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Dataset Title:  Results from experiment examining effects of 4 different dyes on growth rates
of scleractinian corals; from the Cohen lab at WHOI in Woods Hole, MA (OA
Nutrition and Coral Calcification project)
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_489382)
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 {
  treatment {
    String bcodmo_name "treatment";
    String description "Name of the dye used to mark the coral.";
    String long_name "Treatment";
    String units "dimensionless";
  }
  treatment_abbrev {
    String bcodmo_name "treatment";
    String description "Abbreviation used to identify the treatment type in Holcomb et al. 2013.";
    String long_name "Treatment Abbrev";
    String units "dimensionless";
  }
  rel_growth_during_treatment {
    Float64 _FillValue NaN;
    Float64 actual_range 0.517823968, 1.381243035;
    String bcodmo_name "unknown";
    String description "Relative coral growth rate estimated via alkalinity depletion measurements the day of dye exposure.";
    String long_name "Rel Growth During Treatment";
    String units "dimensionless";
  }
  rel_growth_post_treatment {
    Float64 _FillValue NaN;
    Float64 actual_range 0.737756892, 1.79697093;
    String bcodmo_name "unknown";
    String description "Relative coral growth rate estimated via alkalinity depletion measurements the day after dye exposure.";
    String long_name "Rel Growth Post Treatment";
    String units "dimensionless";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv";
    String acquisition_description 
"Methodology as described in Holcomb et al. (2013):
 
Colonies of the temperate scleractinian coral Astrangia poculata were
collected and processed as previously described. Newly settled polyps and
their associated substratum were attached to slides. The slides with corals
were suspended vertically in a flow-through aquarium receiving 20 micrometers
filtered Vineyard Sound seawater. Corals experienced a temperature range of 14
to 30 degrees C. Aquaria were aerated, and corals were maintained under these
conditions for at least one month prior to use in experiments. A mixture of
brown and white colonies (zooxanthellate and azooxanthellate colonies) was
used for all treatments.
 
For the marking experiments, corals were placed in pre-washed containers with
lids containing ~800 ml of water from the source aquarium. Airstones were
added to each container and each container bubbled continuously. Containers
were held within a water bath with a temperature similar to that of the source
aquarium.
 
One of four dyes was used to mark the coral skeleton: alizarin red S (sodium
salt \\u2013 Alfa Aesar 42040 lot E22R017 \\u2013 referred to as alizarin),
alizarin complexone (Alfa Aesar A16699 lot E8180A), calcein (Alfa Aesar L10255
lot USLF006789), and oxytetracycline HCl (USB 23659 lot 113648).
 
The dye experiments took place from March to October 2009. Growth rates were
estimated via alkalinity depletion measurements the day before (pre-
treatment), the day of (treatment), and the day after (post-treatment) dye
exposure. The alkalinity incubations were about 24 hours in duration (one full
light-dark cycle). Temperatures ranged from 25 to 26 degrees C. Four to seven
corals were used in each treatment, each in a separate incubation container.
Irradiance in each container, measured using a diving-PAM underwater quantum
sensor (WALZ), ranged from 10 to 40 micromoles photons/m^2/sec.
 
Samples for alkalinity were taken from each container about 1 hour after the
corals were added, and once again at the end of the incubation. Salinity and
pH were also measured at the end of each incubation for each container (and at
the start for a sub-set of the containers). Aragonite deposition was assumed
to be the only process affecting alkalinity, with 2 mol alkalinity consumed
per mol of CaCO3 deposited. Alkalinity depletion rates were corrected for
evaporation and background rates measured in the control containers (the
control containers contained no slides).
 
