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Dataset Title:  Acropora cervicornis buoyant weight measurements under different pH and
temperature treatments from experiments at Summerland Key, Florida from July to
September 2017
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_811853)
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 {
  Tank {
    Byte _FillValue 127;
    Byte actual_range 11, 30;
    String bcodmo_name "tank";
    String description "identifies the tank number that held the particular coral fragment";
    String long_name "Tank";
    String units "unitless";
  }
  Genotype {
    Byte _FillValue 127;
    Byte actual_range 1, 63;
    String bcodmo_name "sample_type";
    String description "identifies the genotype number of the coral animal for each fragment";
    String long_name "Genotype";
    String units "unitless";
  }
  Date {
    String bcodmo_name "date";
    String description "the day that the buoyant weight measurement was taken; format: yyyy-mm-dd";
    String long_name "Date";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/ADATAA01/";
    String units "unitless";
  }
  pH {
    String bcodmo_name "treatment";
    String description "identifies the treatment pH level: Ambient = 8.1 pH; High CO2 = 7.7 pH";
    String long_name "pH";
    String units "unitless";
  }
  Temp {
    String bcodmo_name "treatment";
    String description "identifies the treatment temperature level: High = 31.5C; Ambient = 27C";
    String long_name "Temperature";
    String units "unitless";
  }
  Weight_July_g {
    Float32 _FillValue NaN;
    Float32 actual_range 4.1064, 10.8183;
    String bcodmo_name "weight";
    String description "identifies the buoyant weight of the coral fragment in July 2017";
    String long_name "Weight July G";
    String units "grams (g)";
  }
  Weight_Aug_g {
    Float32 _FillValue NaN;
    Float32 actual_range 4.174, 11.224;
    String bcodmo_name "weight";
    String description "identifies the buoyant weight of the coral fragment in August 2017";
    String long_name "Weight Aug G";
    String units "grams (g)";
  }
  Weight_Sept_g {
    Float32 _FillValue NaN;
    Float32 actual_range 4.219, 11.342;
    String bcodmo_name "weight";
    String description "identifies the buoyant weight of the coral fragment in September 2017";
    String long_name "Weight Sept G";
    String units "grams (g)";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv";
    String acquisition_description 
"A 5 gallon aquaria was filled with treatment water conditions and an
analytical balance was suspended over the aquaria using a solid wooden board
with a hole cut through the middle. Corals were placed on a suspended
structure that was attached underneath an analytical balance and held until
the total buoyant weight was stable. The data was recorded each month for each
fragment. Photographs were also taken to determine the surface area of the
coral using ImageJ analysis.";
    String awards_0_award_nid "642851";
    String awards_0_award_number "OCE-1452538";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward?AWD_ID=1452538&HistoricalAwards=false";
    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 "Michael E. Sieracki";
    String awards_0_program_manager_nid "50446";
    String cdm_data_type "Other";
    String comment 
"Buoyant weight data: 2017 
  PI: Erinn Muller (MOTE) 
  Version date: 2020-05-19";
    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 "2020-05-19T19:02:13Z";
    String date_modified "2020-05-20T13:28:41Z";
    String defaultDataQuery "&time<now";
    String doi "10.26008/1912/bco-dmo.811853.1";
    String history 
"2020-08-08T00:55:14Z (local files)
2020-08-08T00:55:14Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_811853.das";
    String infoUrl "https://www.bco-dmo.org/dataset/811853";
    String institution "BCO-DMO";
    String instruments_0_acronym "camera";
    String instruments_0_dataset_instrument_nid "811895";
    String instruments_0_description "All types of photographic equipment including stills, video, film and digital systems.";
    String instruments_0_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/311/";
    String instruments_0_instrument_name "Camera";
    String instruments_0_instrument_nid "520";
    String instruments_1_acronym "Scale";
    String instruments_1_dataset_instrument_nid "811894";
    String instruments_1_description "An instrument used to measure weight or mass.";
    String instruments_1_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/LAB13/";
    String instruments_1_instrument_name "Scale";
    String instruments_1_instrument_nid "714";
    String instruments_1_supplied_name "analytical balance";
    String keywords "bco, bco-dmo, biological, chemical, data, dataset, date, dmo, erddap, genotype, management, oceanography, office, preliminary, sept, tank, Temp, temperature, weight, Weight_Aug_g, Weight_July_g, Weight_Sept_g";
