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| Dataset Title: | [Phosphohydrolysis rates in the coastal western North Atlantic] - Phosphohydrolysis rates from samples collected in the coastal western North Atlantic on R/V Endeavor cruise EN588 during September 2016 (Collaborative Research: Exploring the role of exogenous polyphosphate in the precipitation of calcium phosphate minerals in the marine environment) 
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| Institution: | BCO-DMO (Dataset ID: bcodmo_dataset_767022) |
| Information: | Summary
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Attributes {
s {
Station {
String bcodmo_name "station";
String description "Station name";
String long_name "Station";
String units "unitless";
}
latitude {
String _CoordinateAxisType "Lat";
Float64 _FillValue NaN;
Float64 actual_range 39.41208, 41.54397;
String axis "Y";
String bcodmo_name "latitude";
Float64 colorBarMaximum 90.0;
Float64 colorBarMinimum -90.0;
String description "Latitude North";
String ioos_category "Location";
String long_name "Latitude";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/LATX/";
String standard_name "latitude";
String units "degrees_north";
}
longitude {
String _CoordinateAxisType "Lon";
Float64 _FillValue NaN;
Float64 actual_range -73.24917, -70.66917;
String axis "X";
String bcodmo_name "longitude";
Float64 colorBarMaximum 180.0;
Float64 colorBarMinimum -180.0;
String description "Longitude East (negative values = West)";
String ioos_category "Location";
String long_name "Longitude";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/LONX/";
String source_name "Long";
String standard_name "longitude";
String units "degrees_east";
}
depth {
String _CoordinateAxisType "Height";
String _CoordinateZisPositive "down";
Float64 _FillValue NaN;
Float64 actual_range 5.0, 35.0;
String axis "Z";
String bcodmo_name "depth";
Float64 colorBarMaximum 8000.0;
Float64 colorBarMinimum -8000.0;
String colorBarPalette "TopographyDepth";
String description "Depth";
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";
}
Temperature {
Float32 _FillValue NaN;
Float32 actual_range 11.2, 22.7;
String bcodmo_name "temperature";
String description "Temperature";
String long_name "Temperature";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/TEMPP901/";
String units "degrees Celsius";
}
Salinity {
Float32 _FillValue NaN;
Float32 actual_range 24.4, 32.8;
String bcodmo_name "sal";
Float64 colorBarMaximum 37.0;
Float64 colorBarMinimum 32.0;
String description "Salinity";
String long_name "Sea Water Practical Salinity";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/PSALST01/";
String units "PSU?";
}
Inorganic_poly_P_hydrolysis {
Float32 _FillValue NaN;
Float32 actual_range 3.8, 19.3;
String bcodmo_name "P";
String description "Inorganic poly-P hydrolysis";
String long_name "Inorganic Poly P Hydrolysis";
String units "nanomoles P per liter per hour (nmol P/L/hr)";
}
MUF_P_hydrolysis {
Float32 _FillValue NaN;
Float32 actual_range 1.4, 50.6;
String bcodmo_name "P";
String description "MUF-P hydrolysis";
String long_name "MUF P Hydrolysis";
String units "nmol P/L/hr";
}
Soluble_reactive_P {
Int16 _FillValue 32767;
Int16 actual_range 147, 890;
String bcodmo_name "P";
String description "Soluble reactive P";
String long_name "Soluble Reactive P";
String units "nanomoles per liter (nmol/L)";
}
Chlorophyll {
Float32 _FillValue NaN;
Float32 actual_range 0.56, 3.06;
String bcodmo_name "chlorophyll a";
Float64 colorBarMaximum 30.0;
Float64 colorBarMinimum 0.03;
String colorBarScale "Log";
String description "Chlorophyll";
String long_name "Concentration Of Chlorophyll In Sea Water";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/CPHLHPP1/";