Alkalinity was measured via titration with 0.01 N HCl containing 40.7 g NaCl/l
using a Metrohm Titrando 808 Dosimat and a 730 Sample Changer controlled by
Tiamo software to perform automated normalized Gran titrations of 1 ml
samples.";
    String awards_0_award_nid "54896";
    String awards_0_award_number "OCE-1041106";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1041106";
    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 "David L. Garrison";
    String awards_0_program_manager_nid "50534";
    String cdm_data_type "Other";
    String comment 
"Coral growth (species <i>Astrangia poculata</i>) dye experiments  
 PI: Anne Cohen (WHOI) 
 Contact: Michael Holcomb 
 Version: 31 Jan 2014";
    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 "2014-01-31T20:25:18Z";
    String date_modified "2019-11-14T19:52:03Z";
    String defaultDataQuery "&amp;time&lt;now";
    String doi "10.1575/1912/bco-dmo.489382.1";
    String history 
"2020-08-13T16:47:58Z (local files)
2020-08-13T16:47:58Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_489382.das";
    String infoUrl "https://www.bco-dmo.org/dataset/489382";
    String institution "BCO-DMO";
    String instruments_0_acronym "Benchtop pH Meter";
    String instruments_0_dataset_instrument_description "A Thermo-Orion ROSS 8165BNWP electrode, read to 0.1 mV, was used to measure the pH of each experimental container.";
    String instruments_0_dataset_instrument_nid "489403";
    String instruments_0_description 
"An instrument consisting of an electronic voltmeter and pH-responsive electrode that gives a direct conversion of voltage differences to differences of pH at the measurement temperature.  (McGraw-Hill Dictionary of Scientific and Technical Terms) 
This instrument does not map to the NERC instrument vocabulary term for 'pH Sensor' which measures values in the water column.  Benchtop models are typically employed for stationary lab applications.";
    String instruments_0_instrument_name "Benchtop pH Meter";
    String instruments_0_instrument_nid "681";
    String instruments_0_supplied_name "pH Probe";
    String instruments_1_acronym "Automatic titrator";
    String instruments_1_dataset_instrument_description "Alkalinities were measured via titration with 0.01 N HCl containing 40.7 g NaCl/l using a Metrohm Titrando 808 Dosimat and a 730 Sample Changer controlled by Tiamo software to performautomated normalized Gran titrations of 1 ml samples.";
    String instruments_1_dataset_instrument_nid "489405";
    String instruments_1_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_1_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/LAB12/";
    String instruments_1_instrument_name "Automatic titrator";
    String instruments_1_instrument_nid "682";
    String instruments_1_supplied_name "Titrator";
    String instruments_2_acronym "Aquarium";
    String instruments_2_dataset_instrument_nid "489463";
    String instruments_2_description "Aquarium - a vivarium consisting of at least one transparent side in which water-dwelling plants or animals are kept";
    String instruments_2_instrument_name "Aquarium";
    String instruments_2_instrument_nid "711";
    String instruments_2_supplied_name "Aquarium";
    String instruments_3_acronym "Conductivity Meter";
    String instruments_3_dataset_instrument_description "A Hach conductivity probe (read to 0.1, accurate to ~1) was used to determine the salinity of each experimental container.";
    String instruments_3_dataset_instrument_nid "489402";
    String instruments_3_description "Conductivity Meter - An electrical conductivity meter (EC meter) measures the electrical conductivity in a solution. Commonly used in hydroponics, aquaculture and freshwater systems to monitor the amount of nutrients, salts or impurities in the water.";
    String instruments_3_instrument_name "Conductivity Meter";
    String instruments_3_instrument_nid "719";
    String instruments_3_supplied_name "Conductivity Probe";
    String keywords "abbrev, bco, bco-dmo, biological, chemical, data, dataset, dmo, during, erddap, growth, management, oceanography, office, post, preliminary, rel, rel_growth_during_treatment, rel_growth_post_treatment, treatment, treatment_abbrev";
    String license "https://www.bco-dmo.org/dataset/489382/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/489382";
    String param_mapping "{'489382': {}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/489382/parameters";
    String people_0_affiliation "Woods Hole Oceanographic Institution";
    String people_0_affiliation_acronym "WHOI";
    String people_0_person_name "Anne L Cohen";
    String people_0_person_nid "51428";
    String people_0_role "Lead Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "Woods Hole Oceanographic Institution";
    String people_1_affiliation_acronym "WHOI";
    String people_1_person_name "Michael Holcomb";
    String people_1_person_nid "489381";
    String people_1_role "Contact";
    String people_1_role_type "related";
    String people_2_affiliation "Woods Hole Oceanographic Institution";
    String people_2_affiliation_acronym "WHOI BCO-DMO";
    String people_2_person_name "Shannon Rauch";
    String people_2_person_nid "51498";
    String people_2_role "BCO-DMO Data Manager";
