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     data   graph     files  public Carbon and nitrogen flux measurements from the Sargasso Sea from 2013-2014.    ?     I   M   background (external link) RSS BCO-DMO bcodmo_dataset_728383

The Dataset's Variables and Attributes

Row Type Variable Name Attribute Name Data Type Value
attribute NC_GLOBAL access_formats String .htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson
attribute NC_GLOBAL acquisition_description String Particle flux measurements and images of settled particles were obtained from
neutrally-buoyant sediment trap (NBST) deployments during a series of five
short cruises in conjunction with the Bermuda Atlantic Time-series Study
(BATS) in the Sargasso Sea from July 2013 to March 2014. The NBST platforms
were constructed around Sounding Oceanographic Lagrangian Observer (SOLO)
profiling floats and carried four sediment trap tubes with areas of 0.0113 m2
(see [https://www.bco-dmo.org/instrument/632](\\"http://www.bco-
dmo.org/instrument/632\\")). NBSTs were programmed to descend to a single
measurement depth (150, 200, 300 or 500 m), sample for a 2\u20133 d period,
and then ascend to the surface for recovery. Details are described fully in
Durkin et al. (2015) and Estapa et al. (2017).

To preserve settling particulate matter for carbon analysis, three trap tubes
were filled with filtered seawater from beneath the mixed layer and 500 mL of
formalin-poisoned brine was then added to the bottom through a tube. After
trap recovery and a settling period of >1 h, the upper seawater layer was
siphoned off each tube and the lower brine layer was drained through a
350-\u03bcm screen to separate the sinking fraction from zooplankton presumed
to have actively entered the trap (Lamborg et al., 2008; Owens et al., 2013).
Owens et al. (2013) found no significant difference between wet-picked and
screened trap samples collected over multiple seasons at BATS. The
<350-\u03bcm and screened zooplankton fractions were filtered onto separate,
precombusted GF/F filters, immediately frozen at -20\u00b0C, dried overnight
at 45 \u00b1 5\u00b0C on shore, and analyzed for total carbon (TC) and total
nitrogen (TN) content via combustion elemental analysis (note that particulate
inorganic carbon fluxes at the BATS site are typically low, on average 5% of
TC at 150 m; Owens et al., 2013). One TC and TN measurement was made per trap
tube. One additional trap tube was identically prepared and processed, but was
kept covered in the ship\u2019s lab during the deployment period to serve as a
process blank.

A fourth tube on each NBST was loaded with a polyacrylamide gel insert to
preserve sizes and shapes of settling particles for imaging. Polyacrylamide
gel layers were prepared in 11-cm diameter polycarbonate jars using methods
described in previous studies (Ebersbach and Trull, 2008; Lundsgaard, 1995;
McDonnell and Buesseler, 2010) with slight modifications. To prepare 12%
polyacrylamide gel, 7.5 g of sea salts was dissolved into 400 mL of surface
seawater from Vineyard Sound, MA, USA and filtered through a 0.2-\u03bcm
polycarbonate filter. The filtered brine was boiled for 15 min to reduce the
oxygen content and reduce the brine volume to 350 mL. The solution was bubbled
with nitrogen gas through glass pipet tips attached to a pressurized tank
while the solution cooled to room temperature. The container of brine was then
placed in an ice bath on a stir plate and 150 mL of 40% acrylamide solution
and 1 g of ammonium persulfate was added to the solution while stirring. After
the ammonium persulfate dissolved, 1 mL of tetramethylethylenediamine was
added to catalyze polymerization. Gels were stored at 4\u00b0C until use.
Prior to deployment, a jar containing a layer of polyacrylamide gel was fitted
to the bottom of the trap tube and the tube was filled with filtered seawater.
Upon recovery and a settling period of >1 h, the overlying seawater was pumped
down to the top of the gel jar and the gel insert was removed and stored at
4\u00b0C until analysis. One additional gel trap tube was identically prepared
and processed, but was kept covered in the ship's lab during the deployment
period to serve as a process blank.

