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Dataset Title:  Host-symbiont respiration related to symbiont density; anemones from Key Largo
from (AnemoneOA project)
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_649708)
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 {
  sample {
    String bcodmo_name "sample";
    String description "sample ID number";
    String long_name "Sample";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/ACYC/";
    String units "unitless";
  }
  holobiont_resp_total {
    Float32 _FillValue NaN;
    Float32 actual_range 0.2603, 1.6616;
    String bcodmo_name "respiration";
    String description "total holobiont (anemone)respiration";
    String long_name "Holobiont Resp Total";
    String units "micromoles of oxygen per hour";
  }
  prot_normal_resp {
    Float32 _FillValue NaN;
    Float32 actual_range 0.6121, 1.9819;
    String bcodmo_name "respiration";
    String description "Host protein-normalised holobiont respiration";
    String long_name "Prot Normal Resp";
    String units "micromoles of oxygen per hour per milligram protein";
  }
  host_CS_activity_product_total {
    Float32 _FillValue NaN;
    Float32 actual_range 0.014, 0.1088;
    String bcodmo_name "metabolic_enzyme";
    String description "Total host citrate synthase activity; the product of host citrate synthase activity and total host protein";
    String long_name "Host CS Activity Product Total";
    String units "Units per milligram protein X milligrams";
  }
  host_CS_activity {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0343, 0.1794;
    String bcodmo_name "metabolic_enzyme";
    String description "Host citrate synthase specific activity";
    String long_name "Host CS Activity";
    String units "units per milligram protein";
  }
  total_host_protein {
    Float32 _FillValue NaN;
    Float32 actual_range 0.1369, 2.1751;
    String bcodmo_name "unknown";
    String description "Total host protein";
    String long_name "Total Host Protein";
    String units "milligrams";
  }
  symb_CS_activity {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0334, 0.1677;
    String bcodmo_name "metabolic_enzyme";
    String description "Symbiont citrate synthase specific activity";
    String long_name "Symb CS Activity";
    String units "Units per milligram protein";
  }
  total_anemone_CS_activity {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0144, 0.1199;
    String bcodmo_name "metabolic_enzyme";
    String description "Total holobiont citrate synthase activity";
    String long_name "Total Anemone CS Activity";
    String units "Units";
  }
  host_DNA_total {
    Float64 _FillValue NaN;
    Float64 actual_range 0.104517579, 18.21235118;
    String bcodmo_name "unknown";
    String description "Total host DNA content";
    String long_name "Host DNA Total";
    String units "micrograms";
  }
  host_symb_dens_normal {
    Float32 _FillValue NaN;
    Float32 actual_range 1.0364, 13.3863;
    String bcodmo_name "abundance";
    String description "Host protein-normalised symbiont density";
    String long_name "Host Symb Dens Normal";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P03/current/B070/";
    String units "million cells per mg protein";
  }
  symb_biomass_fraction {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0291, 0.2336;
    String bcodmo_name "unknown";
    Float64 colorBarMaximum 1.0;
    Float64 colorBarMinimum 0.0;
    String description "Symbiont biomass fraction (calculated as total symbiont protein [mg]/total host+symbiont protein [mg])";
    String long_name "Symb Biomass Fraction";
    String units "dimensionless";
  }
  symb_respir_fraction {
    Float32 _FillValue NaN;
    Float32 actual_range 0.00665, 0.1981;
    String bcodmo_name "unknown";
    Float64 colorBarMaximum 1.0;
    Float64 colorBarMinimum 0.0;
    String description "Symbiont respiration fraction (calculated as total symbiont citrate synthase activity [U]/total host+symbiont citrate synthase activity [U])";
    String long_name "Symb Respir Fraction";
    String units "dimensionless";
  }
  genome_ratio_CO1 {
    Float32 _FillValue NaN;
    Float32 actual_range 20.2126, 406.0552;
    String bcodmo_name "unknown";
    String description "Mitochondrial:nuclear genome ratio calculated using CO1 (QiaAmp DNA Mini Kit)";
    String long_name "Genome Ratio CO1";
    String units "dimensionless";
  }
  genome_ratio_AT96 {
    Float32 _FillValue NaN;
    Float32 actual_range 13.1141, 395.0889;
    String bcodmo_name "unknown";
    String description "Mitochondrial:nuclear genome ratio calculated using ATP6 (QiaAmp DNA Mini Kit)";
    String long_name "Genome Ratio AT96";
    String units "dimensionless";
  }
  genome_ratio_CO1_Pro {
    Float32 _FillValue NaN;
