Accessing BCO-DMO data
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| Dataset Title: | [Experiment Metrics] - Experiment details for invertebrate larvae electrophysiology (Vision-mediated influence of low oxygen on the physiology and ecology of marine larvae) 
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| Institution: | BCO-DMO (Dataset ID: bcodmo_dataset_779387) |
| Information: | Summary
| License
| ISO 19115
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Attributes {
s {
Species {
String bcodmo_name "unknown";
String description "Species name";
String long_name "Species";
String units "unitless";
}
Experiment_Name {
String bcodmo_name "exp_id";
String description "Original experiment name that can be linked back to raw datafile collected in Igor.";
String long_name "Experiment Name";
String units "unitless";
}
Normoxia_Time {
Float32 _FillValue NaN;
Float32 actual_range 17.65, 54.85;
String bcodmo_name "dissolved Oxygen";
String description "Total time (in minutes) that was spend at 100-105% saturation oxygen before oxygen decline. NA indicates there were no visual recordings in normoxia.";
String long_name "Normoxia Time";
String units "minute (min)";
}
O2_Decay {
Float32 _FillValue NaN;
Float32 actual_range 22.43, 90.67;
String bcodmo_name "incubation time";
String description "Total time during which the animal was exposed to a decrease in oxygen (in minutes)";
String long_name "O2 Decay";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/AZDRZZ01/";
String units "minute (min)";
}
Normoxia_O2 {
Float32 _FillValue NaN;
Float32 actual_range 243.13, 289.4;
String bcodmo_name "O2_umol_L";
String description "The average oxygen concentration of the normoxia (~100-105% saturation) period";
String long_name "Normoxia O2";
String units "micromole per liter (umol/L)";
}
Low_O2 {
Float32 _FillValue NaN;
Float32 actual_range 37.94, 88.72;
String bcodmo_name "O2_umol_L";
String description "The average oxygen concentration of the lowest oxygen period";
String long_name "Low O2";
String units "micromole per liter (umol/L)";
}
O2_Change {
Float32 _FillValue NaN;
Float32 actual_range 186.57, 238.8;
String bcodmo_name "O2_umol_L";
String description "Subtracted value between the average in normoxia and the average in the low oxygen period";
String long_name "O2 Change";
String units "micromole per liter (umol/L)";
}
O2_Change_Time {
Float64 _FillValue NaN;
Float64 actual_range 2.14, 9.88;
String bcodmo_name "O2_umol_L";
String description "The rate of decline in oxygen (see above) over the total time when the animal was exposed to a decline in oxygen";
String long_name "O2 Change Time";
String units "micromole per liter per minute (umol/l per min)";
}
Low_O2_Min {
Float64 _FillValue NaN;
Float64 actual_range 0.0, 43.82;
String bcodmo_name "incubation time";
String description "Total time (in minutes) the animal was exposed to Low oxygen";
String long_name "Low O2 Min";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/AZDRZZ01/";
String units "minute (min)";
}
Total_Exp_Time {
Float32 _FillValue NaN;
Float32 actual_range 1.78, 3.3;
String bcodmo_name "duration";
String description "Total experiment duration in hours";
String long_name "Total Exp Time";
String units "hour (hr)";
}
pH {
String bcodmo_name "pH";
String description "pH of the seawater during the experiment. No buffer indicates the solution was not buffered and the pH might have varied during the experiment";
String long_name "pH";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/PHXXZZXX/";
String units "unitless";
}
Temp_Max {
Float32 _FillValue NaN;
Float32 actual_range 14.2, 16.9;
String bcodmo_name "temperature";
String description "Maximum temperature of the experiment";
String long_name "Temp Max";
String units "degrees Celsius (C";
}
Temp_Min {
Float32 _FillValue NaN;
Float32 actual_range 13.0, 15.4;
String bcodmo_name "temperature";
String description "Minimum temperature of the experiment";
String long_name "Temp Min";
String units "degrees Celsius (C";
}
Temp_Avg {
Float64 _FillValue NaN;
Float64 actual_range 13.8, 16.2;
String bcodmo_name "temperature";
String description "Mean temperature of the experiment";
String long_name "Temp Avg";
String units "degrees Celsius (C";
}
Stimulus_Irradiance {
Float32 _FillValue NaN;
Float32 actual_range 3.56, 3.56;
String bcodmo_name "irradiance";
String description "Irradiance of the light stimulus (LED 525 nm)";
String long_name "Stimulus Irradiance";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/VSRW/";
String units "mol photons per second and square meter (mol m-2s-1)";
}
}
NC_GLOBAL {
String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv";
String acquisition_description
"Detailed methods can be found in McCormick, et al., 2019.