    String license "https://www.bco-dmo.org/dataset/811853/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/811853";
    String param_mapping "{'811853': {}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/811853/parameters";
    String people_0_affiliation "Mote Marine Laboratory";
    String people_0_affiliation_acronym "Mote";
    String people_0_person_name "Erinn Muller";
    String people_0_person_nid "642853";
    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 BCO-DMO";
    String people_1_person_name "Shannon Rauch";
    String people_1_person_nid "51498";
    String people_1_role "BCO-DMO Data Manager";
    String people_1_role_type "related";
    String project "Resilient Acerv";
    String projects_0_acronym "Resilient Acerv";
    String projects_0_description 
"Caribbean staghorn coral was one of the most common corals within reefs of the Florida Keys several decades ago. Over the last 40 years disease, bleaching, overfishing and habitat degradation caused a 95% reduction of the population. Staghorn coral is now listed as threatened under the U.S. Endangered Species Act of 1973. Within the past few years, millions of dollars have been invested for the purpose of restoring the population of staghorn coral within Florida and the U.S. Virgin Islands. Significant effort has been placed on maintaining and propagating corals of known genotypes within coral nurseries for the purpose of outplanting. However, little is known about the individual genotypes that are currently being outplanted from nurseries onto coral reefs. Are the genotypes being used for outplanting resilient enough to survive the three major stressors affecting the population in the Florida Keys: disease, high water temperatures, and ocean acidification? The research within the present study will be the first step in answering this critically important question. The funded project will additionally develop a research-based afterschool program with K-12 students in the Florida Keys and U.S. Virgin Islands that emphasizes an inquiry-based curriculum, STEM research activities, and peer-to-peer mentoring. The information from the present study will help scientists predict the likelihood of species persistence within the lower Florida Keys under future climate-change and ocean-acidification scenarios. Results of this research will also help guide restoration efforts throughout Florida and the Caribbean, and lead to more informative, science-based restoration activities.
Acropora cervicornis dominated shallow-water reefs within the Florida Keys for at least the last half a million years, but the population has recently declined due to multiple stressors. Understanding the current population level of resilience to three major threats - disease outbreaks, high water temperatures, and ocean acidification conditions - is critical for the preservation of this threatened species. Results from the present study will answer the primary research question: will representative genotypes from the lower Florida Keys provide enough phenotypic variation for this threatened species to survive in the future? The present proposal will couple controlled laboratory challenge experiments with field data and modeling applications, and collaborate with local educators to fulfill five objectives: 1) identify A. cervicornis genotypes resistant to disease, 2) identify A. cervicornis genotypes resilient to high water temperature and ocean acidification conditions, 3) quantify how high water temperature and ocean acidification conditions impact disease dynamics on A. cervicornis; 4) determine tradeoffs in life-history traits because of resilience factors; and 5) apply a trait-based model, which will predict genotypic structure of a population under different environmental scenarios.";
    String projects_0_end_date "2020-05";
    String projects_0_geolocation "Florida Keys, Summerland Key, FL  24.563595°, -81.278572°";
    String projects_0_name "CAREER: Applying phenotypic variability to identify resilient Acropora cervicornis genotypes in the Florida Keys";
    String projects_0_project_nid "642850";
    String projects_0_start_date "2015-04";
    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 "This dataset contains Acropora cervicornis buoyant weight measurements from different pH and temperature treatments. The experiments were conducted in tanks at Summerland Key, Florida (24.6616,-81.4538) July to September of 2017.";
    String title "Acropora cervicornis buoyant weight measurements under different pH and temperature treatments from experiments at Summerland Key, Florida from July to September 2017";
    String version "1";
    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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