.1, 2541.44;
String bcodmo_name "cell_concentration";
Float64 colorBarMaximum 100.0;
Float64 colorBarMinimum 0.0;
String description "Concentration (cells/ul) of events above gating threshold";
String long_name "Cell Count";
String units "cells/ul";
}
Total_Volume {
Float32 _FillValue NaN;
Float32 actual_range 1.97, 100.3;
String bcodmo_name "volume";
String description "Total volume of sample measured in microliters";
String long_name "Total Volume";
String units "microliters";
}
Acquisition_Time {
Float32 _FillValue NaN;
Float32 actual_range 8.34, 425.01;
String bcodmo_name "time_elapsed";
String description "Total acquisition time on instrument in seconds";
String long_name "Acquisition Time";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/ELTMZZZZ/";
String units "seconds";
}
Negative_Total_Count {
Int16 _FillValue 32767;
Int16 actual_range 22, 517;
String bcodmo_name "cell_concentration";
Float64 colorBarMaximum 100.0;
Float64 colorBarMinimum 0.0;
String description "Number of events above gating threshold in negative control";
String long_name "Negative Total Count";
String units "various";
}
Negative_Events {
Float32 _FillValue NaN;
Float32 actual_range 14.4, 36137.93;
String bcodmo_name "cell_concentration";
String description "Concentration of cells (cells/ml) in negative control above gating threshold";
String long_name "Negative Events";
String units "cells/ml";
}
Negative_Sym_Conc {
Float32 _FillValue NaN;
Float32 actual_range 0.0, 2935.75;
String bcodmo_name "cell_concentration";
String description "Concentration of symbiont cells in negative control above gating threshold";
String long_name "Negative Sym Conc";
String units "various";
}
Negative_Cells {
Float32 _FillValue NaN;
Float32 actual_range 1.54, 36.14;
String bcodmo_name "cell_concentration";
String description "Concentration of cells (cells/ul) in negative control above gating threshold";
String long_name "Negative Cells";
String units "cell/ul";
}
Negative_Total_Vol {
Float32 _FillValue NaN;
Float32 actual_range 14.3, 14.31;
String bcodmo_name "volume";
String description "Total volume of negative control measured in microliters";
String long_name "Negative Total Vol";
String units "microliters";
}
Negative_Acquisition_Time {
Float32 _FillValue NaN;
Float32 actual_range 60.6, 60.62;
String bcodmo_name "time_elapsed";
String description "Total acquisistion time on instrument for negative control in seconds";
String long_name "Negative Acquisition Time";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/ELTMZZZZ/";
String units "seconds";
}
}
NC_GLOBAL {
String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv";
String acquisition_description
"These samples were collected according to the protocol published by Krediet et
al. 2015: Article Rapid, Precise, and Accurate Counts of Symbiodinium Cells
Using the Guava Flow Cytometer, and a Comparison to Other Methods
The samples that were analyzed for this study are 400 colonies of Acropora
hyacinthus. Nubbins from each colony were experimentally bleached at
temperatures of 34, 34.5 and 35 degrees Celsius as well as two control
treatments (30 deg. C). These nubbins were then airbrushed and the resulting
tissue slurry was preserved in RNAlater. Tissue dissociation and preparation
for analysis on the Guava EasyCyte flow cytometer followed the protocol by
Krediet et al. 2015.
Procedures followed Krediet et al. 2015 (above), with the exception that
protein concentration was not measured.";
String awards_0_award_nid "764076";
String awards_0_award_number "OCE-1736736";
String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1736736";
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
"Flowcyt
Stephen Palumbi
Data Version 1: 2020-06-23";
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 "2020-05-28T16:36:32Z";
String date_modified "2020-07-08T18:02:32Z";
String defaultDataQuery "&time<now";
String doi "10.26008/1912/bco-dmo.813210.1";
String history
"2024-12-31T03:03:39Z (local files)
2024-12-31T03:03:39Z https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_813210.html";
String infoUrl "https://www.bco-dmo.org/dataset/813210";
String institution "BCO-DMO";
String instruments_0_acronym "Flow Cytometer";
String instruments_0_dataset_instrument_nid "813213";
String instruments_0_description
"Flow cytometers (FC or FCM) are automated instruments that quantitate properties of single cells, one cell at a time. They can measure cell size, cell granularity, the amounts of cell components such as total DNA, newly synthesized DNA, gene expression as the amount messenger RNA for a particular gene, amounts of specific surface receptors, amounts of intracellular proteins, or transient signalling events in living cells.
