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Dataset Title:  Chlorophyll measurements from HHQ experiments conducted during the MesoHux
mesocosm experiment, May 2017, Bergen, Norway
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_753388)
Information:  Summary ? | License ? | ISO 19115 | Metadata | Background (external link) | Subset | 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 {
  Date {
    String description "sampling date formatted as Mon dd yyyy";
    String ioos_category "Time";
    String long_name "Date";
    String units "unitless";
  }
  Sample {
    String description "sample identifier";
    String ioos_category "Unknown";
    String long_name "Sample";
    String units "unitless";
  }
  Experiment_num {
    Byte _FillValue 127;
    Byte actual_range 1, 8;
    String description "experiment number";
    String ioos_category "Unknown";
    String long_name "Experiment Num";
    String units "unitless";
  }
  time2 {
    Byte _FillValue 127;
    Byte actual_range 0, 24;
    String description "time since start of experiment";
    String ioos_category "Time";
    String long_name "Time";
    String units "hours";
  }
  Replication {
    Byte _FillValue 127;
    Byte actual_range 1, 3;
    String description "replicate number";
    String ioos_category "Unknown";
    String long_name "Replication";
    String units "unitless";
  }
  Volume_Filtered_mL {
    Int16 _FillValue 32767;
    Int16 actual_range 100, 155;
    String description "volume filtered";
    String ioos_category "Unknown";
    String long_name "Volume Filtered M L";
    String units "milliliters (mL)";
  }
  Extract_Volume_mL {
    Byte _FillValue 127;
    Byte actual_range 6, 6;
    String description "volume extracted";
    String ioos_category "Unknown";
    String long_name "Extract Volume M L";
    String units "milliliters (mL)";
  }
  Dilution_Factor {
    Byte _FillValue 127;
    Byte actual_range 1, 1;
    String description "dilution factor";
    String ioos_category "Unknown";
    String long_name "Dilution Factor";
    String units "unitless";
  }
  F_o {
    Float32 _FillValue NaN;
    Float32 actual_range 11.4, 176.0;
    String description "initial fluorescence reading";
    String ioos_category "Unknown";
    String long_name "F O";
    String units "Relative Fluorescence Units (RFU)";
  }
  F_o_blank {
    Float32 _FillValue NaN;
    Float32 actual_range 11.4, 176.0;
    String description "initial fluorescence of control blank";
    String ioos_category "Unknown";
    String long_name "F O Blank";
    String units "Relative Fluorescence Units (RFU)";
  }
  F_a {
    Float32 _FillValue NaN;
    Float32 actual_range 6.49, 96.9;
    String description "fluorescence after acidification";
    String ioos_category "Unknown";
    String long_name "F A";
    String units "Relative Fluorescence Units (RFU)";
  }
  F_a_blank {
    Float32 _FillValue NaN;
    Float32 actual_range 6.49, 96.9;
    String description "fluorescence of control blank after acidification";
    String ioos_category "Unknown";
    String long_name "F A Blank";
    String units "Relative Fluorescence Units (RFU)";
  }
  Total_chl_with_phaeo {
    Float32 _FillValue NaN;
    Float32 actual_range 0.5, 6.77;
    String description "total chlorophyll including phaeophytin";
    String ioos_category "Unknown";
    String long_name "Total Chl With Phaeo";
    String units "micrograms chlorophyll/Liter (ug/L)";
  }
  Total_Chl_no_phaeo {
    Float32 _FillValue NaN;
    Float32 actual_range 0.42, 6.42;
    String description "total chlorophyll NOT including phaeophytin";
    String ioos_category "Unknown";
    String long_name "Total Chl No Phaeo";
    String units "micrograms chlorophyll/Liter (ug/L)";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv";
    String acquisition_description 
"Water samples for chlorophyll extraction were collected either from the
mesocosms via a 5 L Niskin or subsampled from experimental bottles.
Chlorophyll samples were filtered in triplicate through a 25mm Glass Fiber
Filter (GFF), and immediately extracted in 6 mL of ethanol for 12-18 hours in
the dark at room temperature. After extraction, filters were removed from the
sample, and the fluorescence of the sample was read on a Turner AU10. The
sample was then acidified with 1 drop of 10% HCL and re-read on the same
instrument. The fluorometer was calibrated prior to using with a chlorophyll
standard purchased from Sigma.\\u00a0
 
Mesocosm treatment for all HHQ experiments was as follows:  
 Redfield: N:P added in a 16:1 ratio during the first 3 days of the
experiment, no shading
 
HHQ treatments here are as follows:  
 High HHQ - 100 ng mL-1 (410 uM) added to triplicate 5L bottles.  
 DMSO control - equivalent (v:v) DMSO added to triplicate 5L bottles.
 