A series of photomicrographs was taken of each gel trap at 7\u00d7, 16\u00d7,
and 63\u00d7 magnifications using an Olympus SZX12 stereomicroscope with an
Olympus Qcolor 5 camera attachment and QCapture imaging software. At a
magnification of 7\u00d7, 49\u201367% of the gel surface area was imaged in
16\u201322 fields of view (0.1 pixels per \u03bcm) in a single focal plane. At
16\u00d7, 17\u201338% of the gel surface area was imaged in randomly
distributed fields of view (0.236 pixels per \u03bcm) across the entire gel
surface. At this magnification, a single focal plane could not capture every
particle within one field of view; large particles typically accumulated
toward the bottom of the gel layer and relatively small particles were
distributed in more focal planes throughout the gel layer. To reduce the
underestimation of small particle abundance, two images were taken from
different focal planes in each field of view (27\u201360 fields, 54\u2013120
images). At 63\u00d7, 0.5\u20130.8% of the total gel surface area was imaged
(12\u201320 fields of view). Images were taken in cross-sections spanning the
diameter of the gel. The purpose of imaging a small percentage of the gel at
high magnification was to accurately quantify the abundance of small
particles. Between 11 and 15 focal planes were imaged in each field of view
(0.746 pixels per \u03bcm), depending on the depth of the gel and how many
distinct focal planes contained particles. Imaging the same particle twice
within one field of view was avoided by ensuring that focal planes did not
include overlapping particles. Between 132 and 220 images were captured of
each gel at 63\u00d7 magnification. By imaging at three magnifications,
between 240 and 360 images were captured of each gel. Image files are named as
\u2018month_trapdepth_magnification_fieldofview_focalplane.tiff\u2019, with
field of view represented as sequential integers and focal plane represented
as sequential letters. Recognizable zooplankton, presumed to have actively
entered the gel traps, were also counted manually in 40 fields of view per gel
at 32\u00d7 magnification.

Flux measurements and images are not available at 200 m for the July 5, 2013
deployment due to failure of the lid closure mechanisms on all tubes.
Occasionally a single tube sample was compromised during collection or
analysis and only two replicate flux measurements are reported.
attribute NC_GLOBAL awards_0_award_nid String 644826
attribute NC_GLOBAL awards_0_award_number String OCE-1406552
attribute NC_GLOBAL awards_0_data_url String http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1406552 (external link)
attribute NC_GLOBAL awards_0_funder_name String NSF Division of Ocean Sciences
attribute NC_GLOBAL awards_0_funding_acronym String NSF OCE
attribute NC_GLOBAL awards_0_funding_source_nid String 355
attribute NC_GLOBAL awards_0_program_manager String Dr Henrietta N Edmonds
attribute NC_GLOBAL awards_0_program_manager_nid String 51517
attribute NC_GLOBAL cdm_data_type String Other
attribute NC_GLOBAL comment String NBST Flux Data
M. Estapa and K. Buesseler, PIs
Version 26 February 2018
attribute NC_GLOBAL Conventions String COARDS, CF-1.6, ACDD-1.3
attribute NC_GLOBAL creator_email String info at bco-dmo.org
attribute NC_GLOBAL creator_name String BCO-DMO
attribute NC_GLOBAL creator_type String institution
attribute NC_GLOBAL creator_url String https://www.bco-dmo.org/ (external link)
attribute NC_GLOBAL data_source String extract_data_as_tsv version 2.2d 13 Jun 2019
attribute NC_GLOBAL date_created String 2018-02-26T20:24:59Z
attribute NC_GLOBAL date_modified String 2018-11-15T17:34:15Z
attribute NC_GLOBAL defaultDataQuery String &time
attribute NC_GLOBAL doi String 10.1575/1912/bco-dmo.734344
attribute NC_GLOBAL Easternmost_Easting double -64.1366
attribute NC_GLOBAL geospatial_lat_max double 31.7057
attribute NC_GLOBAL geospatial_lat_min double 31.5564
attribute NC_GLOBAL geospatial_lat_units String degrees_north
attribute NC_GLOBAL geospatial_lon_max double -64.1366
attribute NC_GLOBAL geospatial_lon_min double -64.2057
attribute NC_GLOBAL geospatial_lon_units String degrees_east
