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Dataset Title:  Chlorophyll a per unit biomass in Ulva lactuca under ocean acidification (OA)
conditions (Seaweed OA Resilience project)
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_732438)
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 {
  Label {
    String description "Trial number-pot number.frozen tissue replicate";
    String ioos_category "Unknown";
    String long_name "Label";
    String units "unitless";
  }
  pCO2_avg {
    Int16 _FillValue 32767;
    Int16 actual_range 248, 1001;
    String description "Average pCO2 partial pressure in seawater tanks";
    String ioos_category "CO2";
    String long_name "P CO2 Avg";
    String units "microatmospheres (�atm)";
  }
  pCO2_sd {
    Float32 _FillValue NaN;
    Float32 actual_range 36.22, 1827.8;
    Float64 colorBarMaximum 50.0;
    Float64 colorBarMinimum 0.0;
    String description "Variability of pCO2 partial pressure - standard deviation";
    String ioos_category "Statistics";
    String long_name "P CO2 Sd";
    String units "microatmospheres (�atm)";
  }
  Fresh_Wt {
    String description "Fresh weight of tissue sample prior to deep freeze";
    String ioos_category "Unknown";
    String long_name "Fresh Wt";
    String units "grams";
  }
  DMSO_A665 {
    String description "Absorbance of light by ground Ulva tissue at 665nm in 1.25 ml of an 80% DMSO solution in water";
    String ioos_category "Unknown";
    String long_name "DMSO A665";
    String units "unitless";
  }
  Methanol_A668 {
    String description "Absorbance of light by ground Ulva tissue at 668nm in 6 ml methanol";
    String ioos_category "Unknown";
    String long_name "Methanol A668";
    String units "unitless";
  }
  Methanol_A635 {
    String description "Absorbance of light by ground Ulva tissue at 635nm in 6 ml methanol";
    String ioos_category "Unknown";
    String long_name "Methanol A635";
    String units "unitless";
  }
  DMSO_ext {
    String description "Chlorophyll a extracted in DMSO";
    String ioos_category "Unknown";
    String long_name "DMSO Ext";
    String units "milligram/liter (mg/L)";
  }
  Meth_ext {
    String description "Chlorophyll a in pooled extracts of 12 ml of methanol";
    String ioos_category "Unknown";
    String long_name "Meth Ext";
    String units "milligram/liter (mg/L)";
  }
  Total_chl_mg {
    String description "Total chlorophyll a extracted from ground tissue";
    String ioos_category "Unknown";
    String long_name "Total Chl Mg";
    String units "milligrams (mg)";
  }
  chl_a {
    Float64 colorBarMaximum 30.0;
    Float64 colorBarMinimum 0.03;
    String colorBarScale "Log";
    String description "Chlorophyll a concentration per unit biomass";
    String ioos_category "Ocean Color";
    String long_name "Concentration Of Chlorophyll In Sea Water";
    String units "milligrams/gram (mg/g)";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv";
    String acquisition_description 
"Culture pots were placed in large thermally insulated coolers in a
temperature-controlled water bath at 15\\u00b0 C under saturating illumination
of ~550 \\u00b5moles photons/m^2/s on a 12:12 L:D cycle. pCO2 treatments were
supplied to closed culture pots by use of a gas mixing system combining
nitrogen, oxygen and carbon dioxide to specific CO2 partial pressures, 20.9%
oxygen and the balance being nitrogen.
