http://lod.bco-dmo.org/id/dataset/847036
eng; USA
utf8
dataset
Highest level of data collection, from a common set of sensors or instrumentation, usually within the same research project
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact
2021-03-30
ISO 19115-2 Geographic Information - Metadata - Part 2: Extensions for Imagery and Gridded Data
ISO 19115-2:2009(E)
Particle fluxes calculated from gel trap images taken on R/V Endeavor and R/V Falkor cruises off the New England shelf break and in the North Pacific during 2016-2017
2021-04-08
publication
2021-04-08
revision
Marine Biological Laboratory/Woods Hole Oceanographic Institution Library (MBLWHOI DLA)
2021-04-08
publication
https://doi.org/10.26008/1912/bco-dmo.847036.1
Colleen Durkin
Moss Landing Marine Laboratories
principalInvestigator
Margaret L. Estapa
Skidmore College
principalInvestigator
Melissa Omand
University of Rhode Island
principalInvestigator
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
publisher
Cite this dataset as: Durkin, C., Estapa, M. L., Omand, M. (2021) Particle fluxes calculated from gel trap images taken on R/V Endeavor and R/V Falkor cruises off the New England shelf break and in the North Pacific during 2016-2017. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2021-04-08 [if applicable, indicate subset used]. doi:10.26008/1912/bco-dmo.847036.1 [access date]
Particle Flux Dataset Description: <p>Samples were collected at the New England shelf break aboard the R/V Endeavor on 3-7 November 2017 (EN572) and 13-18 June 2016 (EN581) and on a transit between Honolulu, Hawaii and Portland, Oregon aboard the R/V Falkor between 24 January-20 February, 2017 (FK170124).</p> Methods and Sampling: <p><strong>Image Acquisition</strong>:<br />
For more information on sediment trap deployment and image acquisition, see the related dataset "Geltrap micrographs" (<a href="https://www.bco-dmo.org/dataset/749412" target="_blank">https://www.bco-dmo.org/dataset/749412</a>). In brief, sediment trap collector tubes were deployed on various platform designs, including a neutrally-buoyant sediment trap (NBST), a surface tethered sediment trap (STST), and a Wire Walker (WW) trap. Trap tubes were filled with filtered water overlying a jar containing a polyacrylamide gel layer (Durkin et al. 2015). Upon recovery, collection tubes were allowed to settle for at least 1 hour before the overlying water was siphoned off. Jars containing polyacrylamide gel were removed from trap tubes and the remaining overlying water was carefully pipetted off the gel. Gels were stored at 4 degrees C and imaged within the following 2 days before being stored at -80 degrees C.</p>
<p>Polyacrylamide gel layers were imaged on a dissecting microscope (Olympus SZX16) with either a Luminera Infinity 2 (FK170124) or an Allied Vision Technologies StingRay (EN572 and EN581) camera attachment. Particles collected in gel layers during EN572 and EN581 were imaged under brightfield illumination. Particles collected in gel layers during FK170124 were imaged under both brightfield and oblique illumination, producing two separate sets of images for each sample. EN572 gel layers were imaged with a transparent grid to assist in tracking gel location during imaging. The grid was not used when imaging samples collected during subsequent cruises because the pronounced grid lines complicated image analysis. All gel layers were imaged at 4 increasing magnifications, though the combination of magnifications varied by cruise. To determine whether measured particle properties changed if gel layers are frozen, samples collected during FK170124 were thawed after being stored for approximately 1 year at -80 degrees C and imaged again under both brightfield and oblique illumination</p>
<p><strong>Determination of Particle Flux:</strong><br />
