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Dataset Title:  Microbial enzymatic activities from seawater and from particle-associated
seawater communities from Greenland, August 2015 (Patterns of activities
project)
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_717660)
Range: depth = 1.0 to 20.0m
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 {
  trip_id {
    String bcodmo_name "Cruise Name";
    String description "sampling trip identifier; YS means Young Sound";
    String long_name "Trip Id";
    String units "unitless";
  }
  sample_type {
    String bcodmo_name "sample_type";
    String description "indication of whether sample was filtered (GF) or not (bulk)";
    String long_name "Sample Type";
    String units "unitless";
  }
  filter_um {
    Float32 _FillValue NaN;
    Float32 actual_range 1.6, 1.6;
    String bcodmo_name "filter_size";
    String description "filter size";
    String long_name "Filter Um";
    String units "nanomol monomer/liter/hour";
  }
  fluorophore {
    String bcodmo_name "unknown";
    String description "fluorescent molecules used to measure hydrolysis rates:  fluorescently-labeled polysaccharides (FLA) or small substrate proxies tagged with methylcoumarine (MCA) and methylumbelliferone (MUF) fluorophores.";
    String long_name "Fluorophore";
    String units "unitless";
  }
  station {
    String bcodmo_name "station";
    String description "station identifier";
    String long_name "Station";
    String units "unitless";
  }
  cast {
    Int32 _FillValue 2147483647;
    Int32 actual_range 120808, 171521;
    String bcodmo_name "cast";
    String description "cast identifier";
    String long_name "Cast";
    String units "unitless";
  }
  depth_id {
    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, 20.0;
    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: ara = arabinogalactan; chn = chondroitin sulfate; fuc = fucoidan; lam = laminarin; pul = pullulan; xyl = xylan";
    String long_name "Substrate";
    String units "unitless";
  }
  timepoint {
    String bcodmo_name "time_point";
    String description "sampling time point (0; 1; 2; etc.) post-incubation";
    String long_name "Timepoint";
    String units "unitless";
  }
  time_elapsed_hr {
    Int16 _FillValue 32767;
    Int16 actual_range 0, 982;
    String bcodmo_name "time_elapsed";
    String description "hours elapsed to reach a specific timepoint";
    String long_name "Time Elapsed Hr";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/ELTMZZZZ/";
    String units "hours";
  }
  rep1_rate {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 76.82;
    String bcodmo_name "unknown";
    String description "replicate 1 hydrolysis rate";
    String long_name "Rep1 Rate";
    String units "nanomol monomer/liter/hour";
  }
  rep2_rate {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 77.36;
    String bcodmo_name "unknown";
    String description "replicate 2 hydrolysis rate";
    String long_name "Rep2 Rate";
    String units "nanomol monomer/liter/hour";
  }
  rep3_rate {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 91.25;
    String bcodmo_name "unknown";
    String description "replicate 3 hydrolysis rate";
    String long_name "Rep3 Rate";
    String units "nanomol monomer/liter/hour";
  }
  rate_average {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 81.81;
    String bcodmo_name "unknown";
    String description "average of the 3 hydrolysis rates";
    String long_name "Rate Average";
    String units "nanomol monomer/liter/hour";
  }
  rate_std_dev {
    String bcodmo_name "unknown";
    String description "standard deviation of the 3 hydrolysis rates";
    String long_name "Rate Std Dev";
    String units "nanomol monomer/liter/hour";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv";
    String acquisition_description 
"Using a small boat, samples were collected in 20L carboys in Tylerfjord-Young
Sound. Three rivers that feed into Tyrolerfjord-Young Sound (Tyroler River,
Lerbugten River and Zackenberg River) were sampled; surface and subsurface
water samples were also collected at transition sites where the rivers feed
into the fjord (Tyro_01, Zac_30, Ler_30, altogether referred to as \\u2018river
transition sites\\u2019). Enzyme activities were measured in unfiltered water.
In addition, water was size-fractionated using gravity filtration through a
GF/A filter to capture \\u22651.6 \\u00b5m particles.
 
Two substrates, a-glucose and b-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].
\\u00a0All substrates were used to measure enzyme activities in unfiltered
water, as well as particle-associated (\\u22651.6 \\u00b5m) enzymatic
activities.
 