attribute NC_GLOBAL geospatial_vertical_max double 500.0
attribute NC_GLOBAL geospatial_vertical_min double 150.0
attribute NC_GLOBAL geospatial_vertical_positive String down
attribute NC_GLOBAL geospatial_vertical_units String m
attribute NC_GLOBAL infoUrl String https://www.bco-dmo.org/dataset/728383 (external link)
attribute NC_GLOBAL institution String BCO-DMO
attribute NC_GLOBAL instruments_0_acronym String NBST
attribute NC_GLOBAL instruments_0_dataset_instrument_description String Used to measure particles
attribute NC_GLOBAL instruments_0_dataset_instrument_nid String 729414
attribute NC_GLOBAL instruments_0_description String In general, sediment traps are specially designed containers deployed in the water column for periods of time to collect particles from the water column falling toward the sea floor. The Neutrally Buoyant Sediment Trap (NBST) was designed by researchers at Woods Hole Oceanographic Institution. The central cylinder of the NBST controls buoyancy and houses a satellite transmitter. The other tubes collect sediment as the trap drifts in currents at a predetermined depth. The samples are collected when the tubes snap shut before the trap returns to the surface. (more: https://www.whoi.edu/instruments/viewInstrument.do?id=10286)
attribute NC_GLOBAL instruments_0_instrument_external_identifier String https://vocab.nerc.ac.uk/collection/L05/current/33/ (external link)
attribute NC_GLOBAL instruments_0_instrument_name String Neutrally Buoyant Sediment Trap
attribute NC_GLOBAL instruments_0_instrument_nid String 632
attribute NC_GLOBAL instruments_0_supplied_name String NBST
attribute NC_GLOBAL instruments_1_dataset_instrument_description String Used to take photomicrographs
attribute NC_GLOBAL instruments_1_dataset_instrument_nid String 729416
attribute NC_GLOBAL instruments_1_description String Instruments that generate enlarged images of samples using the phenomena of reflection and absorption of visible light. Includes conventional and inverted instruments. Also called a "light microscope".
attribute NC_GLOBAL instruments_1_instrument_external_identifier String https://vocab.nerc.ac.uk/collection/L05/current/LAB05/ (external link)
attribute NC_GLOBAL instruments_1_instrument_name String Microscope-Optical
attribute NC_GLOBAL instruments_1_instrument_nid String 708
attribute NC_GLOBAL instruments_1_supplied_name String Olympus SZX12 stereomicroscope with an Olympus Qcolor 5 camera attachment
attribute NC_GLOBAL instruments_2_dataset_instrument_description String Used to measure TC and TN
attribute NC_GLOBAL instruments_2_dataset_instrument_nid String 729415
attribute NC_GLOBAL instruments_2_description String Instruments that quantify carbon, nitrogen and sometimes other elements by combusting the sample at very high temperature and assaying the resulting gaseous oxides. Usually used for samples including organic material.
attribute NC_GLOBAL instruments_2_instrument_external_identifier String https://vocab.nerc.ac.uk/collection/L05/current/LAB01/ (external link)
attribute NC_GLOBAL instruments_2_instrument_name String Elemental Analyzer
attribute NC_GLOBAL instruments_2_instrument_nid String 546339
attribute NC_GLOBAL instruments_2_supplied_name String Combustion Elemental Analyzer
attribute NC_GLOBAL keywords String bco, bco-dmo, biological, chemical, conc, data, dataset, date, deploy, deploy_lat, deploy_length, deploy_lon, depth, dmo, erddap, error, length, management, N_f, N_f_err, N_f_err_swimmer, N_f_swimmer, no_replicates, oceanography, office, preliminary, recover, recover_lat, recover_lon, replicates, statistics, swimmer, TC_f, TC_f_err, TC_f_err_swimmer, TC_f_swimmer, time, zoop, zoop_conc, zoop_conc_err, zoop_f, zoop_f_err
attribute NC_GLOBAL license String The data may be used and redistributed for free but is not intended
for legal use, since it may contain inaccuracies. Neither the data
Contributor, ERD, NOAA, nor the United States Government, nor any
of their employees or contractors, makes any warranty, express or
implied, including warranties of merchantability and fitness for a
particular purpose, or assumes any legal liability for the accuracy,
completeness, or usefulness, of this information.