Particles in gel images were quantified with an image processing protocol created using functions available in python’s Sci-Kit Image. Particles present in each micrograph were detected through a series of image transformation steps that maximize the detection of entire particle areas while minimizing the detection of imaging noise. The background was removed, a brightness threshold was applied, and an edge-detection kernel transformation was used to identify the in-focus particles. Duplicate particles detected in multiple focal planes were removed and the remaining particles were counted and measured.<br />
<br />
Particles were categorized into 9 different sinking particle classes. Identities were assigned by manually identifying particle images. Aggregates were defined as loosely packed detritus with irregular edges. Dense detritus was defined as densely packed amorphous material, often brown or golden in color. Large, loose pellets were similar to dense detritus but were also elongated like a fecal pellet. Long fecal pellets were defined as long, thin, cylindrical fecal pellets with a smooth edge, such as the chitin-encased pellets produced by euphausiids. Short fecal pellets were also smooth-edged pellets but with an oval or ellipsoid shape, such as those produced by larvaceans. Mini pellets were defined as small (usually &lt;100 micrometer ESD), spheres such as those produced by rhizarians and microzooplankton (Gowing &amp; Silver, 1985). A small number of individual organisms considered to be passively sinking were also detected, including Rhizarians, primarily Phaeodaria, and various phytoplankton, usually diatoms. Pteropods, copepods, amphipods, foraminifera, and other zooplankton that probably swam into the gel and human-produced fibers were also detected but not considered passive flux and not included in the categories of sinking particles. Unidentifiable objects were also detected and were likely caused by out-of-focus particles, shadows, smudges, or noise detected by the image processing steps that are sensitive to the particular thresholds used.</p>
<p>Only identifiable, sinking particle classes from the dataset were considered in calculations of sinking flux. For each imaging magnification, particles were grouped by their equivalent spherical diameter (ESD) into logarithmically-scaled size bins. To calculate number fluxes at each magnification, the number of particles counted in each size bin was divided by the total imaged surface area of the gel and the trap collection time. Uncertainty of the number flux was estimated by applying these same calculations to the counting uncertainty (square root of the number of particles counted, ie. Poisson distribution).</p>
<p>The carbon flux by each particle type was determined by modeling particle volumes, calculating the carbon per unit volume, and multiplying the carbon per particle by the measured particle number fluxes in each size category.</p>
Funding provided by NSF Division of Ocean Sciences (NSF OCE) Award Number: OCE-1703664 Award URL: https://www.nsf.gov/awardsearch/show-award?AWD_ID=1703664
completed
Colleen Durkin
Moss Landing Marine Laboratories
831-771-4431
8272 Moss Landing Road
Moss Landing
CA
95039-9647
USA
cdurkin@mbari.org
pointOfContact
Margaret L. Estapa
Skidmore College
207-581-5176
193 Clarks Cove Road
Walpole
ME
04573
United States
margaret.estapa@maine.edu
pointOfContact
Melissa Omand
University of Rhode Island
401-874-6610
215 S Ferry Rd
Narrangsett
RI
02882-1197
USA
momand@uri.edu
pointOfContact
asNeeded
Dataset Version: 1
Unknown
orig_file_name
trap
cruise_id
depth_meters
trap_platform
deployment_duration
bin_mids
bin_width
flux
flux_uncertainty
number_counted
aggregate_flux
aggregate_flux_uncertainty
aggregate_number_counted
long_fp_flux
long_fp_flux_uncertainty
long_fp_number_counted
dense_detritus_flux
dense_detritus_flux_uncertainty
dense_detritus_number_counted
large_loose_flux
large_loose_flux_uncertainty
large_loose_number_counted
short_fp_flux