String units "micrograms per liter (ug/L)";
}
Bacterial_abundance {
Float32 _FillValue NaN;
Float32 actual_range 7.12, 37.9;
String bcodmo_name "abundance";
String description "Bacterial abundance";
String long_name "Bacterial Abundance";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P03/current/B070/";
String units "10^5 cells per milliiter (10^5 cells/mL)";
}
Total_phytoplankton {
Float32 _FillValue NaN;
Float32 actual_range 0.99, 22.0;
String bcodmo_name "abundance";
String description "Total phytoplankton";
String long_name "Total Phytoplankton";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P03/current/B070/";
String units "10^4 cells/mL";
}
Synechococcus_spp {
Float32 _FillValue NaN;
Float32 actual_range 0.37, 15.5;
String bcodmo_name "abundance";
String description "Synechococcus spp.";
String long_name "Synechococcus Spp";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P03/current/B070/";
String units "10^4 cells/mL";
}
Picoeukaryotic_phytoplankton {
Float32 _FillValue NaN;
Float32 actual_range 0.44, 35.4;
String bcodmo_name "abundance";
String description "Picoeukaryotic phytoplankton";
String long_name "Picoeukaryotic Phytoplankton";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P03/current/B070/";
String units "10^3 cells/mL";
}
Nanoeukaryotic_phytoplankton {
Float32 _FillValue NaN;
Float32 actual_range 1.05, 19.5;
String bcodmo_name "abundance";
String description "Nanoeukaryotic phytoplankton";
String long_name "Nanoeukaryotic Phytoplankton";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P03/current/B070/";
String units "10^3 cells/mL";
}
Large_eukaryotic_phytoplankton {
Float32 _FillValue NaN;
Float32 actual_range 0.78, 13.7;
String bcodmo_name "abundance";
String description "Large eukaryotic phytoplankton";
String long_name "Large Eukaryotic Phytoplankton";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P03/current/B070/";
String units "10^2 cells/mL";
}
Bacterial_abundance_to_Total_phytoplankton {
Byte _FillValue 127;
String _Unsigned "false";
Byte actual_range 17, 125;
String bcodmo_name "abundance";
String description "Ratio of Bacterial abundance:Total phytoplankton";
String long_name "Bacterial Abundance To Total Phytoplankton";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P03/current/B070/";
String units "unitless";
}
}
NC_GLOBAL {
String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson";
String acquisition_description
"Field sampling: Surface seawater (5\\u201335 m) was collected in September 2016
during two sampling campaigns in the coastal western North Atlantic (Diaz et
al., 2018; Supplementary Table S1). Three sites were sampled aboard the R/V
Endeavor using a Niskin rosette sampler and incubated immediately in order to
determine rates of P hydrolysis. Two sites accessible by small boat in Woods
Hole Harbor and Buzzard's Bay, MA, were sampled utilizing a peristaltic pump.
These samples were transported on ice packs and analyzed for P hydrolysis
rates within 5\\u20136 hours of collection. Additional samples were preserved
and analyzed for chlorophyll, bacteria and phytoplankton abundance, and
soluble reactive P (SRP), as detailed below.
Chlorophyll: In the dark, 250 mL of seawater was filtered onto 25 mm GF/F
filters. Samples were stored in the dark at -20C until analyzed according to
protocols adapted from Strickland and Parsons (1972). Briefly, samples were
extracted in 90% acetone in the dark (4C, 9 hr) and measured using a 10AU
fluorometer (Turner). Sample signals were calibrated using a chlorophyll-a
standard (Sigma) and were corrected for phaeopigments by accounting for the
fluorescence of extracts before and after acidification to 0.003 M HCl.