attribute NC_GLOBAL metadata_source String https://www.bco-dmo.org/api/dataset/728383 (external link)
attribute NC_GLOBAL Northernmost_Northing double 31.7057
attribute NC_GLOBAL param_mapping String {'728383': {'deploy_lon': 'master - longitude', 'depth': 'master - depth', 'deploy_lat': 'master - latitude'}}
attribute NC_GLOBAL parameter_source String https://www.bco-dmo.org/mapserver/dataset/728383/parameters (external link)
attribute NC_GLOBAL people_0_affiliation String Skidmore College
attribute NC_GLOBAL people_0_person_name String Dr Margaret L. Estapa
attribute NC_GLOBAL people_0_person_nid String 644830
attribute NC_GLOBAL people_0_role String Principal Investigator
attribute NC_GLOBAL people_0_role_type String originator
attribute NC_GLOBAL people_1_affiliation String Woods Hole Oceanographic Institution
attribute NC_GLOBAL people_1_affiliation_acronym String WHOI
attribute NC_GLOBAL people_1_person_name String Dr Kenneth O. Buesseler
attribute NC_GLOBAL people_1_person_nid String 50522
attribute NC_GLOBAL people_1_role String Co-Principal Investigator
attribute NC_GLOBAL people_1_role_type String originator
attribute NC_GLOBAL people_2_affiliation String Skidmore College
attribute NC_GLOBAL people_2_person_name String Dr Margaret L. Estapa
attribute NC_GLOBAL people_2_person_nid String 644830
attribute NC_GLOBAL people_2_role String Contact
attribute NC_GLOBAL people_2_role_type String related
attribute NC_GLOBAL people_3_affiliation String Woods Hole Oceanographic Institution
attribute NC_GLOBAL people_3_affiliation_acronym String WHOI BCO-DMO
attribute NC_GLOBAL people_3_person_name String Hannah Ake
attribute NC_GLOBAL people_3_person_nid String 650173
attribute NC_GLOBAL people_3_role String BCO-DMO Data Manager
attribute NC_GLOBAL people_3_role_type String related
attribute NC_GLOBAL project String Rapid, Autonomous Particle Flux Observations in the Oligotrophic Ocean
attribute NC_GLOBAL projects_0_acronym String RapAutParticleFlux
attribute NC_GLOBAL projects_0_description String Particles settling into the deep ocean remove carbon and biologically-important trace elements from sunlit, productive surface waters and from contact with the atmosphere over short timescales.�A shifting balance among physical, chemical, and biological processes determines the ultimate fate of most particles at depths between 100 and 1,000 m, where fluxes are hardest to measure.�Our challenge is to expand the number of particle flux observations in the critical "twilight zone", something that has proven elusive with ship-based “snapshots” that have lengths of, at most, a few weeks.�Here, we propose an optical, transmissometer-based method to make particle flux observations from autonomous, biogeochemical profiling floats.�Novel developments in data interpretation, sensor operation, and platform control now allow flux measurements at hourly resolution and give us observational access to the water-column processes driving particle flux over short timescales.�The sensors and float platforms that we propose to use are simple, robust, and commercially-available, making them immediately compatible with community-scale efforts to implement other float-based biogeochemical measurements.
We have two main goals:� First, we will quantify particulate organic carbon (POC) flux using float-based optical measurements by validating our observations against fluxes measured directly with neutrally-buoyant, drifting sediment traps. Second, we will evaluate the contribution of rapid export events to total POC fluxes in the oligotrophic ocean by using a biogeochemical profiling float to collect nearly-continuous, depth-resolved flux measurements and coupled, water-column bio-optical profiles.�
To achieve these goals, we will implement a work plan consisting of 1) a set of laboratory-based sensor calibration experiments to determine detection limits and evaluate sensitivity to particle size; 2) a series of four sediment trap and biogeochemical float co-deployments during which we will collect POC flux and field calibration data; and 3) a long-term sampling and analysis period (approximately 1 year) during which data will be returned by satellite from the biogeochemical float.�We will conduct calibration fieldwork in conjunction with monthly Bermuda Atlantic Time-series Study (BATS) cruises, taking advantage of the timeseries measurements and the context provided by the 25-year record of POC flux at that site.�The data returned by the float will comprise the first quantitative particle flux observations made at high-enough temporal resolution to interpret in the context of short-term, upper-ocean production events.