short_fp_flux_uncertainty
short_fp_number_counted
mini_pellet_flux
mini_pellet_flux_uncertainty
mini_pellet_number_counted
salp_pellet_flux
salp_pellet_flux_uncertainty
salp_pellet_number_counted
phyto_flux
phyto_flux_uncertainty
phyto_number_counted
foraminifera_flux
foraminifera_flux_uncertainty
foraminifera_number_counted
rhizaria_flux
rhizaria_flux_uncertainty
rhizaria_number_counted
fiber_flux
fiber_flux_uncertainty
fiber_number_counted
copepod_flux
copepod_flux_uncertainty
copepod_number_counted
pteropod_flux
pteropod_flux_uncertainty
pteropod_number_counted
amphipod_flux
amphipod_flux_uncertainty
amphipod_number_counted
other_zooplankton_flux
other_zooplankton_flux_uncertainty
other_zooplankton_number_counted
zooplankton_part_flux
zooplankton_part_flux_uncertainty
zooplankton_part_number_counted
unidentifiable_flux
unidentifiable_flux_uncertainty
unidentifiable_number_counted
long_fp_Cflux
short_fp_Cflux
salp_fp_Cflux
mini_fp_Cflux
phytoplankton_Cflux
rhizaria_Cflux
agg_Cflux
dense_Cflux
large_fp_Cflux
long_fp_Cflux_uncertainty
short_fp_Cflux_uncertainty
salp_fp_Cflux_uncertainty
mini_fp_Cflux_uncertainty
phytoplankton_Cflux_uncertainty
rhizaria_Cflux_uncertainty
agg_Cflux_uncertainty
dense_Cflux_uncertainty
large_fp_Cflux_uncertainty
long_fp_Vflux
short_fp_Vflux
salp_fp_Vflux
mini_fp_Vflux
phytoplankton_Vflux
rhizaria_Vflux
agg_Vflux
dense_Vflux
large_fp_Vflux
Luminera Infinity 2 microscope camera
Olympus SZX16 Stereomicroscope
theme
None, User defined
file_name
type of sediment trap
cruise name
depth
platform
duration
No BCO-DMO term
flux
count
featureType
BCO-DMO Standard Parameters
Camera
Microscope - Optical
Sediment Trap
instrument
BCO-DMO Standard Instruments
EN572
EN581
FK170124
service
Deployment Activity
North Pacific Ocean
place
Locations
otherRestrictions
otherRestrictions
Access Constraints: none. Use Constraints: Please follow guidelines at: http://www.bco-dmo.org/terms-use Distribution liability: Under no circumstances shall BCO-DMO be liable for any direct, incidental, special, consequential, indirect, or punitive damages that result from the use of, or the inability to use, the materials in this data submission. If you are dissatisfied with any materials in this data submission your sole and exclusive remedy is to discontinue use.
Collaborative Research: EAGER: Particle-specific DNA sequencing to directly observe ecological mechanisms of the biological pump
https://osprey.bco-dmo.org/project/675296
Collaborative Research: EAGER: Particle-specific DNA sequencing to directly observe ecological mechanisms of the biological pump
<p><em>NSF Award Abstract:</em><br />
Carbon is fixed into organic matter by phytoplankton growing in the surface ocean, and is naturally sequestered in the ocean interior when particles and organisms sink: a process called the "biological pump." Because of its recognized influence on the global carbon cycle, ocean scientists have studied the biological pump for decades. However, we still do not have a sufficient understanding of the underlying processes to accurately quantify and predict carbon cycling. Much of this uncertainty stems from an inability to directly link specific plankton in the surface ocean with the types of particles sinking out of the surface ocean. To address this missing link in biological pump research, this work will directly observe how plankton are transported out of the surface ocean using novel, particle-specific observational approaches embedded within an interdisciplinary field program that will finely resolve upper ocean plankton groups and the resulting amount of sinking carbon across space and in time. The genetic identity of organisms within different types of sinking particles will be determined by sequencing the genetic contents of individually collected particles. This new application of a molecular method will definitively link surface plankton with sinking particles at five locations