\\u00a0All bottles were incubated for 24h in a flow-through tank, that was
shaded to mimic in situ conditions. Chlorophyll samples were taken at T0 and
T24 for all experiments.
 
Data were processed in Excel with statistics run in Excel, R, or Matlab.";
    String awards_0_award_nid "709952";
    String awards_0_award_number "OCE-1657898";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1657898";
    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 "Dr David  L. Garrison";
    String awards_0_program_manager_nid "50534";
    String cdm_data_type "Other";
    String comment 
"HHQ Chlorophyll 
     from MesoHux mesocosm experiment, May 2017, Bergen, Norway 
   PI: E. Harvey (SkIO) 
   version: 2019-01-23";
    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 2.2d  13 Jun 2019";
    String date_created "2019-01-23T15:43:33Z";
    String date_modified "2019-03-14T19:44:45Z";
    String defaultDataQuery "&time";
    String doi "10.1575/1912/bco-dmo.753388.1";
    String history 
"2019-08-19T19:18:54Z (local files)
2019-08-19T19:18:54Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_753388.das";
    String infoUrl "https://www.bco-dmo.org/dataset/753388";
    String institution "BCO-DMO";
    String instruments_0_acronym "Niskin bottle";
    String instruments_0_dataset_instrument_description "Used to collect water samples.";
    String instruments_0_dataset_instrument_nid "753396";
    String instruments_0_description "A Niskin bottle (a next generation water sampler based on the Nansen bottle) is a cylindrical, non-metallic water collection device with stoppers at both ends.  The bottles can be attached individually on a hydrowire or deployed in 12, 24 or 36 bottle Rosette systems mounted on a frame and combined with a CTD.  Niskin bottles are used to collect discrete water samples for a range of measurements including pigments, nutrients, plankton, etc.";
    String instruments_0_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L22/current/TOOL0412/";
    String instruments_0_instrument_name "Niskin bottle";
    String instruments_0_instrument_nid "413";
    String instruments_0_supplied_name "5 L Niskin";
    String instruments_1_acronym "Fluorometer";
    String instruments_1_dataset_instrument_nid "753399";
    String instruments_1_description "A fluorometer or fluorimeter is a device used to measure parameters of fluorescence: its intensity and wavelength distribution of emission spectrum after excitation by a certain spectrum of light. The instrument is designed to measure the amount of stimulated electromagnetic radiation produced by pulses of electromagnetic radiation emitted into a water sample or in situ.";
    String instruments_1_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/113/";
    String instruments_1_instrument_name "Fluorometer";
    String instruments_1_instrument_nid "484";
    String instruments_1_supplied_name "Turner AU10 fluorometer";
    String keywords "bco, bco-dmo, biological, blank, chemical, chl, chlorophyll, data, dataset, date, dilution, Dilution_Factor, dmo, erddap, experiment, Experiment_num, extract, Extract_Volume_mL, F_a, F_a_blank, F_o, F_o_blank, factor, filtered, management, num, oceanography, office, phaeo, preliminary, replication, sample, time, time2, total, Total_Chl_no_phaeo, Total_chl_with_phaeo, volume, Volume_Filtered_mL, with";
    String license 
"The data may be used and redistributed for free but is not intended
for legal use, since it may contain inaccuracies. Neither the data
Contributor, ERD, NOAA, nor the United States Government, nor any
of their employees or contractors, makes any warranty, express or
implied, including warranties of merchantability and fitness for a
particular purpose, or assumes any legal liability for the accuracy,
completeness, or usefulness, of this information.";
    String metadata_source "https://www.bco-dmo.org/api/dataset/753388";
    String param_mapping "{'753388': {}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/753388/parameters";
    String people_0_affiliation "Skidaway Institute of Oceanography";
    String people_0_affiliation_acronym "SkIO";
    String people_0_person_name "Dr Elizabeth Harvey";
    String people_0_person_nid "645518";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "University of Rhode Island";
    String people_1_affiliation_acronym "URI";
    String people_1_person_name "Dr David Rowley";
    String people_1_person_nid "709954";
    String people_1_role "Co-Principal Investigator";
    String people_1_role_type "originator";
    String people_2_affiliation "Haverford College";
    String people_2_affiliation_acronym "Haveford";
    String people_2_person_name "Dr Kristen E. Whalen";
    String people_2_person_nid "709960";
    String people_2_role "Co-Principal Investigator";
    String people_2_role_type "originator";
    String people_3_affiliation "Woods Hole Oceanographic Institution";
    String people_3_affiliation_acronym "WHOI BCO-DMO";
    String people_3_person_name "Nancy Copley";
    String people_3_person_nid "50396";
    String people_3_role "BCO-DMO Data Manager";
    String people_3_role_type "related";
    String project "Collaborative Research: Building a framework for the role of bacterial-derived chemical signals in mediating phytoplankton population dynamics";