(from: http://www.bio.umass.edu/micro/immunology/facs542/facswhat.htm)";
String instruments_0_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/LAB37/";
String instruments_0_instrument_name "Flow Cytometer";
String instruments_0_instrument_nid "660";
String instruments_0_supplied_name "Guava easyCyte HT 2-laser flow cytometer (Millipore)";
String keywords "acquisition, Acquisition_Time, allevents, ALLEVENTS_Conc, bco, bco-dmo, biological, cell, Cell_Count, cells, chemical, conc, count, data, dataset, dmo, erddap, events, management, negative, Negative_Acquisition_Time, Negative_Cells, Negative_Events, Negative_Sym_Conc, Negative_Total_Count, Negative_Total_Vol, number, Number_of_Events, oceanography, office, preliminary, sample, Sample_ID, sym, symbiodinium, SYMBIODINIUM_Conc, temperature, time, total, Total_Volume, treatment, vol, volume";
String license "https://www.bco-dmo.org/dataset/813210/license";
String metadata_source "https://www.bco-dmo.org/api/dataset/813210";
String param_mapping "{'813210': {}}";
String parameter_source "https://www.bco-dmo.org/mapserver/dataset/813210/parameters";
String people_0_affiliation "Stanford University";
String people_0_person_name "Stephen R. Palumbi";
String people_0_person_nid "51368";
String people_0_role "Lead Principal Investigator";
String people_0_role_type "originator";
String people_1_affiliation "Woods Hole Oceanographic Institution";
String people_1_affiliation_acronym "WHOI BCO-DMO";
String people_1_person_name "Christina Haskins";
String people_1_person_nid "746212";
String people_1_role "BCO-DMO Data Manager";
String people_1_role_type "related";
String project "Heat Tolerant Corals";
String projects_0_acronym "Heat Tolerant Corals";
String projects_0_description
"NSF Award Abstract:
When coral reefs heat up just a few degrees above normal summer temperatures, a reaction called coral bleaching can occur in which single celled plants living inside coral cells are expelled. The coral turns from its normal tan color to bleached white, and because it is deprived of the normal food supply from its plant partner, most of these corals die. Yet, some corals naturally can survive high temperatures that cause others in the same species to bleach. Identifying where these heat tolerant corals are common would provide a general tool for protecting and restoring heat tolerant reefs. The investigators will conduct experiments on 30 patch reefs in Palau of very different sizes in two lagoons, record local temperatures for 400 corals, and test coral heat tolerance using a newly designed coral stress tank. Because large patch reefs generally heat up during daytime low tides, The investigators hypothesize that they are commonly home to heat resistant corals. They will also move heat tolerant corals to cooler locations to test the stability of heat resistance among corals. The stress tank technologies can be widely used in remote settings, and will provide a set of generalizable, practical tools for communities and managers to find and protect heat tolerant corals in reefs around the world. The work will advance undergraduate STEM education in California and Palau. A partnership with the Palau Community College will facilitate the engagement of Pacific Island communities and students. Students will receive interdisciplinary training in field research, genomics and bioinformatics and learn practical skills that will enable them to collect and interpret stress tank and temperature data. Broader outreach efforts will include the production and dissemination of a series of microdocumentaries and blog posts designed to bring the concept of a world-wide search for heat tolerant corals to a global audience.
Previous coral reef research has demonstrated that periodic high water temperatures can induce high heat tolerance in reef building corals through a combination of acclimation and selection at many genetic loci. Key questions include whether these kinds of heat tolerant habitats are common or rare, and whether their locations can be predicted by identifying coral reefs where daily temperature spikes regularly occur at low tide. This project will examine heat tolerance of 400 corals in the Acropora hyacinthus species complex across 30 patch reefs in Palau that experience variable temperature and flow profiles. This study will utilize a variety of methods to characterize spatial and temporal patterns of heat tolerance including: (1) the development of low-cost, portable heat stress tanks to quickly and affordably assess in situ conditions, (2) genomic assays of physiological condition to identify the genes and gene expression mechanisms that are responsible for heat tolerance, (3) high resolution temperature mapping to trace the role of temperature variation in producing stable, high temperature tolerance in reef building corals, and (4) reciprocal transplant experiments to evaluate whether heat resistant corals retain heat resistance when moved to cooler locations. This research will expand the geographic map of habitats with known heat tolerance, and expedite the ability to locate coral populations that may be most resistant to future ocean warming.";
String projects_0_end_date "2020-09";
String projects_0_geolocation "Palau";
String projects_0_name "Predicting the global location of heat tolerant corals: Palau patch reefs as a general model";
String projects_0_project_nid "764077";
String projects_0_start_date "2017-10";
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 "Results of the quantification of symbiont cell numbers from 400 Acropora hyacinthus colonies subjected to experimental bleaching in the summer of 2018 in Palau.";
String title "[Flow Cytometry Results] - Results of the quantification of symbiont cell numbers from 400 Acropora hyacinthus colonies subjected to experimental bleaching in the summer of 2018 in Palau. (Predicting the global location of heat tolerant corals: Palau patch reefs as a general model)";
String version "1";
String xml_source "osprey2erddap.update_xml() v1.5";
}
}
Data Access Protocol (DAP) and its
selection constraints.
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.