across the Pacific Ocean. This work has the potential to transform our understanding of the biological pump by identifying previously unknown links between surface ecosystems and sinking carbon particles. Because this work is embedded within an interdisciplinary field program, including biogeochemical modelers and remote sensing scientists, these data will feed directly into new models of the biological pump, improving our ability to quantify and predict carbon uptake by the ocean. This project will train 1 graduate student and at least 2 undergraduate researchers. Findings will be communicated to the non-scientific public through blogs, videos, and the public communication channels of participating institutions.</p>
<p>Accurate prediction of the global carbon cycle requires an understanding of the specific processes that link surface plankton communities and sinking particulate carbon flux (export) out of the surface ocean, but current methodological paradigms in biological pump research do not directly observe these processes. This project will comprehensively determine who is exported from the surface ocean and how using new, particle-resolving optical and molecular techniques embedded within a sampling scheme that characterizes export events at high time and space resolution. The investigation suggests that different plankton types in the surface waters are transported out of the surface ocean by distinct export pathways, and that an understanding of these connections is critical knowledge for global carbon cycle modeling. If successful, this work has the potential to transform our conceptual understanding of the biological pump by directly identifying mechanisms that link surface plankton with particle export, without relying on bulk sampling schemes and large-scale correlation analysis. Particle export environments will be studied at five open ocean locations during a cruise from Hawaii to Seattle in January-February 2017. The surface plankton communities will be characterized by a combination of satellite observations, sensors attached to a free-drifting, continuously profiling WireWalker, an in situ holographic camera, microscopy, and by sequencing 18S and 16S rRNA gene fragments. Exported particles will simultaneously be captured by various specialized sediment traps and their characteristics will be directly related to their sources in the surface community by identifying the genetic contents of individual particle types. Individual particles will be isolated from gel layers and the 16S and 18S rRNA gene fragments will be amplified and sequenced. This work would, for the first time, combine molecular approaches with particle-specific observations to enable simultaneous identification of both which organisms are exported and the processes responsible for their export.</p>
EAGER DNA BioPump
largerWorkCitation
project
eng; USA
oceans
North Pacific Ocean
-151.779
-70.8119
21.52
39.94
2016-06-13
2017-11-07
Eastern Pacific
0
BCO-DMO catalogue of parameters from Particle fluxes calculated from gel trap images taken on R/V Endeavor and R/V Falkor cruises off the New England shelf break and in the North Pacific during 2016-2017
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact
http://lod.bco-dmo.org/id/dataset-parameter/848475.rdf
Name: orig_file_name
Units: unitless
Description: <p>original file name</p>
http://lod.bco-dmo.org/id/dataset-parameter/848476.rdf
Name: trap
Units: unitless
Description: <p>trap identification</p>
http://lod.bco-dmo.org/id/dataset-parameter/848477.rdf
Name: cruise_id
Units: name
Description: <p>Name of the cruise that the sample was collected</p>
http://lod.bco-dmo.org/id/dataset-parameter/848478.rdf
Name: depth_meters
Units: meters
Description: <p>Depth of sample collection</p>
http://lod.bco-dmo.org/id/dataset-parameter/848479.rdf
Name: trap_platform
Units: name
Description: <p>Type of sediment trap platform and numerical identifier</p>