attribute NC_GLOBAL projects_0_end_date String 2014-11
attribute NC_GLOBAL projects_0_geolocation String Sargasso Sea
attribute NC_GLOBAL projects_0_name String Rapid, Autonomous Particle Flux Observations in the Oligotrophic Ocean
attribute NC_GLOBAL projects_0_project_nid String 644827
attribute NC_GLOBAL projects_0_start_date String 2013-07
attribute NC_GLOBAL publisher_name String Hannah Ake
attribute NC_GLOBAL publisher_role String BCO-DMO Data Manager(s)
attribute NC_GLOBAL sourceUrl String (local files)
attribute NC_GLOBAL Southernmost_Northing double 31.5564
attribute NC_GLOBAL standard_name_vocabulary String CF Standard Name Table v29
attribute NC_GLOBAL summary String Nearly-continuous, optical sediment trap proxy measurements of particle flux were obtained in the Sargasso Sea over nearly a year by a beam transmissometer mounted vertically on quasi-Lagrangian profiling floats. Fluxes measured directly with neutrally-buoyant, drifting sediment traps co-deployed with the floats during a series of five BATS cruises prior to this year-long deployment provide a calibration for the float-based optical measurements. A well-correlated, positive relationship (R2=0.66, n=15) exists between the optical flux proxy and the particulate carbon flux measured directly using NBSTs.
attribute NC_GLOBAL title String Carbon and nitrogen flux measurements from the Sargasso Sea from 2013-2014.
attribute NC_GLOBAL version String 1
attribute NC_GLOBAL Westernmost_Easting double -64.2057
attribute NC_GLOBAL xml_source String osprey2erddap.update_xml() v1.5-beta
variable deploy_date   String  
attribute deploy_date description String Date of deployment; yyyy/mm/dd
attribute deploy_date ioos_category String Time
attribute deploy_date long_name String Deploy Date
attribute deploy_date source_name String deploy_date
attribute deploy_date units String unitless
variable depth   double  
attribute depth _CoordinateAxisType String Height
attribute depth _CoordinateZisPositive String down
attribute depth _FillValue double NaN
attribute depth actual_range double 150.0, 500.0
attribute depth axis String Z
attribute depth colorBarMaximum double 8000.0
attribute depth colorBarMinimum double -8000.0
attribute depth colorBarPalette String TopographyDepth
attribute depth description String The nominal depth of the NBST. During the July 2013 deployment the NBSTs were programmed to hold depth within +/-25 m of the measurement depth while in subsequent deployments this band was narrowed to +/-10 m.
attribute depth ioos_category String Location
attribute depth long_name String Depth
attribute depth positive String down
attribute depth standard_name String depth
attribute depth units String m
variable latitude   double  
attribute latitude _CoordinateAxisType String Lat
attribute latitude _FillValue double NaN
attribute latitude actual_range double 31.5564, 31.7057
attribute latitude axis String Y
attribute latitude description String Latitude of the deployment
attribute latitude ioos_category String Location
attribute latitude long_name String Deploy Lat
attribute latitude standard_name String latitude
attribute latitude units String degrees_north
variable longitude   double  
attribute longitude _CoordinateAxisType String Lon
attribute longitude _FillValue double NaN
attribute longitude actual_range double -64.2057, -64.1366
attribute longitude axis String X
attribute longitude description String Longitude of the deployment
attribute longitude ioos_category String Location
attribute longitude long_name String Deploy Lon
attribute longitude standard_name String longitude
attribute longitude units String degrees_east
variable recover_lat   float  
attribute recover_lat _FillValue float NaN
attribute recover_lat actual_range float 31.2133, 31.7852
attribute recover_lat description String Latitude of the point of recovery
attribute recover_lat ioos_category String Location
attribute recover_lat long_name String Recover Lat
attribute recover_lat units String decimal degrees
variable recover_lon   float  
attribute recover_lon _FillValue float NaN
attribute recover_lon actual_range float -64.7877, -64.252
attribute recover_lon description String Longitude of the point of recovery
attribute recover_lon ioos_category String Location
attribute recover_lon long_name String Recover Lon
attribute recover_lon units String decimal degrees
variable deploy_length   float  
attribute deploy_length _FillValue float NaN
attribute deploy_length actual_range float 1.45, 2.92