Briefly, the time series test recorded electroretinogram (ERG) responses to a
1 s square step of light at a constant irradiance of 3.56 \\u03bcmol photons
m\\u22122 s\\u22121 repeated every 20 s, providing a nearly continuous measure
of ERG response in a tethered, live larva during the experimental manipulation
of partial pressure of oxygen (pO2). There was a constant flow of pH-buffered
sterile seawater in the chamber where the larva was held, and after a brief
period in \\u201cnormoxia\\u201d (surface-ocean oxygen levels), the pO2 was
decreased, and then held at a low pO2 before re-oxygenating the solution. This
dataset shows additional experimental details for the \\u201cTimeSeries\\u201d
and \\u201cOxygenMetrics_Vision\\u201d datasets, including the original
experiment name (that can be matched with the experiment name from the other
datasets), the time periods for each oxygen exposure, and the pH and
temperature of the experiments.
Oxygen was measured using a Microx4 (PreSens) oxygen meter and a Pst-7 oxygen
optode probe.
\\u00a0";
String awards_0_award_nid "775842";
String awards_0_award_number "OCE-1829623";
String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1829623";
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
"Experiment metrics
PI: Lisa A. Levin
Data Version 1: 2019-10-29";
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 "2019-10-23T16:26:05Z";
String date_modified "2019-11-01T15:44:28Z";
String defaultDataQuery "&time<now";
String doi "10.1575/1912/bco-dmo.779387.1";
String history
"2024-11-08T05:47:55Z (local files)
2024-11-08T05:47:55Z https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_779387.html";
String infoUrl "https://www.bco-dmo.org/dataset/779387";
String institution "BCO-DMO";
String instruments_0_acronym "O2 microsensor";
String instruments_0_dataset_instrument_description "Oxygen was measured using a Microx4 (PreSens) oxygen meter and a Pst-7 oxygen optode probe.";
String instruments_0_dataset_instrument_nid "779725";
String instruments_0_description "A miniaturized Clark-type dissolved oxygen instrument, including glass micro-sensors with minute tips (diameters ranging from 1 to 800 um). A gold or platinum sensing cathode is polarized against an internal reference and, driven by external partial pressure, oxygen from the environment penetrates through the sensor tip membrane and is reduced at the sensing cathode surface. A picoammeter converts the resulting reduction current to a signal. The size of the signal generated by the electrode is proportional to the flux of oxygen molecules to the cathode.The sensor also includes a polarized guard cathode, which scavenges oxygen in the electrolyte, thus minimizing zero-current and pre-polarization time.With the addition of a meter and a sample chamber, the respiration of a small specimen can be measured. Example: Strathkelvin Inst. http://www.strathkelvin.com";
String instruments_0_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/351/";
String instruments_0_instrument_name "Oxygen Microelectrode Sensor";
String instruments_0_instrument_nid "701";
String keywords "average, bco, bco-dmo, biological, change, chemical, data, dataset, decay, dmo, erddap, exp, experiment, Experiment_Name, irradiance, low, Low_O2, Low_O2_Min, management, max, min, name, normoxia, Normoxia_O2, Normoxia_Time, O2, O2_Change, O2_Change_Time, O2_Decay, oceanography, office, oxygen, preliminary, species, stimulus, Stimulus_Irradiance, Temp_Avg, Temp_Max, Temp_Min, temperature, time, total, Total_Exp_Time";
String license "https://www.bco-dmo.org/dataset/779387/license";
String metadata_source "https://www.bco-dmo.org/api/dataset/779387";
String param_mapping "{'779387': {}}";
String parameter_source "https://www.bco-dmo.org/mapserver/dataset/779387/parameters";
String people_0_affiliation "University of California-San Diego";
String people_0_affiliation_acronym "UCSD";
String people_0_person_name "Lisa A Levin";
String people_0_person_nid "51242";
String people_0_role "Principal Investigator";
String people_0_role_type "originator";
String people_1_affiliation "University of California-San Diego";
String people_1_affiliation_acronym "UCSD";
String people_1_person_name "Nicholas Oesch";