    String projects_0_acronym "HHQSignals";
    String projects_0_description 
"NSF Abstract:
Bacteria and phytoplankton play a central role in the modification and flow of materials and nutrients through the marine environment. While it has been established that interactions between these two domains are complex, the mechanisms that underpin these interactions remain largely unknown. There is increasing recognition, however, that dissolved chemical cues govern these microbial interactions. This project focuses on establishing a mechanistic framework for how bacterially derived signaling molecules influence interactions between phytoplankton and bacteria. The quorum-sensing (QS) molecule, 2-heptyl-4-quinolone (HHQ) will be used as a model compound for these investigations. Previously published work suggests that exposure to very low levels of HHQ results in phytoplankton mortality. Gaining a mechanistic understanding of these ecologically important interactions will help to inform mathematical models for the accurate prediction of the cycling of material through the marine microbial loop. This work initiates a new, hybrid workshop-internship undergraduate research program in chemical ecology, with a focus
Bacteria and phytoplankton play a central role in the modification and flow of materials and nutrients through the marine environment. While it has been established that interactions between these two domains are complex, the mechanisms that underpin these interactions remain largely unknown. There is increasing recognition, however, that dissolved chemical cues govern these microbial interactions. This project focuses on establishing a mechanistic framework for how bacterially derived signaling molecules influence interactions between phytoplankton and bacteria. The quorum-sensing (QS) molecule, 2-heptyl-4-quinolone (HHQ) will be used as a model compound for these investigations. Previously published work suggests that exposure to very low levels of HHQ results in phytoplankton mortality. Gaining a mechanistic understanding of these ecologically important interactions will help to inform mathematical models for the accurate prediction of the cycling of material through the marine microbial loop. This work initiates a new, hybrid workshop-internship undergraduate research program in chemical ecology, with a focus into bacteria-phytoplankton interactions. Undergraduate students participate in an intense summer learning experience where research and field-based exercises are supplemented with short-lecture based modules. Students return to their home institutions and work closely with the PIs to conduct interdisciplinary research relating to the aims and scope of the summer research. This research also provides training and career development to two graduate students and a postdoctoral scientist.
Interactions between phytoplankton and bacteria play a central role in mediating biogeochemical cycling and microbial trophic structure in the ocean. The intricate relationships between these two domains of life are mediated via excreted molecules that facilitate communication and determine competitive outcomes. Despite their predicted importance, identifying these released compounds has remained a challenge. The PIs recently identified a bacterial QS molecule, HHQ, produced by globally distributed marine gamma-proteobacteria, which induces phytoplankton mortality. The PIs therefore hypothesize that bacteria QS signals are critical drivers of phytoplankton population dynamics and, ultimately, biogeochemical fluxes. This project investigates the timing and magnitude of HHQ production, and the physiological and transcriptomic responses of susceptible phytoplankton species to HHQ exposure, and quantifies the influence of HHQ on natural algal and bacterial assemblages. The work connects laboratory and field-based experiments to understand the governance of chemical signaling on marine microbial interactions, and has the potential to yield broadly applicable insights into how microbial interactions influence biogeochemical fluxes in the marine environment.";
    String projects_0_end_date "2020-03";
    String projects_0_geolocation "Bergen, Norway";
    String projects_0_name "Collaborative Research: Building a framework for the role of bacterial-derived chemical signals in mediating phytoplankton population dynamics";
    String projects_0_project_nid "709948";
    String projects_0_start_date "2017-04";
    String publisher_name "Nancy Copley";
    String publisher_role "BCO-DMO Data Manager(s)";
    String sourceUrl "(local files)";
    String standard_name_vocabulary "CF Standard Name Table v29";
    String subsetVariables "Extract_Volume_mL, Dilution_Factor";
    String summary "This dataset includes chlorophyll measurements from HHQ experiments conducted during the MesoHux mesocosm experiment, May 2017, Bergen, Norway. Microbial mesocosms were spiked with 2-heptyl-4-quinolone (HHQ).";
    String title "Chlorophyll measurements from HHQ experiments conducted during the MesoHux mesocosm experiment, May 2017, Bergen, Norway";
    String version "1";
    String xml_source "osprey2erddap.update_xml() v1.5-beta";
  }
}

 

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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