Abundance of bacteria and phytoplankton: Seawater samples were preserved for
flow cytometry with 0.5% glutaraldehyde (final concentration), flash frozen in
liquid nitrogen and stored at -80\\u00b0C until analysis. Bacteria and group-
specific phytoplankton counts were conducted on a Guava EasyCyte HT flow
cytometer (Millipore). Instrument-specific beads were used to calibrate the
cytometer. Samples were analyzed at a low flow rate (0.24 \\u00b5L
s\\u207b\\u00b9) for 3 min. To enumerate bacteria, samples were diluted (1:100)
with filtered seawater (0.01 \\u00b5m). Samples and filtered seawater blanks
were stained with SYBR Green I (Invitrogen) according to the manufacturer's
instructions and incubated in a 96-well plate in the dark at room temperature
for 1 hr. Bacterial cells were counted based on diagnostic forward scatter vs.
green fluorescence signals. Major phytoplankton groups were distinguished
based on plots of forward scatter vs. orange (phycoerythrin-containing
Synechococcus sp.), and forward scatter vs. red (eukaryotes). Size classes of
eukaryotic phytoplankton were further distinguished based on forward scatter
(pico-, nano- and large eukaryotes).
Soluble reactive P: Seawater samples were collected from Niskin rosette
bottles or the peristaltic pump into acid cleaned, high density polyethylene
bottles. Samples used for determining in situ SRP concentrations were frozen
and stored upright at -20\\u00b0C until analysis. Field samples and diatom
filtrates were both analyzed for SRP using a standard colorimetric method
(Hansen and Koroleff, 1999). To determine in situ SRP concentrations in field
samples, SRP analysis was conducted using a 4 cm glass spectrophotometry cell
on triplicate subsamples, and the detection limit, defined as three times the
standard deviation of replicate blank measurements, was 115 nmol L\\u207b\\u00b9
SRP. For incubations to determine P hydrolysis rates (see below), replicate
samples were analyzed in clear 96-well plates on a multimode plate reader
(Molecular Devices) with a detection limit of 800 nmol L\\u207b\\u00b9 P.
P-hydrolysis of model DOP substrates: Field samples were incubated with the
fluorogenic probe 4-methylumbeliferone phosphate (MUF-P) and two inorganic
polyphosphate compounds with an average chain length of 3 or 45 P atoms.
Samples were amended with each substrate at a final concentration of 20 M P.
This concentration was assumed to be rate-saturating based on preliminary
experiments. Hydrolysis of polyphosphates was determined from the production
of phosphate using the colorimetric protocol outlined above. Hydrolysis of the
fluorogenic probe MUF-P was monitored using a standard fluorescence technique.
Briefly, hydrolysis of MUF-P to 4-methylumbellierone (MUF) was measured
(excitation: 359 nm, emission: 449 nm) and calibrated with a multi-point
standard curve of MUF (10\\u2013500 nmol L\\u207b\\u00b9). In both methods,
samples were corrected for substrate autohydrolysis by accounting for negative
controls, which were filtered (0.2 m) and boiled (99C, 15 min) prior to P
amendment in order to eliminate enzyme activity. See Diaz et al. 2018
Frontiers in Marine Science 5: 380 for full methods.";
String awards_0_award_nid "757060";
String awards_0_award_number "OCE-1559124";
String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1559124";
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 awards_1_award_nid "757065";
String awards_1_award_number "OCE-1559087";
String awards_1_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1559087";
String awards_1_funder_name "NSF Division of Ocean Sciences";
String awards_1_funding_acronym "NSF OCE";
String awards_1_funding_source_nid "355";
String awards_1_program_manager "Henrietta N Edmonds";
String awards_1_program_manager_nid "51517";
String cdm_data_type "Other";
String comment
"Phosphohydrolysis rates in the coastal western North Atlantic
PI: Julia Diaz (SkIO)
Co-PI: Yuanzhi Tang (GA Tech)
Version date: 08-May-2019";
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 "2019-05-07T20:18:53Z";
String date_modified "2019-05-14T13:44:05Z";
String defaultDataQuery "&time<now";
String doi "10.1575/1912/bco-dmo.767022.1";
Float64 Easternmost_Easting -70.66917;
Float64 geospatial_lat_max 41.54397;
Float64 geospatial_lat_min 39.41208;
String geospatial_lat_units "degrees_north";
Float64 geospatial_lon_max -70.66917;
Float64 geospatial_lon_min -73.24917;
