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Dataset Title:  Hydrolysis rates from bulk samples, plate reader results from RV/Endeavor
EN556, 2015 (Patterns of activities project)
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_719487)
Range: depth = 1.0 to 4574.0m
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 {
  cruise_id {
    String bcodmo_name "cruise_id";
    String description "cruise identifier";
    String long_name "Cruise Id";
    String units "unitless";
  }
  station {
    Byte _FillValue 127;
    Byte actual_range 1, 8;
    String bcodmo_name "station";
    String description "station number";
    String long_name "Station";
    String units "unitless";
  }
  cast {
    Byte _FillValue 127;
    Byte actual_range 1, 13;
    String bcodmo_name "cast";
    String description "cast number";
    String long_name "Cast";
    String units "unitless";
  }
  depth_no {
    String bcodmo_name "depth_comment";
    String description "depth description: sequence of depths sampled with 1 is surface and higher numbers at greater depths";
    String long_name "Depth";
    String standard_name "depth";
    String units "unitless";
  }
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    Float64 _FillValue NaN;
    Float64 actual_range 1.0, 4574.0;
    String axis "Z";
    String bcodmo_name "depth";
    Float64 colorBarMaximum 8000.0;
    Float64 colorBarMinimum -8000.0;
    String colorBarPalette "TopographyDepth";
    String description "actual depth at which water collected";
    String ioos_category "Location";
    String long_name "Depth";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/DEPH/";
    String positive "down";
    String standard_name "depth";
    String units "m";
  }
  substrate {
    String bcodmo_name "unknown";
    String description "substrates for measurement of enzymatic activities: a-glu = alpha glucosidase: 4-methylumbelliferyl-a-D-glucopyranoside; b-glu = beta glucosidase: 4-methylumbelliferyl-beta-D-glucopyranoside; L = leucine aminopeptidase (L-leucine-7-amido-4 MCA); AAF = chymotrypsin activity: ala-ala-phe-MCA; AAPF = chymotrypsin activity: N-succinyl-ala-ala-pro-phe-MCA; QAR = trypsin activity: Boc-gln-ala-arg-MCA; FSR = trypsin activity: N-t-boc-phe-ser-arg-MCA";
    String long_name "Substrate";
    String units "unitless";
  }
  rep1_rate {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 127.93;
    String bcodmo_name "unknown";
    String description "replicate 1 of enzymatic hydrolysis rate";
    String long_name "Rep1 Rate";
    String units "nanomol monosaccharide/liter/hour";
  }
  rep2_rate {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 88.86;
    String bcodmo_name "unknown";
    String description "replicate 2 of enzymatic hydrolysis rate";
    String long_name "Rep2 Rate";
    String units "nanomol monosaccharide/liter/hour";
  }
  rep3_rate {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 85.03;
    String bcodmo_name "unknown";
    String description "replicate 3 of enzymatic hydrolysis rate";
    String long_name "Rep3 Rate";
    String units "nanomol monosaccharide/liter/hour";
  }
  average {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 80.0;
    String bcodmo_name "unknown";
    String description "average of the 3 hydrolysis rates";
    String long_name "Average";
    String units "nanomol monosaccharide/liter/hour";
  }
  std_dev {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 53.23;
    String bcodmo_name "unknown";
    String description "standard deviation of the 3 hydrolysis rates";
    String long_name "Std Dev";
    String units "nanomol monosaccharide/liter/hour";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv";
    String acquisition_description 
"Seawater was transferred to 20 L carboys that were rinsed three times with
water from the sampling depth and then filled with seawater from a single
Niskin bottle, using silicone tubing that had been acid washed then rinsed
with distilled water prior to use. From each carboy, water was dispensed into
smaller glass containers that were cleaned and pre-rinsed three times with
water from the carboy prior to dispensing. This water was used to measure cell
counts, bacterial productivity, and the activities of polysaccharide
hydrolases, peptidases, and glucosidases. A separate glass Duran bottle was
filled with seawater from the carboy and sterilized in an autoclave for 20-30
minutes to serve as a killed control for microbial activity measurements.
 
Two substrates, -glucose and -glucose linked to a 4-methylumbelliferyl (MUF)
fluorophore, were used to measure glucosidase activities. Five substrates
linked to a 7-amido-4-methyl coumarin (MCA) fluorophore, one amino acid \\u2013
leucine \\u2013 and four oligopeptides \\u2013 the chymotrypsin substrates
alanine-alanine-phenylalanine (AAF) and alanine-alanine-proline-phenylalanine
(AAPF), and the trypsin substrates glutamine-alanine-arginine (QAR) and
phenylalanine-serine-arginine (FSR) \\u2013 were used to measure exo- and endo-
acting peptidase activities, respectively. Hydrolysis rates of the substrates
were measured as an increase in fluorescence as the fluorophore was hydrolyzed
from the substrate over time [as in Hoppe, 1993; Obayashi and Suzuki, 2005].
Incubations with the seven low molecular weight substrates were set up in a
96-well plate. For each substrate, triplicate wells were filled with a total
volume of 200 L seawater for experimental incubations; triplicate wells were
filled with 200 L autoclaved seawater for killed control incubations.
Substrate was added at saturating concentrations. A saturation curve was
determined with surface water from each station to determine saturating
concentrations of substrate. The saturating concentration was identified as
the lowest tested concentration of substrate at which additional substrate did
not yield higher rates of hydrolysis. Fluorescence was measured over 24-48
hours incubation time with a plate reader (TECAN spectrafluor plus; 360 nm
excitation, 460 emission), with time points taken every 4-6 hours. Hydrolysis
rates were calculated from the rate of increase of fluorescence in the
incubation over time relative to a set of standards of known concentration of
fluorophore. Scripts to calculate hydrolysis rates and produce the figures
shown here are available in the associated Github repository [Hoarfrost,
2017].
 