In unfiltered water, enzyme activities were measured by adding 4 mL of water
to triplicate cuvettes. One incubation containing autoclaved water served as
the killed control. This procedure was applied to each of the 7 substrates and
one live blank and autoclave blank (no substrate addition). Each cuvette
containing either live or autoclaved water was amended with one substrate to a
concentration of 100 \\u00b5M. Fluroescence was measured using a Promega
Quanti\\ufb02uor solid-state single-cuvette \\ufb02uorimeter; excitation and
emission maxima were 365 nm and 410\\u2013450 nm, respectively,
 
To measure particle-associated enzyme assays, 1/12th piece of a GF/A filter
through which water had been gravity filtered was put into a cuvette
containing 4 mL of cooled, autoclaved water from the same station/depth as the
live samples. In addition, killed controls were set up using sterile GF/A
filters cut into 1/12th pieces. Bulk water and particle-associated enzyme
assays were incubated for up to 24 and 16 hours, respectively; timepoints were
taken at specific intervals. Incubations were kept in the dark either at
0\\u00b0C, 5\\u00b0C, or 8\\u00b0C, depending on in situ water temperature at the
time of sampling.
 
Activities of polysaccharide hydrolases were measured using fluorescently
labeled polysaccharides (Arnosti 2003). Activities of enzymes that hydrolyze
pullulan, laminarin, xylan, fucoidan, arabinogalactan, and chondroitin sulfate
were measured in unfiltered water, and using GF/A filters through which water
had been gravity-filtered. For these measurements, substrate was added (of 3.5
\\u00b5M monomer equivalent) to 15 mL of water; autoclaved ambient water served
as the killed control. Particle-associated activities were measured by
submerging 1/12th of a GF/A filter in 15 ml autoclaved seawater. Samples were
incubated in the dark at near in situ temperature (0\\u00b0C, 5\\u00b0C, or
8\\u00b0C), and sub-sampled at specific time intervals\\u2014t0 (0h, upon
substrate addition), t1 (120 h), t2 (240 h), t3 (360 h) and t4 (600 h). Sub-
samples from each timepoint were filtered using 0.2 \\u00b5M pore size SFCA
(surfactant-free cellulose acetate) syringe filters, and the filtrate was
collected in tubes and frozen at -20\\u00b0C until processing in the lab. Sub-
samples were processed using gel permeation chromatography (Arnosti,
2003).\\u00a0";
    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 
"Microbial enzyme activities and bacterial productivity: hydrolysis rates 
   Greenland bulk (unfiltered) and GF filtered samples 
   C. Arnosti (UNC) 
   version: 2017-10-30";
    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 "2017-10-25T16:47:01Z";
    String date_modified "2020-05-13T14:07:45Z";
    String defaultDataQuery "&time<now";
    String doi "10.26008/1912/bco-dmo.717660.1";
    Float64 geospatial_vertical_max 20.0;
    Float64 geospatial_vertical_min 1.0;
    String geospatial_vertical_positive "down";
    String geospatial_vertical_units "m";
    String history 
"2020-09-25T16:51:50Z (local files)
2020-09-25T16:51:50Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_717660.das";
    String infoUrl "https://www.bco-dmo.org/dataset/717660";
    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 "717666";
    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 "20 liter Niskin bottles";
    String instruments_1_acronym "Fluorometer";
    String instruments_1_dataset_instrument_nid "718104";
    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 "Promega Quantifluor solid-state single-cuvette fluorimeter";
    String keywords "average, bco, bco-dmo, biological, cast, chemical, data, dataset, depth, depth_id, depth_m, dev, dmo, elapsed, erddap, filter, filter_um, fluorophore, management, oceanography, office, preliminary, profiler, rate, rate_average, rate_std_dev, rep1, rep1_rate, rep2, rep2_rate, rep3, rep3_rate, salinity, salinity-temperature-depth, sample, sample_type, station, std, substrate, temperature, time, time_elapsed_hr, timepoint, trip, trip_id, type";
    String license "https://www.bco-dmo.org/dataset/717660/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/717660";
    String param_mapping "{'717660': {'depth_m': 'master - depth'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/717660/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 "trip_id";
    String summary "Bacterial activity as measured by hydrolysis rates from unfiltered seawater and particle-associated communities collected near shore in northeastern Greenland in August 2015.";
    String title "Microbial enzymatic activities from seawater and from particle-associated seawater communities from Greenland, August 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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