    String people_2_role_type "related";
    String project "OA Nutrition and Coral Calcification";
    String projects_0_acronym "OA Nutrition and Coral Calcification";
    String projects_0_description 
"The project description is a modification of the original NSF award abstract.
This research project is part of the larger NSF funded CRI-OA collaborative research initiative and was funded as an Ocean Acidification-Category 1, 2010 award. Over the course of this century, all tropical coral reef ecosystems, whether fringing heavily populated coastlines or lining remote islands and atolls, face unprecedented threat from ocean acidification caused by rising levels of atmospheric CO2. In many laboratory experiments conducted to date, calcium carbonate production (calcification) by scleractinian (stony) corals showed an inverse correlation to seawater saturation state OMEGAar), whether OMEGAar was manipulated by acid or CO2 addition. Based on these data, it is predicted that coral calcification rates could decline by up to 80% of modern values by the end of this century. A growing body of new experimental data however, suggests that the coral calcification response to ocean acidification may be less straightforward and a lot more variable than previously recognized. In at least 10 recent experiments including our own, 8 different tropical and temperate species reared under nutritionally-replete but significantly elevated CO2 conditions (780-1200 ppm, OMEAGar ~1.5-2), continued to calcify at rates comparable to conspecifics reared under ambient CO2. These experimental results are consistent with initial field data collected on reefs in the eastern Pacific and southern Oman, where corals today live and accrete their skeletons under conditions equivalent to 2X and 3X pre-industrial CO2. On these high CO2, high nutrient reefs (where nitrate concentrations typically exceed 2.5 micro-molar), coral growth rates rival, and sometimes even exceed, those of conspecifics in low CO2, oligotrophic reef environments.
The investigators propose that a coral's energetic status, tightly coupled to the availability of inorganic nutrients and/or food, is a key factor in the calcification response to CO2-induced ocean acidification. Their hypothesis, if confirmed by the proposed laboratory investigations, implies that predicted changes in coastal and open ocean nutrient concentrations over the course of this century, driven by both climate impacts on ocean stratification and by increased human activity in coastal regions, could play a critical role in exacerbating and in some areas, modulating the coral reef response to ocean acidification. This research program builds on the investigators initial results and observations. The planned laboratory experiments will test the hypothesis that: (1) The coral calcification response to ocean acidification is linked to the energetic status of the coral host. The relative contribution of symbiont photosynthesis and heterotrophic feeding to a coral's energetic status varies amongst species. Enhancing the energetic status of corals reared under high CO2, either by stimulating photosynthesis with inorganic nutrients or by direct heterotrophic feeding of the host lowers the sensitivity of calcification to decreased seawater OMEGAar; (2) A species-specific threshold CO2 level exists over which enhanced energetic status can no longer compensate for decreased OMEGAar of the external seawater. Similarly, we will test the hypothesis that a nutrient threshold exists over which nutrients become detrimental for calcification even under high CO2 conditions; and (3) Temperature-induced reduction of algal symbionts is one stressor that can reduce the energetic reserve of the coral host and exacerbate the calcification response to ocean acidification.
The investigator's initial findings highlight the critical importance of energetic status in the coral calcification response to ocean acidification. Verification of these findings in the laboratory, and identification of nutrient and CO2 thresholds for a range of species will have immediate, direct impact on predictions of reef resilience in a high CO2 world. The research project brings together a diverse group of expertise in coral biogeochemistry, chemical oceanography, molecular biology and coral reproductive ecology to focus on a problem that has enormous societal, economic and conservation relevance.";
    String projects_0_end_date "2013-09";
    String projects_0_geolocation "global; experimental";
    String projects_0_name "An Investigation of the Role of Nutrition in the Coral Calcification Response to Ocean Acidification";
    String projects_0_project_nid "2183";
    String projects_0_start_date "2010-10";
    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 "Results from experiment examining effects of 4 different dyes on growth rates of scleractinian corals; from the Cohen lab at WHOI in Woods Hole, MA.";
    String title "Results from experiment examining effects of 4 different dyes on growth rates of scleractinian corals; from the Cohen lab at WHOI in Woods Hole, MA (OA Nutrition and Coral Calcification 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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