http://lod.bco-dmo.org/id/dataset-parameter/848480.rdf
Name: deployment_duration
Units: days
Description: <p>Elapsed time over which particles were collected</p>
http://lod.bco-dmo.org/id/dataset-parameter/848481.rdf
Name: bin_mids
Units: micrometers
Description: <p>middle of size bin</p>
http://lod.bco-dmo.org/id/dataset-parameter/848482.rdf
Name: bin_width
Units: micrometers
Description: <p>width of the size bin</p>
http://lod.bco-dmo.org/id/dataset-parameter/848483.rdf
Name: flux
Units: number per square meter per day (# m^-2 d^-1)
Description: <p>number flux of all passively sinking particles particles</p>
http://lod.bco-dmo.org/id/dataset-parameter/848484.rdf
Name: flux_uncertainty
Units: number per square meter per day (# m^-2 d^-1)
Description: <p>counting uncertainty of the number flux of all passively sinking particles</p>
http://lod.bco-dmo.org/id/dataset-parameter/848485.rdf
Name: number_counted
Units: scalar
Description: <p>Number of raw counts of passively sinking particles</p>
http://lod.bco-dmo.org/id/dataset-parameter/848486.rdf
Name: aggregate_flux
Units: number per square meter per day (# m^-2 d^-1)
Description: <p>number flux of aggregates</p>
http://lod.bco-dmo.org/id/dataset-parameter/848487.rdf
Name: aggregate_flux_uncertainty
Units: number per square meter per day (# m^-2 d^-1)
Description: <p>counting uncertainty of the number flux of aggregates</p>
http://lod.bco-dmo.org/id/dataset-parameter/848488.rdf
Name: aggregate_number_counted
Units: scalar
Description: <p>Number of raw counts of aggregates</p>
http://lod.bco-dmo.org/id/dataset-parameter/848489.rdf
Name: long_fp_flux
Units: number per square meter per day (# m^-2 d^-1)
Description: <p>number flux of long fecal pellets</p>
http://lod.bco-dmo.org/id/dataset-parameter/848490.rdf
Name: long_fp_flux_uncertainty
Units: number per square meter per day (# m^-2 d^-1)
Description: <p>counting uncertainty of the number flux of long fecal pellets</p>
http://lod.bco-dmo.org/id/dataset-parameter/848491.rdf
Name: long_fp_number_counted
Units: scalar
Description: <p>Number of raw counts of long fecal pellets</p>
http://lod.bco-dmo.org/id/dataset-parameter/848492.rdf
Name: dense_detritus_flux
Units: number per square meter per day (# m^-2 d^-1)
Description: <p>number flux of dense detritus</p>
http://lod.bco-dmo.org/id/dataset-parameter/848493.rdf
Name: dense_detritus_flux_uncertainty
Units: number per square meter per day (# m^-2 d^-1)
Description: <p>counting uncertainty of the number flux of dense detritus</p>
http://lod.bco-dmo.org/id/dataset-parameter/848494.rdf
Name: dense_detritus_number_counted
Units: scalar
Description: <p>Number of raw counts of dense detritus</p>
http://lod.bco-dmo.org/id/dataset-parameter/848495.rdf
Name: large_loose_flux
Units: number per square meter per day (# m^-2 d^-1)
Description: <p>number flux of large-loose fecal pellets</p>
http://lod.bco-dmo.org/id/dataset-parameter/848496.rdf
Name: large_loose_flux_uncertainty
Units: number per square meter per day (# m^-2 d^-1)
Description: <p>counting uncertainty of the number flux of large-loose fecal pellets</p>
http://lod.bco-dmo.org/id/dataset-parameter/848497.rdf
Name: large_loose_number_counted
Units: scalar
Description: <p>Number of raw counts of large-loose fecal pellets</p>
http://lod.bco-dmo.org/id/dataset-parameter/848498.rdf
Name: short_fp_flux
Units: number per square meter per day (# m^-2 d^-1)
Description: <p>number flux of short fecal pellets</p>
http://lod.bco-dmo.org/id/dataset-parameter/848499.rdf
Name: short_fp_flux_uncertainty
Units: number per square meter per day (# m^-2 d^-1)
Description: <p>counting uncertainty of the number flux of short fecal pellets</p>
http://lod.bco-dmo.org/id/dataset-parameter/848500.rdf
Name: short_fp_number_counted
Units: scalar
Description: <p>Number of raw counts of short fecal pellets</p>
http://lod.bco-dmo.org/id/dataset-parameter/848501.rdf