attribute deploy_length description String Days between deployment of NBST and tube lid closure
attribute deploy_length ioos_category String Unknown
attribute deploy_length long_name String Deploy Length
attribute deploy_length units String days
variable no_replicates   byte  
attribute no_replicates _FillValue byte 127
attribute no_replicates actual_range byte 2, 3
attribute no_replicates description String Number of tubes averaged to obtain mean TC and TN flux measurements at a single depth
attribute no_replicates ioos_category String Unknown
attribute no_replicates long_name String No Replicates
attribute no_replicates units String number
variable TC_f   float  
attribute TC_f _FillValue float NaN
attribute TC_f actual_range float 0.11, 1.79
attribute TC_f description String Total carbon flux of the sinking fraction operationally defined as particles
attribute TC_f ioos_category String Unknown
attribute TC_f long_name String TC F
attribute TC_f units String milligrams of carbon per square meter per day
variable TC_f_err   float  
attribute TC_f_err _FillValue float NaN
attribute TC_f_err actual_range float 0.12, 0.63
attribute TC_f_err description String Total carbon flux error; Uncertainties are propagated from the standard deviation of the process blanks from the five cruises (0.2 mg C) and the standard deviation or range of the two or three TC measurements per NBST deployment: TC_f_err = (STD tubes^2 + STD blanks^2)^1/2 / deployment length / trap area; For depths with only two replicate analyses the range of the TC fluxes measured in each tube is used in place of STDtubes in the above equation.
attribute TC_f_err ioos_category String Unknown
attribute TC_f_err long_name String TC F Err
attribute TC_f_err units String milligrams of carbon per square meter per day
variable N_f   float  
attribute N_f _FillValue float NaN
attribute N_f actual_range float 0.01, 0.22
attribute N_f description String Total nitrogen flux of the sinking fraction operationally defined as particles
attribute N_f ioos_category String Statistics
attribute N_f long_name String N F
attribute N_f units String milligrams of nitrogen per square meter per day
variable N_f_err   float  
attribute N_f_err _FillValue float NaN
attribute N_f_err actual_range float 0.02, 0.09
attribute N_f_err description String Total nitrogen flux error; Uncertainties are propagated from the standard deviation of the process blanks from the five cruises (0.006 mg N) and the standard deviation or range of the two or three TN measurements per NBST deployment.
TN_f_err = (STD tubes^2 + STD blanks^2)^1/2 / deployment length / trap area;
For depths with only two replicate analyses the range of the TN fluxes measured in each tube is used in place of STDtubes in the above equation.
attribute N_f_err ioos_category String Statistics
attribute N_f_err long_name String N F Err
attribute N_f_err units String milligrams of nitrogen per square meter per day
variable TC_f_swimmer   float  
attribute TC_f_swimmer _FillValue float NaN
attribute TC_f_swimmer actual_range float 0.18, 2.98
attribute TC_f_swimmer description String Total carbon flux of the >350-um screened fraction presumed to be zooplankton that actively entered the trap. Calculated as for 'total carbon flux' above using a >350-um process blank of 0.05 +/- 0.04 mg C.
attribute TC_f_swimmer ioos_category String Unknown
attribute TC_f_swimmer long_name String TC F Swimmer
attribute TC_f_swimmer units String milligrams of carbon per square meter per day
variable TC_f_err_swimmer   float  
attribute TC_f_err_swimmer _FillValue float NaN
attribute TC_f_err_swimmer actual_range float 0.13, 3.66
attribute TC_f_err_swimmer description String Swimmer total carbon flux error; Calculated for the >350-um screened fraction as for 'total carbon flux error' above using a >350-um process blank standard deviation of 0.04 mg C.
attribute TC_f_err_swimmer ioos_category String Unknown
attribute TC_f_err_swimmer long_name String TC F Err Swimmer
attribute TC_f_err_swimmer units String milligrams of carbon per square meter per day
variable N_f_swimmer   float  
attribute N_f_swimmer _FillValue float NaN
attribute N_f_swimmer actual_range float 0.02, 0.5
attribute N_f_swimmer description String Total nitrogen flux of the >350-um screened fraction presumed to be zooplankton that actively entered the trap. Calculated as for 'total nitrogen flux' above using a >350-um process blank of 0.005 +/- 0.003 mg N.