    Float32 actual_range 50.8763, 352.7607;
    String bcodmo_name "unknown";
    String description "Mitochondrial:nuclear genome ratio calculated using CO1 (Promega Wizard Kit)";
    String long_name "Genome Ratio CO1 Pro";
    String units "dimensionless";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv";
    String acquisition_description "Full details of the experimental design are provided in Hawkins et al., 2016";
    String awards_0_award_nid "628966";
    String awards_0_award_number "EF-1316055";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1316055";
    String awards_0_funder_name "NSF Emerging Frontiers Division";
    String awards_0_funding_acronym "NSF EF";
    String awards_0_funding_source_nid "392";
    String awards_0_program_manager "Irwin Forseth";
    String awards_0_program_manager_nid "520504";
    String cdm_data_type "Other";
    String comment 
"Anemone host and symbiont respiration 
   per symbiont density in laboratory setting 
   Fresh anemones from Key Largo 
   M. Warner, PI 
    CS=Citrate Synthase 
   Version 14 June 2016";
    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 "2016-06-17T14:55:35Z";
    String date_modified "2019-07-02T15:44:44Z";
    String defaultDataQuery "&time<now";
    String doi "10.1575/1912/bco-dmo.649708.1";
    String history 
"2020-08-10T06:27:13Z (local files)
2020-08-10T06:27:13Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_649708.das";
    String infoUrl "https://www.bco-dmo.org/dataset/649708";
    String institution "BCO-DMO";
    String instruments_0_dataset_instrument_description "Used to visualize cells' chlorophyll a fluorescence.  [EVOS system, ThermoFisher (Life Technologies), Waltham, MA, USA; excitation: 628 ± 20 nm, emission: 692 ± 20 nm].";
    String instruments_0_dataset_instrument_nid "708840";
    String instruments_0_description "Instruments that generate enlarged images of samples using the phenomena of fluorescence and phosphorescence instead of, or in addition to, reflection and absorption of visible light. Includes conventional and inverted instruments.";
    String instruments_0_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/LAB06/";
    String instruments_0_instrument_name "Microscope-Fluorescence";
    String instruments_0_instrument_nid "695";
    String instruments_0_supplied_name "fluorescence microscope";
    String instruments_1_acronym "Hemocytometer";
    String instruments_1_dataset_instrument_description "Used along with fluorescence microscope to quantify microbial densities.";
    String instruments_1_dataset_instrument_nid "708835";
    String instruments_1_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_1_instrument_name "Hemocytometer";
    String instruments_1_instrument_nid "704";
    String instruments_1_supplied_name "Improved Neubauer hemocytometer";
    String instruments_2_acronym "Spectrophotometer";
    String instruments_2_dataset_instrument_description "ThermoFisher, Waltham, MA, USA";
    String instruments_2_dataset_instrument_nid "708844";
    String instruments_2_description "An instrument used to measure the relative absorption of electromagnetic radiation of different wavelengths in the near infra-red, visible and ultraviolet wavebands by samples.";
    String instruments_2_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/LAB20/";
    String instruments_2_instrument_name "Spectrophotometer";
    String instruments_2_instrument_nid "707";
    String instruments_2_supplied_name "NanoDrop spectrophotometer";
    String instruments_3_dataset_instrument_description "an oxygen sensitive optode (Fibox 4, PreSens Gmbh, Regensburg, Germany).";
    String instruments_3_dataset_instrument_nid "708834";
    String instruments_3_description "An optode or optrode is an optical sensor device that optically measures a specific substance usually with the aid of a chemical transducer.";
    String instruments_3_instrument_name "Optode";
    String instruments_3_instrument_nid "727";
    String instruments_3_supplied_name "Oxygen sensitive optode";
    String instruments_4_acronym "Thermal Cycler";
    String instruments_4_dataset_instrument_description "AB-7500 real-time QPCR system [ThermoFisher (Applied Biosystems), Waltham, MA, USA], with the following cycling conditions: 94◦ C for 10 min, followed by 40 cycles of 94◦C for 15 s, 60◦C for 1 min, and 72◦C for 15 s.";
    String instruments_4_dataset_instrument_nid "708845";
    String instruments_4_description 
"General term for a laboratory apparatus commonly used for performing polymerase chain reaction (PCR). The device has a thermal block with holes where tubes with the PCR reaction mixtures can be inserted. The cycler then raises and lowers the temperature of the block in discrete, pre-programmed steps.