String geospatial_lon_units "degrees_east";
Float64 geospatial_vertical_max 35.0;
Float64 geospatial_vertical_min 5.0;
String geospatial_vertical_positive "down";
String geospatial_vertical_units "m";
String history
"2024-12-20T22:29:29Z (local files)
2024-12-20T22:29:29Z https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_767022.html";
String infoUrl "https://www.bco-dmo.org/dataset/767022";
String institution "BCO-DMO";
String instruments_0_acronym "Niskin bottle";
String instruments_0_dataset_instrument_nid "767235";
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_1_acronym "Turner Fluorometer -10AU";
String instruments_1_dataset_instrument_nid "767237";
String instruments_1_description "The Turner Designs 10-AU Field Fluorometer is used to measure Chlorophyll fluorescence. The 10AU Fluorometer can be set up for continuous-flow monitoring or discrete sample analyses. A variety of compounds can be measured using application-specific optical filters available from the manufacturer. (read more from Turner Designs, turnerdesigns.com, Sunnyvale, CA, USA)";
String instruments_1_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L22/current/TOOL0393/";
String instruments_1_instrument_name "Turner Designs Fluorometer -10-AU";
String instruments_1_instrument_nid "464";
String instruments_1_supplied_name "10AU fluorometer (Turner)";
String instruments_2_acronym "Flow Cytometer";
String instruments_2_dataset_instrument_nid "767238";
String instruments_2_description
"Flow cytometers (FC or FCM) are automated instruments that quantitate properties of single cells, one cell at a time. They can measure cell size, cell granularity, the amounts of cell components such as total DNA, newly synthesized DNA, gene expression as the amount messenger RNA for a particular gene, amounts of specific surface receptors, amounts of intracellular proteins, or transient signalling events in living cells.
(from: http://www.bio.umass.edu/micro/immunology/facs542/facswhat.htm)";
String instruments_2_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/LAB37/";
String instruments_2_instrument_name "Flow Cytometer";
String instruments_2_instrument_nid "660";
String instruments_2_supplied_name "Guava EasyCyte HT flow cytometer (Millipore)";
String instruments_3_dataset_instrument_nid "767236";
String instruments_3_description "A pump is a device that moves fluids (liquids or gases), or sometimes slurries, by mechanical action. Pumps can be classified into three major groups according to the method they use to move the fluid: direct lift, displacement, and gravity pumps";
String instruments_3_instrument_name "Pump";
String instruments_3_instrument_nid "726";
String instruments_3_supplied_name "peristaltic pump";
String instruments_4_dataset_instrument_nid "767239";
String instruments_4_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_4_instrument_name "plate reader";
String instruments_4_instrument_nid "528693";
String instruments_4_supplied_name "multimode plate reader (Molecular Devices)";
String keywords "abundance, bacterial, Bacterial_abundance, Bacterial_abundance_to_Total_phytoplankton, bco, bco-dmo, biological, chemical, chemistry, chlorophyll, concentration, concentration_of_chlorophyll_in_sea_water, data, dataset, density, depth, dmo, earth, Earth Science > Oceans > Ocean Chemistry > Chlorophyll, Earth Science > Oceans > Salinity/Density > Salinity, erddap, eukaryotic, hydrolysis, inorganic, Inorganic_poly_P_hydrolysis, large, Large_eukaryotic_phytoplankton, latitude, longitude, management, muf, MUF_P_hydrolysis, nanoeukaryotic, Nanoeukaryotic_phytoplankton, ocean, oceanography, oceans, office, phytoplankton, picoeukaryotic, Picoeukaryotic_phytoplankton, poly, practical, preliminary, reactive, salinity, science, sea, sea_water_practical_salinity, seawater, soluble, Soluble_reactive_P, spp, station, synechococcus, Synechococcus_spp, temperature, total, Total_phytoplankton, water";
String keywords_vocabulary "GCMD Science Keywords";
String license "https://www.bco-dmo.org/dataset/767022/license";
String metadata_source "https://www.bco-dmo.org/api/dataset/767022";
Float64 Northernmost_Northing 41.54397;
String param_mapping "{'767022': {'Lat': 'flag - latitude', 'Depth': 'flag - depth', 'Long': 'flag - longitude'}}";
String parameter_source "https://www.bco-dmo.org/mapserver/dataset/767022/parameters";
String people_0_affiliation "Skidaway Institute of Oceanography";