 
Chlorophyll a was extracted from Ulva tissue following the procedure described
in Duncan and Harrison (1982). Chlorophyll a concentrations were measured
using a Shimadzu UV-2450 UV-visible spectrophotometer.";
    String awards_0_award_nid "55177";
    String awards_0_award_number "OCE-1316198";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward?AWD_ID=1316198";
    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 
"Chl_a - Ulva 
   Chlorophyll a per unit biomass in Ulva lactuca under ocean acidification conditions 
   PI's: J. Kubler, S. Dudgeon (CSU-Northbridge) 
   version: 2018-03-22";
    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 "2018-03-28T12:21:30Z";
    String date_modified "2019-06-03T18:19:55Z";
    String defaultDataQuery "&time";
    String doi "10.1575/1912/bco-dmo.732438.1";
    String history 
"2019-11-21T11:58:50Z (local files)
2019-11-21T11:58:50Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_732438.das";
    String infoUrl "https://www.bco-dmo.org/dataset/732438";
    String institution "BCO-DMO";
    String instruments_0_acronym "UV Spectrophotometer-Shimadzu";
    String instruments_0_dataset_instrument_description "Used to measure chlorophyll a�concentration.";
    String instruments_0_dataset_instrument_nid "732449";
    String instruments_0_description "The Shimadzu UV Spectrophotometer is manufactured by Shimadzu Scientific Instruments (ssi.shimadzu.com). Shimadzu manufacturers several models of spectrophotometer; refer to dataset for make/model information.";
    String instruments_0_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/LAB20/";
    String instruments_0_instrument_name "UV Spectrophotometer-Shimadzu";
    String instruments_0_instrument_nid "595";
    String instruments_0_supplied_name "Shimadzu UV-2450 UV-visible spectrophotometer";
    String keywords "a635, a665, a668, average, bco, bco-dmo, biological, carbon, carbon dioxide, chemical, chemistry, chl, chl_a, chlorophyll, co2, color, concentration, concentration_of_chlorophyll_in_sea_water, data, dataset, dioxide, dmo, dmso, DMSO_A665, DMSO_ext, earth, Earth Science > Oceans > Ocean Chemistry > Chlorophyll, erddap, ext, fresh, Fresh_Wt, label, management, meth, Meth_ext, methanol, Methanol_A635, Methanol_A668, ocean, ocean color, oceanography, oceans, office, pCO2_avg, pCO2_sd, preliminary, science, sea, seawater, statistics, total, Total_chl_mg, water";
    String keywords_vocabulary "GCMD Science Keywords";
    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/732438";
    String param_mapping "{'732438': {}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/732438/parameters";
    String people_0_affiliation "California State University Northridge";
    String people_0_affiliation_acronym "CSU-Northridge";
    String people_0_person_name "Dr Janet  E Kubler";
    String people_0_person_nid "51681";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "California State University Northridge";
    String people_1_affiliation_acronym "CSU-Northridge";
    String people_1_person_name "Dr Steve Dudgeon";
    String people_1_person_nid "51682";
    String people_1_role "Co-Principal Investigator";
    String people_1_role_type "originator";
    String people_2_affiliation "Woods Hole Oceanographic Institution";
    String people_2_affiliation_acronym "WHOI BCO-DMO";
    String people_2_person_name "Nancy Copley";
    String people_2_person_nid "50396";
    String people_2_role "BCO-DMO Data Manager";
    String people_2_role_type "related";
    String project "Ocean Acidification: Scope for Resilience to Ocean Acidification in Macroalgae";
    String projects_0_acronym "Seaweed OA Resilience";
    String projects_0_description "Benthic macroalgae contribute to intensely productive near shore  ecosystems and little is known about the potential effects of ocean  acidification on non-calcifying macroalgae. K�bler and Dudgeon will test  hypotheses about two macroalgae, Ulva spp. and Plocamium cartilagineum,  which, for different reasons, are hypothesized to be more productive  and undergo ecological expansions under predicted changes in ocean  chemistry. They have designed laboratory culture-based experiments to  quantify the scope for response to ocean acidification in Plocamium,  which relies solely on diffusive uptake of CO2, and populations of Ulva  spp., which have an inducible concentrating mechanism (CCM). The  investigators will culture these algae in media equilibrated at 8  different pCO2 levels ranging from 380 to 940 ppm to address three key  hypotheses. The first is that macroalgae (such as Plocamium  cartilagineum) that are not able to acquire inorganic carbon in changed  form will benefit, in terms of photosynthetic and growth rates, from  ocean acidification. There is little existing data to support this  common assumption. The second hypothesis is that enhanced growth of Ulva  sp. under OA will result from the energetic savings from down  regulating the CCM, rather than from enhanced photosynthesis per se.  Their approach will detect existing genetic variation for adaptive  plasticity. The third key hypothesis to be addressed in short-term  culture experiments is that there will be a significant interaction  between ocean acidification and nitrogen limited growth of Ulva spp.,  which are indicator species of eutrophication. K�bler and Dudgeon will  be able to quantify the individual effects of ocean acidification and  nitrogenous nutrient addition on Ulva spp. and also, the synergistic  effects, which will inevitably apply in many highly productive, shallow  coastal areas. The three hypotheses being addressed have been broadly  identified as urgent needs in our growing understanding of the impacts  of ocean acidification.";
    String projects_0_end_date "2016-05";
    String projects_0_geolocation "Temperate coastal waters of the USA (30 - 45 N latitude, -66 to -88 W and -117 to -125 W longitude)";
    String projects_0_name "Ocean Acidification: Scope for Resilience to Ocean Acidification in Macroalgae";
    String projects_0_project_nid "2275";
    String projects_0_start_date "2013-06";
    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 summary "This dataset reports the chlorophyll a concentration per unit biomass of Ulva lactuca grown in closed culture pots at varying pCO2 levels.";
    String title "Chlorophyll a per unit biomass in Ulva lactuca under ocean acidification (OA) conditions (Seaweed OA Resilience project)";
    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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