attribute N_f_swimmer ioos_category String Statistics
attribute N_f_swimmer long_name String N F Swimmer
attribute N_f_swimmer units String milligrams of nitrogen per square meter per day
variable N_f_err_swimmer   float  
attribute N_f_err_swimmer _FillValue float NaN
attribute N_f_err_swimmer actual_range float 0.01, 0.58
attribute N_f_err_swimmer description String Swimmer total nitrogen flux error; Calculated for the >350-um screened fraction as for 'total nitrogen flux error' above using a >350-um process blank standard deviation of 0.003 mg N.
attribute N_f_err_swimmer ioos_category String Statistics
attribute N_f_err_swimmer long_name String N F Err Swimmer
attribute N_f_err_swimmer units String milligrams of nitrogen per square meter per day
variable A   float  
attribute A _FillValue float NaN
attribute A actual_range float 4.73, 339.86
attribute A description String Flux particle size distribution magnitude and slope parameters�(parameter names ‘A’, ‘B’):�
Particles imaged in each gel at the same magnification were identified, enumerated and measured using an analysis macro created using ImageJ software. Using this macro, images were processed by 1) converting images to greyscale, 2) removing�background, 3) adjusting brightness/contrast to a consistent degree, 4) thresholding using the “Intermodes” technique, 5) filling holes, and 6) measuring particles.� Particles imaged from the same field of view but different focal planes were grouped together and the equivalent spherical diameter (ESD) of each particle was calculated based on the measured two-dimensional surface area. Particles were divided into 26 base-2, log-spaced size classes ranging from 1 um to 8192 um based on their ESD. Counting error was calculated as the square root of the number of particles counted in each size category. Size classes with 4 or fewer counted particles (≥50% error) were excluded from analysis. The abundance of particles in each size bin was calculated by normalizing the number of particles counted by the size�bin�width and by the percentage of the gel surface counted. The optimal magnification to calculate the abundance of a particle size category was defined as the magnification where the observed abundance most closely followed a power-law distribution. The abundance of 11–45 um particles�was�quantified at 63� magnification, the abundance of 45–128 um particles�was�quantified at 16� magnification, and the abundance of >128 um particles was quantified at 7� magnification. Three samples had slightly different size detection limits at each magnification and required different size ranges to quantify a power law distribution of particle abundance. For the 200-m sample collected in August, optimal particle size ranges were 11–64 um (63�), 64–90 um (16�), and >90 um (7�). For the 500-m samples collected in October and March, the optimal size ranges were 11–45 um (63�), 45–64 um (16�), and >64 um (7�). The particle abundance of all five gel trap process blanks�were�measured and averaged together, and the average was subtracted from the particle abundance measured in each gel trap sample. Particle number flux was calculated by dividing blank-subtracted particle abundance by the trap deployment time.
The slope of each particle size distribution (B) was calculated by fitting the observations of particle number flux (Num_f) to a differential power law size distribution model (Jackson et al., 1997),
Num_f(ESD) = A(ESDr) � (ESD/ESDr)−B
where A(ESDr) equals the number flux of particles in the reference size category ESDr�(here 300 um). B indicates the slope of the power law function; higher values have steeper slopes and a higher proportion of small particles relative to large particles. The “optim” function in R (R. Development Core Team, 2008) was used to find the least-squares, best-fit values of Α(ESDr) and Β describing particle number fluxes measured in each gel trap.