(adapted from http://serc.carleton.edu/microbelife/research_methods/genomics/pcr.html)";
    String instruments_4_instrument_name "PCR Thermal Cycler";
    String instruments_4_instrument_nid "471582";
    String instruments_4_supplied_name "ThermoFisher QPCR system";
    String instruments_5_dataset_instrument_description "Measured baseline absorbance at 412nm. (Fluostar Omega, BMG, Cary, NC, USA)";
    String instruments_5_dataset_instrument_nid "743373";
    String instruments_5_description "Plate readers (also known as microplate readers) are laboratory instruments designed to detect biological, chemical or physical events of samples in microtiter plates. They are widely used in research, drug discovery, bioassay validation, quality control and manufacturing processes in the pharmaceutical and biotechnological industry and academic organizations. Sample reactions can be assayed in 6-1536 well format microtiter plates. The most common microplate format used in academic research laboratories or clinical diagnostic laboratories is 96-well (8 by 12 matrix) with a typical reaction volume between 100 and 200 uL per well. Higher density microplates (384- or 1536-well microplates) are typically used for screening applications, when throughput (number of samples per day processed) and assay cost per sample become critical parameters, with a typical assay volume between 5 and 50 µL per well. Common detection modes for microplate assays are absorbance, fluorescence intensity, luminescence, time-resolved fluorescence, and fluorescence polarization. From: https://en.wikipedia.org/wiki/Plate_reader, 2014-09-0-23.";
    String instruments_5_instrument_name "plate reader";
    String instruments_5_instrument_nid "528693";
    String instruments_5_supplied_name "microplate reader";
    String keywords "activity, anemone, at96, bco, bco-dmo, biological, biomass, chemical, co1, data, dataset, dens, dmo, dna, erddap, fraction, genome, genome_ratio_AT96, genome_ratio_CO1, genome_ratio_CO1_Pro, holobiont, holobiont_resp_total, host, host_CS_activity, host_CS_activity_product_total, host_DNA_total, host_symb_dens_normal, management, normal, oceanography, office, preliminary, pro, product, prot, prot_normal_resp, protein, ratio, resp, respir, sample, symb, symb_biomass_fraction, symb_CS_activity, symb_respir_fraction, total, total_anemone_CS_activity, total_host_protein";
    String license "https://www.bco-dmo.org/dataset/649708/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/649708";
    String param_mapping "{'649708': {}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/649708/parameters";
    String people_0_affiliation "University of Delaware";
    String people_0_person_name "Mark E. Warner";
    String people_0_person_nid "51387";
    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 "Ms Dicky Allison";
    String people_1_person_nid "50382";
    String people_1_role "BCO-DMO Data Manager";
    String people_1_role_type "related";
    String project "AnemoneOA";
    String projects_0_acronym "AnemoneOA";
    String projects_0_description 
"The projected rise in carbon dioxide (CO2) in the atmosphere is considered a primary threat to marine systems throughout the world due to both ocean acidification and rising ocean temperatures. Coral reefs are very sensitive to these projected changes in the earth's climate, with continued losses in growth as well as disruption (also known as bleaching) in the symbiotic relationship between the algae (Symbiodinium) living within a diversity of host animals, including stony corals, soft corals and sea anemones. While much information has been gleaned as to how acidification may affect stony corals, considerably less is known about the interactive effects of acidification and temperature to other symbiotic anthozoans.
To this end, this proposal will investigate the long-term impacts of elevated CO2 and temperature on the model sea anemone, Aiptasia pallida, while harboring four different genotypes of Symbiodinium. The primary goals of this project are (1) to determine the sensitivity and capacity for acclimation in molecular and physiological processes while exposed to elevated CO2 and temperature, and (2) to assess the degree to which acclimated adult animals may confer (or transfer) an imprinted physiological characteristic to the next generation of asexual offspring. A series of long-term experiments will be conducted with each animal/algal combination (holobiont) in order to collect initial (3 month) stress markers and genomic data and then follow animal response and asexual reproduction through several generations for one year. The possibility for enhanced resilience or acclimation will be measured by tracking the recovery of each holobiont, followed by repeated exposure to elevated temperature while held in high CO2. This project will tease apart fine scale mechanisms of stress, acclimation, or amelioration that may vary as a function of algal genotype and host animal response, and the degree to which environmental imprinting may pre-acclimate propagules. Project results will provide information regarding how future acidification and warming will affect cnidarian-algal symbioses, and the fundamental profile of their flexibility in stress response processes across organismal, metabolic, genomic and epigenetic scales.";
    String projects_0_end_date "2016-06";
    String projects_0_geolocation "Lewes, Delaware";
    String projects_0_name "Ocean Acidification: Understanding the Impact of CO2 and Temperature on the Physiological, Genetic, and Epigenetic Response of a Model Sea Anemone System with Different Symbionts";
    String projects_0_project_nid "628967";
    String projects_0_start_date "2013-07";
    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 "Host-symbiont respiration related to symbiont density; anemones from Key Largo from (AnemoneOA project)";
    String title "Host-symbiont respiration related to symbiont density; anemones from Key Largo from (AnemoneOA project)";
    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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