String people_0_affiliation_acronym "SkIO";
String people_0_person_name "Julia Diaz";
String people_0_person_nid "747718";
String people_0_role "Principal Investigator";
String people_0_role_type "originator";
String people_1_affiliation "Georgia Institute of Technology";
String people_1_affiliation_acronym "Georgia Tech";
String people_1_person_name "Yuanzhi Tang";
String people_1_person_nid "757067";
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 "Shannon Rauch";
String people_2_person_nid "51498";
String people_2_role "BCO-DMO Data Manager";
String people_2_role_type "related";
String project "PolyP and P-minerals";
String projects_0_acronym "PolyP and P-minerals";
String projects_0_description
"NSF Award Abstract:
Phosphorous is an important nutrient sustaining all forms of life. In particular, in the ocean, phosphorous is a key limiting nutrient, controlling levels of primary productivity across large swaths of the ocean. Removal of phosphorous occurs largely via formation of stable apatite minerals in ocean sediments. However, average ocean conditions generally inhibit the formation of apatite, thus the abundance of apatite minerals in marine sediments is a mystery. This research aims to determine the mechanisms of apatite formation in the ocean to answer this century-old question. Evaluating these mechanisms will greatly advance current understanding of phosphorous cycling in the ocean. A more detailed understanding of phosphorous cycling can be applied across the disciplines of ocean science, and because of the importance of phosphorous as a nutrient and an element with a variety of interactions with other elements, it will be applicable to a variety of other research questions. The researchers are dedicated to promoting diversity in ocean science and plan to include undergraduate students from underrepresented groups in the study. They will also mentor a postdoc and communicate their science to the public and K-12 teachers via a blog entitled ?Britannica Blog?, the Atlanta Science Festival, a rock show, and educational material, the latter two to be developed as part of this work.
Marine phosphorous burial via authigenic stable apatite formation in sediments is a major pathway for phosphorous removal in the ocean. However, in most marine environments, under natural conditions, this process is kinetically inhibited. It has been a mystery for more than a century as to how it is therefore possible for apatite to be oversaturated in large areas of marine sediments. A possible mechanism that could explain 95% of the apatite burial flux is that apatite minerals are precipitated as fine-grained particles from exogenous polyphosphate intermediates. Exogenous polyphosphates have been understudied, despite this possible importance as a mechanism for phosphorous removal. As a consequence this research could revolutionize current understanding of phosphorous cycling in the ocean for the major aim is to make a thorough and detailed study of the mechanisms behind marine apatite formation, focusing on the role of exogenous polyphosphate particles. Phosphorous is an element with widespread importance in ocean sciences, and more clearly understanding its burial will have applications across the disciplines.";
String projects_0_end_date "2020-01";
String projects_0_name "Collaborative Research: Exploring the role of exogenous polyphosphate in the precipitation of calcium phosphate minerals in the marine environment";
String projects_0_project_nid "757061";
String projects_0_start_date "2016-02";
String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
String publisher_type "institution";
String sourceUrl "(local files)";
Float64 Southernmost_Northing 39.41208;
String standard_name_vocabulary "CF Standard Name Table v55";
String summary "Phosphohydrolysis rates from samples collected in the coastal western North Atlantic on R/V Endeavor cruise EN588 during September 2016.";
String title "[Phosphohydrolysis rates in the coastal western North Atlantic] - Phosphohydrolysis rates from samples collected in the coastal western North Atlantic on R/V Endeavor cruise EN588 during September 2016 (Collaborative Research: Exploring the role of exogenous polyphosphate in the precipitation of calcium phosphate minerals in the marine environment)";
String version "1";
Float64 Westernmost_Easting -73.24917;
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.