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Dataset Title:  Acropora cervicornis growth rates under different pH and temperature
treatments from experiments at Summerland Key, Florida in September of 2016
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_712377)
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 {
  pH {
    String bcodmo_name "pH";
    String description "Treatment pH level; ambient = 8.1 pH; hCO2 = 7.7 pH";
    String long_name "pH";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/PHXXZZXX/";
    String units "unitless";
  }
  Temp {
    Byte _FillValue 127;
    Byte actual_range 27, 31;
    String bcodmo_name "temperature";
    String description "Treatment temperature level";
    String long_name "Temperature";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/TEMPP901/";
    String units "Celsius";
  }
  Tank {
    Byte _FillValue 127;
    Byte actual_range 1, 20;
    String bcodmo_name "tank";
    String description "Tank number that held the particular coral fragment";
    String long_name "Tank";
    String units "unitless";
  }
  Chamber {
    String bcodmo_name "treatment";
    String description "Chamber number that held the coral fragment during the light and dark cycle";
    String long_name "Chamber";
    String units "unitless";
  }
  Genotype {
    Byte _FillValue 127;
    Byte actual_range 1, 63;
    String bcodmo_name "sample_descrip";
    String description "Genotype number of the coral animal for each fragment";
    String long_name "Genotype";
    String units "unitless";
  }
  Cycle {
    String bcodmo_name "treatment";
    String description "Characterizes whether the coral was exposed to light or held in the dark prior to final measurements";
    String long_name "Cycle";
    String units "unitless";
  }
  Calcification {
    Float32 _FillValue NaN;
    Float32 actual_range -0.307, 1.594;
    String bcodmo_name "calcification";
    String description "Rate at which the coral is utilizing calcium carbonate for skeletal growth";
    String long_name "Calcification";
    String units "micromoles of calcium carbonate per centimeter squred per hour (CaCO3/cm2/h)";
  }
  Date {
    String bcodmo_name "date";
    String description "Date in format 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";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv";
    String acquisition_description 
"Physiological Methods
 
Photosynthesis, respiration, and calcification measurements were performed on
each fragment using 300 mL temperature-controlled respirometry chambers filled
with seawater from the treatment aquaria that was continuously stirred with a
magnetic stir bar. \\u00a0The chambers were used to assess the rates of
respiration (Rd) in the dark and rates of photosynthesis (Pn) and
calcification in the light. \\u00a0Light was supplied by a series of blue and
red LEDs with adjustable intensity (150 uMol quanta m-2 sec-1). \\u00a0Water
samples were taken from each chamber prior to a cycle and also at the end of
both dark and light incubations (60 minutes each) for measurements of pHT (pH
on the total scale) and total alkalinity (AT) as described in Martin and
Gattuso (2009). \\u00a0
 
Calcification - Total alkalinity (TA) values were measured using an automatic
potentiometric titrator (Metrohm 807 Titrando, Riverview, FL) to the second
end point of a 15.3-g accurately weighed seawater sample. \\u00a0Total
alkalinity values were then computed using the Gran equation (DOE, 1994) with
pH values lower than 3.9 for creating the Gran plot. The pH electrodes
(Metrohm 807 Titrando) were calibrated daily as described above. \\u00a0The
acid titrant concentration was 0.05N HCl (JT Baker, Phillipsburg, NJ).
\\u00a0Alkalinity was calculated using the first derivative of the curve for
the evaluation of the exact end point. \\u00a0Standards for total seawater
alkalinity and provided by Dickson were run daily (Dickson, 2007). \\u00a0The
differences between duplicate samples and standards were less than 5 uEq kg-1
(for calibration of the titrator, differences were measured between triplicate
samples). \\u00a0Water samples were analyzed immediately or stored in darkness
at 4C and processed within 24 hours of collection. \\u00a0
 
Dickson AG, Sabine CL, and Christian JR (2007) Guide to best practices for
ocean CO2 measurements: PICES Special Publication. 3, 191 p.
 
Martin S and Gattuso J-P (2009) Response of Mediterranean coralline algae to
ocean acidification and elevated temperature. Glob Change Biol
15:2089-2100.\\u00a0  
 Marubini F and Thake B (1999) Bicarbonate addition promotes coral growth.
Limnol and Oceanogr 44: 716-720.
 
Riebesell U, Fabry VJ, Hansson L, and Gattuso JP (2010) Guide to best
practices for ocean acidification research and data reporting. European
Commission, European Research Area. Brussels. 258 p
 
\\u00a0";
    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 
"Acropora cervicornis calcification 
   PI: Erinn Muller 
   data version: 2017-10-05";
    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 "2017-08-08T15:40:41Z";
    String date_modified "2019-10-18T16:32:43Z";
    String defaultDataQuery "&time<now";
    String doi "10.1575/1912/bco-dmo.712377.1";
    String history 
"2020-12-01T12:00:10Z (local files)
2020-12-01T12:00:10Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_712377.das";
    String infoUrl "https://www.bco-dmo.org/dataset/712377";
    String institution "BCO-DMO";
    String instruments_0_acronym "YSI ProPlus";
    String instruments_0_dataset_instrument_description "temperature measured with YSI Pro 2030";
    String instruments_0_dataset_instrument_nid "716203";
    String instruments_0_description "The YSI Professional Plus handheld multiparameter meter provides for the measurement of a variety of combinations for dissolved oxygen, conductivity, specific conductance, salinity, resistivity, total dissolved solids (TDS), pH, ORP, pH/ORP combination, ammonium (ammonia), nitrate, chloride and temperature. More information from the manufacturer.";
    String instruments_0_instrument_name "YSI Professional Plus Multi-Parameter Probe";
    String instruments_0_instrument_nid "666";
    String instruments_0_supplied_name "YSI Pro 2030";
    String instruments_1_acronym "pH Sensor";
    String instruments_1_dataset_instrument_nid "716206";
    String instruments_1_description "General term for an instrument that measures the pH or how acidic or basic a solution is.";
    String instruments_1_instrument_name "pH Sensor";
    String instruments_1_instrument_nid "674";
    String instruments_1_supplied_name "Mettler Toledo SevenGo Pro";
    String instruments_2_acronym "Automatic titrator";
    String instruments_2_dataset_instrument_nid "712520";
    String instruments_2_description "Instruments that incrementally add quantified aliquots of a reagent to a sample until the end-point of a chemical reaction is reached.";
    String instruments_2_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/LAB12/";
    String instruments_2_instrument_name "Automatic titrator";
    String instruments_2_instrument_nid "682";
    String instruments_2_supplied_name "Metrohm 807 Titrando";
    String keywords "bco, bco-dmo, biological, calcification, chamber, chemical, cycle, data, dataset, date, dmo, erddap, genotype, management, oceanography, office, preliminary, tank, Temp, temperature, time";
    String license "https://www.bco-dmo.org/dataset/712377/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/712377";
    String param_mapping "{'712377': {}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/712377/parameters";
    String people_0_affiliation "Mote Marine Laboratory";
    String people_0_affiliation_acronym "Mote";
    String people_0_person_name "Dr 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 "Amber York";
    String people_1_person_nid "643627";
    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 
"ABSTRACT
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 calcification data from experiments conducted in tanks at Summerland Key, Florida (24.6616,-81.4538) between 2016-09-02 and 2016-09-10 with corals from a nursery located near Looe Key Reef (24.5636, -81.2786).";
    String title "Acropora cervicornis growth rates under different pH and temperature treatments from experiments at Summerland Key, Florida in September of 2016";
    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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