Name: mini_pellet_flux
Units: number per square meter per day (# m^-2 d^-1)
Description: <p>number flux of mini pellets</p>
http://lod.bco-dmo.org/id/dataset-parameter/848502.rdf
Name: mini_pellet_flux_uncertainty
Units: number per square meter per day (# m^-2 d^-1)
Description: <p>counting uncertainty of the number flux of mini pellets</p>
http://lod.bco-dmo.org/id/dataset-parameter/848503.rdf
Name: mini_pellet_number_counted
Units: scalar
Description: <p>Number of raw counts of mini pellets</p>
http://lod.bco-dmo.org/id/dataset-parameter/848504.rdf
Name: salp_pellet_flux
Units: number per square meter per day (# m^-2 d^-1)
Description: <p>number flux of salp fecal pellets</p>
http://lod.bco-dmo.org/id/dataset-parameter/848505.rdf
Name: salp_pellet_flux_uncertainty
Units: number per square meter per day (# m^-2 d^-1)
Description: <p>counting uncertainty of the number flux of salp fecal pellets</p>
http://lod.bco-dmo.org/id/dataset-parameter/848506.rdf
Name: salp_pellet_number_counted
Units: scalar
Description: <p>Number of raw counts of salp fecal pellets</p>
http://lod.bco-dmo.org/id/dataset-parameter/848507.rdf
Name: phyto_flux
Units: number per square meter per day (# m^-2 d^-1)
Description: <p>number flux of phytoplankton cells</p>
http://lod.bco-dmo.org/id/dataset-parameter/848508.rdf
Name: phyto_flux_uncertainty
Units: number per square meter per day (# m^-2 d^-1)
Description: <p>counting uncertainty of the number flux of phytoplankton cells</p>
http://lod.bco-dmo.org/id/dataset-parameter/848509.rdf
Name: phyto_number_counted
Units: scalar
Description: <p>Number of raw counts of phytoplankton cells</p>
http://lod.bco-dmo.org/id/dataset-parameter/848510.rdf
Name: foraminifera_flux
Units: number per square meter per day (# m^-2 d^-1)
Description: <p>number flux of foraminifera</p>
http://lod.bco-dmo.org/id/dataset-parameter/848511.rdf
Name: foraminifera_flux_uncertainty
Units: number per square meter per day (# m^-2 d^-1)
Description: <p>counting uncertainty of the number flux of foraminifera</p>
http://lod.bco-dmo.org/id/dataset-parameter/848512.rdf
Name: foraminifera_number_counted
Units: scalar
Description: <p>Number of raw counts of foraminifera</p>
http://lod.bco-dmo.org/id/dataset-parameter/848513.rdf
Name: rhizaria_flux
Units: number per square meter per day (# m^-2 d^-1)
Description: <p>number flux of rhizaria</p>
http://lod.bco-dmo.org/id/dataset-parameter/848514.rdf
Name: rhizaria_flux_uncertainty
Units: number per square meter per day (# m^-2 d^-1)
Description: <p>counting uncertainty of the number flux of rhizaria</p>
http://lod.bco-dmo.org/id/dataset-parameter/848515.rdf
Name: rhizaria_number_counted
Units: scalar
Description: <p>Number of raw counts of rhizaria</p>
http://lod.bco-dmo.org/id/dataset-parameter/848516.rdf
Name: fiber_flux
Units: number per square meter per day (# m^-2 d^-1)
Description: <p>number flux of fibers</p>
http://lod.bco-dmo.org/id/dataset-parameter/848517.rdf
Name: fiber_flux_uncertainty
Units: number per square meter per day (# m^-2 d^-1)
Description: <p>counting uncertainty of the number flux of fibers</p>
http://lod.bco-dmo.org/id/dataset-parameter/848518.rdf
Name: fiber_number_counted
Units: scalar
Description: <p>Number of raw counts of fibers</p>
http://lod.bco-dmo.org/id/dataset-parameter/848519.rdf
Name: copepod_flux
Units: number per square meter per day (# m^-2 d^-1)
Description: <p>number flux of copepods</p>
http://lod.bco-dmo.org/id/dataset-parameter/848520.rdf
Name: copepod_flux_uncertainty
Units: number per square meter per day (# m^-2 d^-1)
Description: <p>counting uncertainty of the number flux of copepods</p>
http://lod.bco-dmo.org/id/dataset-parameter/848521.rdf
Name: copepod_number_counted
Units: scalar
Description: <p>Number of raw counts of copepods</p>
http://lod.bco-dmo.org/id/dataset-parameter/848522.rdf
Name: pteropod_flux
Units: number per square meter per day (# m^-2 d^-1)