attribute A ioos_category String Unknown
attribute A long_name String A
attribute A units String unitless
variable B   float  
attribute B _FillValue float NaN
attribute B actual_range float 2.93, 4.02
attribute B description String Flux particle size distribution magnitude and slope parameters�(parameter names ‘A’, ‘B’):�
Particles imaged in each gel at the same magnification were identified, enumerated and measured using an analysis macro created using ImageJ software. Using this macro, images were processed by 1) converting images to greyscale, 2) removing�background, 3) adjusting brightness/contrast to a consistent degree, 4) thresholding using the “Intermodes” technique, 5) filling holes, and 6) measuring particles.� Particles imaged from the same field of view but different focal planes were grouped together and the equivalent spherical diameter (ESD) of each particle was calculated based on the measured two-dimensional surface area. Particles were divided into 26 base-2, log-spaced size classes ranging from 1 um to 8192 um based on their ESD. Counting error was calculated as the square root of the number of particles counted in each size category. Size classes with 4 or fewer counted particles (≥50% error) were excluded from analysis. The abundance of particles in each size bin was calculated by normalizing the number of particles counted by the size�bin�width and by the percentage of the gel surface counted. The optimal magnification to calculate the abundance of a particle size category was defined as the magnification where the observed abundance most closely followed a power-law distribution. The abundance of 11–45 um particles�was�quantified at 63� magnification, the abundance of 45–128 um particles�was�quantified at 16� magnification, and the abundance of >128 um particles was quantified at 7� magnification. Three samples had slightly different size detection limits at each magnification and required different size ranges to quantify a power law distribution of particle abundance. For the 200-m sample collected in August, optimal particle size ranges were 11–64 um (63�), 64–90 um (16�), and >90 um (7�). For the 500-m samples collected in October and March, the optimal size ranges were 11–45 um (63�), 45–64 um (16�), and >64 um (7�). The particle abundance of all five gel trap process blanks�were�measured and averaged together, and the average was subtracted from the particle abundance measured in each gel trap sample. Particle number flux was calculated by dividing blank-subtracted particle abundance by the trap deployment time.
The slope of each particle size distribution (B) was calculated by fitting the observations of particle number flux (Num_f) to a differential power law size distribution model (Jackson et al., 1997),
Num_f(ESD) = A(ESDr) � (ESD/ESDr)−B
where A(ESDr) equals the number flux of particles in the reference size category ESDr�(here 300 um). B indicates the slope of the power law function; higher values have steeper slopes and a higher proportion of small particles relative to large particles. The “optim” function in R (R. Development Core Team, 2008) was used to find the least-squares, best-fit values of Α(ESDr) and Β describing particle number fluxes measured in each gel trap.
attribute B ioos_category String Unknown
attribute B long_name String B
attribute B units String unitless
variable zoop_conc   int  
attribute zoop_conc _FillValue int 2147483647
attribute zoop_conc actual_range int 1299, 35729
attribute zoop_conc description String Zooplankton concentration; Recognizable zooplankton presumed to have actively entered the gel traps were counted manually in 40 fields of view at 32_ magnification on the stereomicroscope. The number of individuals counted was normalized by the percentage of gel surface counted and divided by the total surface area of the gel (0.0095 m^2).
attribute zoop_conc ioos_category String Unknown
attribute zoop_conc long_name String Zoop Conc
attribute zoop_conc units String individuals per square meter
variable zoop_conc_err   short  
attribute zoop_conc_err _FillValue short 32767
attribute zoop_conc_err actual_range short 919, 4818
attribute zoop_conc_err description String Zooplankton concentration error; Calculated as the square root of the number of individuals counted normalized by the percentage of gel surface counted and divided by the total surface area of the gel (0.0095 m^2).
attribute zoop_conc_err ioos_category String Unknown
attribute zoop_conc_err long_name String Zoop Conc Err
attribute zoop_conc_err units String individuals per square meter
variable zoop_f   short  
attribute zoop_f _FillValue short 32767
attribute zoop_f actual_range short 494, 14583
attribute zoop_f description String Zooplankton flux; The zooplankton concentration calculated above was divided by the deployment length to yield flux.
attribute zoop_f ioos_category String Unknown
attribute zoop_f long_name String Zoop F
attribute zoop_f units String individuals per square meter per day
variable zoop_f_err   short  
attribute zoop_f_err _FillValue short 32767
attribute zoop_f_err actual_range short 347, 2029
attribute zoop_f_err description String Zooplankton flux error; Calculated as the square root of the number of individuals counted normalized by the percentage of gel surface counted and divided by the total surface area of the gel (0.0095 m^2) and the deployment length.
attribute zoop_f_err ioos_category String Unknown
attribute zoop_f_err long_name String Zoop F Err
attribute zoop_f_err units String individuals per square meter per day

The information in the table above is also available in other file formats (.csv, .htmlTable, .itx, .json, .jsonlCSV, .jsonlKVP, .mat, .nc, .nccsv, .tsv, .xhtml) via a RESTful web service.


 
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