String people_1_person_nid "775846";
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 "Karen Soenen";
String people_2_person_nid "748773";
String people_2_role "BCO-DMO Data Manager";
String people_2_role_type "related";
String project "Vision under hypoxia";
String projects_0_acronym "Vision under hypoxia";
String projects_0_description
"NSF abstract:
Oxygen is being lost in the ocean worldwide as a result of ocean warming and the input of nutrients from land. Vision requires a large amount of oxygen, and may be less effective or require more light when oxygen is in short supply. This is especially true for active marine animals with complex eyes and visual capabilities, including active arthropods (crabs), cephalopods (squid), and fish. The California coastal waters exhibit a sharp drop in oxygen and light with increasing water depth. This project examines how visual physiology and ecology in young (larval) highly visual marine animals respond to oxygen loss, with a focus on key fisheries and aquaculture species. Experiments and observations will test the hypothesis that oxygen stress will change the light required for these organisms to see effectively, influencing the water depths where they can live and survive. The project will provide interdisciplinary experiences to students and an early career scientist and inform both the public (through outreach at the Birch Aquarium at Scripps Institution of Oceanography) and policy makers about the effects of oxygen decline in the ocean.
Negative effects of oxygen loss on vision have been described for humans and other terrestrial organisms, but never in the marine environment, despite the large changes in oxygen that can occur with depth and over time in the ocean, and the high metabolic demand of visual systems. This project will test the effects of low oxygen on vision in 3 combinations of eye design and photo-transduction mechanisms: compound eye with rhabdomeric photoreceptors (arthropods), simple eye with rhabdomeric photoreceptors (cephalopods), and simple eye with ciliary photoreceptors (fish). A series of oxygen- and light-controlled laboratory experiments will be conducted on representative taxa of each group including the tuna crab, Pleuroncodes planipes; the market squid, Doryteuthis opalescens, and the white sea bass, Atractoscion nobilis. In vivo electrophysiology and behavioral phototaxis experiments will identify new oxygen metrics for visual physiology and function, and will be compared to metabolic thresholds determined in respiration experiments. Hydrographic data collected over 3 decades by the CalCOFI program in the Southern California Bight will be evaluated with respect to visual and metabolic limits to determine the consequences of oxygen variation on the critical luminoxyscape (range of oxygen and light conditions required for visual physiology and function in target species) boundary in each species. Findings for the three vision-based functional groups may test whether oxygen-limited visual responses offer an additional explanation for the shoaling of species distributions among highly visual pelagic taxa in low oxygen, and will help to focus future research efforts and better understand the stressors contributing to habitat compression with expanding oxygen loss in the ocean.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.";
String projects_0_end_date "2020-09";
String projects_0_geolocation "Southern California Bight, Northeast Pacific Ocean";
String projects_0_name "Vision-mediated influence of low oxygen on the physiology and ecology of marine larvae";
String projects_0_project_nid "775843";
String projects_0_start_date "2018-10";
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 subsetVariables "Stimulus_Irradiance";
String summary "Experiment Details for invertebrate larvae electrophysiology";
String title "[Experiment Metrics] - Experiment details for invertebrate larvae electrophysiology (Vision-mediated influence of low oxygen on the physiology and ecology of marine larvae)";
String version "1";
String xml_source "osprey2erddap.update_xml() v1.3";
}
}
Data Access Protocol (DAP) and its
selection constraints.
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.