ERDDAP > info > bcodmo_dataset_728383

Grid DAP Data	Sub- set	Table DAP Data	Make A Graph	W M S	Source Data Files	Acces- sible	Title	Sum- mary	FGDC, ISO, Metadata	Back- ground Info	RSS	E mail	Institution	Dataset ID
		data	graph		files	public	[NBST flux measurements] - Carbon and nitrogen flux measurements from the Sargasso Sea from 2013-2014. (Rapid, Autonomous Particle Flux Observations in the Oligotrophic Ocean)		F   I   M	background			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
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	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/
attribute	NC_GLOBAL	data_source	String	extract_data_as_tsv version 2.3 19 Dec 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	&amp;time&lt;now
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
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/
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/
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/
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, 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	https://www.bco-dmo.org/dataset/728383/license
attribute	NC_GLOBAL	metadata_source	String	https://www.bco-dmo.org/api/dataset/728383
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
attribute	NC_GLOBAL	people_0_affiliation	String	Skidmore College
attribute	NC_GLOBAL	people_0_person_name	String	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	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	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	RapAutParticleFlux
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	Biological and Chemical Oceanographic Data Management Office (BCO-DMO)
attribute	NC_GLOBAL	publisher_type	String	institution
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 v55
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	[NBST flux measurements] - Carbon and nitrogen flux measurements from the Sargasso Sea from 2013-2014. (Rapid, Autonomous Particle Flux Observations in the Oligotrophic Ocean)
attribute	NC_GLOBAL	version	String	1
attribute	NC_GLOBAL	Westernmost_Easting	double	-64.2057
attribute	NC_GLOBAL	xml_source	String	osprey2erddap.update_xml() v1.3
variable	deploy_date		String
attribute	deploy_date	bcodmo_name	String	date
attribute	deploy_date	description	String	Date of deployment; yyyy/mm/dd
attribute	deploy_date	long_name	String	Deploy Date
attribute	deploy_date	nerc_identifier	String	https://vocab.nerc.ac.uk/collection/P01/current/ADATAA01/
attribute	deploy_date	source_name	String	deploy_date
attribute	deploy_date	time_precision	String	1970-01-01
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	bcodmo_name	String	depth
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	nerc_identifier	String	https://vocab.nerc.ac.uk/collection/P09/current/DEPH/
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	bcodmo_name	String	latitude
attribute	latitude	description	String	Latitude of the deployment
attribute	latitude	ioos_category	String	Location
attribute	latitude	long_name	String	Deploy Lat
attribute	latitude	nerc_identifier	String	https://vocab.nerc.ac.uk/collection/P09/current/LATX/
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	bcodmo_name	String	longitude
attribute	longitude	description	String	Longitude of the deployment
attribute	longitude	ioos_category	String	Location
attribute	longitude	long_name	String	Deploy Lon
attribute	longitude	nerc_identifier	String	https://vocab.nerc.ac.uk/collection/P09/current/LONX/
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	bcodmo_name	String	latitude
attribute	recover_lat	description	String	Latitude of the point of recovery
attribute	recover_lat	long_name	String	Recover Lat
attribute	recover_lat	nerc_identifier	String	https://vocab.nerc.ac.uk/collection/P09/current/LATX/
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	bcodmo_name	String	longitude
attribute	recover_lon	description	String	Longitude of the point of recovery
attribute	recover_lon	long_name	String	Recover Lon
attribute	recover_lon	nerc_identifier	String	https://vocab.nerc.ac.uk/collection/P09/current/LONX/
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	bcodmo_name	String	duration
attribute	deploy_length	description	String	Days between deployment of NBST and tube lid closure
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	bcodmo_name	String	count
attribute	no_replicates	description	String	Number of tubes averaged to obtain mean TC and TN flux measurements at a single depth
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	bcodmo_name	String	TOC
attribute	TC_f	description	String	Total carbon flux of the sinking fraction operationally defined as particles
attribute	TC_f	long_name	String	TC F
attribute	TC_f	nerc_identifier	String	https://vocab.nerc.ac.uk/collection/P01/current/CORGCOTX/
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	bcodmo_name	String	TOC
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	long_name	String	TC F Err
attribute	TC_f_err	nerc_identifier	String	https://vocab.nerc.ac.uk/collection/P01/current/CORGCOTX/
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	bcodmo_name	String	TON
attribute	N_f	description	String	Total nitrogen flux of the sinking fraction operationally defined as particles
attribute	N_f	long_name	String	N F
attribute	N_f	nerc_identifier	String	https://vocab.nerc.ac.uk/collection/P01/current/NTOTZZZZ/
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	bcodmo_name	String	TON
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	long_name	String	N F Err
attribute	N_f_err	nerc_identifier	String	https://vocab.nerc.ac.uk/collection/P01/current/NTOTZZZZ/
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	bcodmo_name	String	TOC
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	long_name	String	TC F Swimmer
attribute	TC_f_swimmer	nerc_identifier	String	https://vocab.nerc.ac.uk/collection/P01/current/CORGCOTX/
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	bcodmo_name	String	TOC
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	long_name	String	TC F Err Swimmer
attribute	TC_f_err_swimmer	nerc_identifier	String	https://vocab.nerc.ac.uk/collection/P01/current/CORGCOTX/
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	bcodmo_name	String	TON
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	long_name	String	N F Swimmer
attribute	N_f_swimmer	nerc_identifier	String	https://vocab.nerc.ac.uk/collection/P01/current/NTOTZZZZ/
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	bcodmo_name	String	TON
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	long_name	String	N F Err Swimmer
attribute	N_f_err_swimmer	nerc_identifier	String	https://vocab.nerc.ac.uk/collection/P01/current/NTOTZZZZ/
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	bcodmo_name	String	unknown
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	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	bcodmo_name	String	unknown
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	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	bcodmo_name	String	abundance
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	long_name	String	Zoop Conc
attribute	zoop_conc	nerc_identifier	String	https://vocab.nerc.ac.uk/collection/P03/current/B070/
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	bcodmo_name	String	abundance
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	long_name	String	Zoop Conc Err
attribute	zoop_conc_err	nerc_identifier	String	https://vocab.nerc.ac.uk/collection/P03/current/B070/
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	bcodmo_name	String	abundance
attribute	zoop_f	description	String	Zooplankton flux; The zooplankton concentration calculated above was divided by the deployment length to yield flux.
attribute	zoop_f	long_name	String	Zoop F
attribute	zoop_f	nerc_identifier	String	https://vocab.nerc.ac.uk/collection/P03/current/B070/
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	bcodmo_name	String	abundance
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	long_name	String	Zoop F Err
attribute	zoop_f_err	nerc_identifier	String	https://vocab.nerc.ac.uk/collection/P03/current/B070/
attribute	zoop_f_err	units	String	individuals per square meter per day

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