The potential of the seawater microbial community to hydrolyze six high-
molecular-weight polysaccharides (arabinogalactan, chondroitin sulfate,
fucoidan, laminarin, pullulan, and xylan) was investigated in surface and
bottom water. For each substrate, three 50 mL falcon tubes were filled with
seawater and one 50 mL falcon tube was filled with autoclaved seawater to
serve as a killed control. Substrate was added at 3.5 \\u03bcM monomer-
equivalent concentrations, except for fucoidan, which was added at 5 \\u03bcM
concentrations (a higher concentration was necessary for sufficient
fluorescence signal). Two 50 mL falcon tubes \\u2013 one with seawater and one
with autoclaved seawater \\u2013 with no added substrate served as blank
controls. Incubations were stored in the dark at as close to in situ
temperature as possible. Subsamples of the incubations were collected at time
zero, and at six subsequent time points (t1-t6): 2 days, 5 days, 10 days, 17
days, 30 days, and 42 days. At each time point, 2 mL of seawater was collected
from the 50 mL falcon tube using a sterile syringe, filtered through a 0.2
\\u03bcm pore size syringe filter, and stored frozen until processing.";
    String awards_0_award_nid "712358";
    String awards_0_award_number "OCE-1332881";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1332881";
    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 "Henrietta N Edmonds";
    String awards_0_program_manager_nid "51517";
    String cdm_data_type "Other";
    String comment 
"Hydrolysis rates from bulk samples, plate reader results: EN556 
   C. Arnosti (UNC) 
   version: 2017-11-16";
    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 dataset_current_state "Final and no updates";
    String date_created "2017-11-17T15:23:29Z";
    String date_modified "2020-05-13T14:03:00Z";
    String defaultDataQuery "&time<now";
    String doi "10.26008/1912/bco-dmo.719487.1";
    Float64 geospatial_vertical_max 4574.0;
    Float64 geospatial_vertical_min 1.0;
    String geospatial_vertical_positive "down";
    String geospatial_vertical_units "m";
    String history 
"2021-09-23T02:20:12Z (local files)
2021-09-23T02:20:12Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_719487.das";
    String infoUrl "https://www.bco-dmo.org/dataset/719487";
    String institution "BCO-DMO";
    String instruments_0_acronym "Niskin bottle";
    String instruments_0_dataset_instrument_description "Used to collect water for large volume mesocosm experiments";
    String instruments_0_dataset_instrument_nid "719493";
    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 "30 liter Niskin bottles";
    String instruments_1_acronym "Fluorometer";
    String instruments_1_dataset_instrument_nid "719494";
    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_2_dataset_instrument_nid "719495";
    String instruments_2_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_2_instrument_name "plate reader";
    String instruments_2_instrument_nid "528693";
    String instruments_2_supplied_name "TECAN spectrafluor plus";
    String keywords "average, bco, bco-dmo, biological, cast, chemical, cruise, cruise_id, data, dataset, depth, depth_m, depth_no, dev, dmo, erddap, management, oceanography, office, preliminary, profiler, rate, rep1, rep1_rate, rep2, rep2_rate, rep3, rep3_rate, salinity, salinity-temperature-depth, station, std, std_dev, substrate, temperature";
    String license "https://www.bco-dmo.org/dataset/719487/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/719487";
    String param_mapping "{'719487': {'depth_m': 'master - depth'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/719487/parameters";
    String people_0_affiliation "University of North Carolina at Chapel Hill";
    String people_0_affiliation_acronym "UNC-Chapel Hill";
    String people_0_person_name "Carol Arnosti";
    String people_0_person_nid "661940";
    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 "Nancy Copley";
    String people_1_person_nid "50396";
    String people_1_role "BCO-DMO Data Manager";
    String people_1_role_type "related";
    String project "Patterns of activities";
    String projects_0_acronym "Patterns of activities";
    String projects_0_description 
"NSF Award Abstract:
Heterotrophic microbial communities are key players in the marine carbon cycle, transforming and respiring organic carbon, regenerating nutrients, and acting as the final filter in sediments through which organic matter passes before long-term burial. Microbially-driven carbon cycling in the ocean profoundly affects the global carbon cycle, but key factors determining rates and locations of organic matter remineralization are unclear. In this study, researchers from the University of North Carolina at Chapel Hill will investigate the ability of pelagic microbial communities to initiate the remineralization of polysaccharides and proteins, which together constitute a major pool of organic matter in the ocean. Results from this study will be predictive on a large scale regarding the nature of the microbial response to organic matter input, and will provide a mechanistic framework for interpreting organic matter reactivity in the ocean.
Broader Impacts: This study will provide scientific training for undergraduate and graduate students from underrepresented groups. The project will also involve German colleagues, thus strengthening international scientific collaboration.";
    String projects_0_end_date "2017-07";
    String projects_0_geolocation "Atlantic Ocean, Arctic Ocean, Pacific Ocean, Greenland";
    String projects_0_name "Latitudinal and depth-related contrasts in enzymatic capabilities of pelagic microbial communities: Predictable patterns in the ocean?";
    String projects_0_project_nid "712359";
    String projects_0_start_date "2013-08";
    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 "cruise_id";
    String summary "This dataset includes polysaccharide hydrolysis rates to measure microbial enzyme activities and bacterial productivity, from bulk samples, plate reader results from RV/Endeavor EN556, 2015.";
    String title "Hydrolysis rates from bulk samples, plate reader results from RV/Endeavor EN556, 2015 (Patterns of activities project)";
    String version "1";
    String xml_source "osprey2erddap.update_xml() v1.5";
  }
}

 

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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