Description: <p>number flux of pteropods</p>
http://lod.bco-dmo.org/id/dataset-parameter/848523.rdf
Name: pteropod_flux_uncertainty
Units: number per square meter per day (# m^-2 d^-1)
Description: <p>counting uncertainty of the number flux of pteropods</p>
http://lod.bco-dmo.org/id/dataset-parameter/848524.rdf
Name: pteropod_number_counted
Units: scalar
Description: <p>Number of raw counts of pteropods</p>
http://lod.bco-dmo.org/id/dataset-parameter/848525.rdf
Name: amphipod_flux
Units: number per square meter per day (# m^-2 d^-1)
Description: <p>number flux of amphipods</p>
http://lod.bco-dmo.org/id/dataset-parameter/848526.rdf
Name: amphipod_flux_uncertainty
Units: number per square meter per day (# m^-2 d^-1)
Description: <p>counting uncertainty of the number flux of amphipods</p>
http://lod.bco-dmo.org/id/dataset-parameter/848527.rdf
Name: amphipod_number_counted
Units: scalar
Description: <p>Number of raw counts of amphipods</p>
http://lod.bco-dmo.org/id/dataset-parameter/848528.rdf
Name: other_zooplankton_flux
Units: number per square meter per day (# m^-2 d^-1)
Description: <p>number flux of other zooplankton</p>
http://lod.bco-dmo.org/id/dataset-parameter/848529.rdf
Name: other_zooplankton_flux_uncertainty
Units: number per square meter per day (# m^-2 d^-1)
Description: <p>counting uncertainty of the number flux of other zooplankton</p>
http://lod.bco-dmo.org/id/dataset-parameter/848530.rdf
Name: other_zooplankton_number_counted
Units: scalar
Description: <p>Number of raw counts of other zooplankton</p>
http://lod.bco-dmo.org/id/dataset-parameter/848531.rdf
Name: zooplankton_part_flux
Units: number per square meter per day (# m^-2 d^-1)
Description: <p>number flux of zooplankton body parts</p>
http://lod.bco-dmo.org/id/dataset-parameter/848532.rdf
Name: zooplankton_part_flux_uncertainty
Units: number per square meter per day (# m^-2 d^-1)
Description: <p>counting uncertainty of the number flux of zooplankton body parts</p>
http://lod.bco-dmo.org/id/dataset-parameter/848533.rdf
Name: zooplankton_part_number_counted
Units: scalar
Description: <p>Number of raw counts of zooplankton body parts</p>
http://lod.bco-dmo.org/id/dataset-parameter/848534.rdf
Name: unidentifiable_flux
Units: number per square meter per day (# m^-2 d^-1)
Description: <p>number flux of unidentifiable particles or imagine noise</p>
http://lod.bco-dmo.org/id/dataset-parameter/848535.rdf
Name: unidentifiable_flux_uncertainty
Units: number per square meter per day (# m^-2 d^-1)
Description: <p>counting uncertainty of the number flux of unidentifiable particles or imagine noise</p>
http://lod.bco-dmo.org/id/dataset-parameter/848536.rdf
Name: unidentifiable_number_counted
Units: scalar
Description: <p>Number of raw counts of unidentifiable particles or imagine noise</p>
http://lod.bco-dmo.org/id/dataset-parameter/848537.rdf
Name: long_fp_Cflux
Units: millimole of carbon per square meter per day (mmol C m^-2 d^-1)
Description: <p>modeled carbon flux by long fecal pellets</p>
http://lod.bco-dmo.org/id/dataset-parameter/848538.rdf
Name: short_fp_Cflux
Units: millimole of carbon per square meter per day (mmol C m^-2 d^-1)
Description: <p>modeled carbon flux by short fecal pellets</p>
http://lod.bco-dmo.org/id/dataset-parameter/848539.rdf
Name: salp_fp_Cflux
Units: millimole of carbon per square meter per day (mmol C m^-2 d^-1)
Description: <p>modeled carbon flux by salp fecal pellets</p>
http://lod.bco-dmo.org/id/dataset-parameter/848540.rdf
Name: mini_fp_Cflux
Units: millimole of carbon per square meter per day (mmol C m^-2 d^-1)
Description: <p>modeled carbon flux by mini pellets</p>
http://lod.bco-dmo.org/id/dataset-parameter/848541.rdf
Name: phytoplankton_Cflux
Units: millimole of carbon per square meter per day (mmol C m^-2 d^-1)
Description: <p>modeled carbon flux by phytoplankton cells</p>
http://lod.bco-dmo.org/id/dataset-parameter/848542.rdf
Name: rhizaria_Cflux
Units: millimole of carbon per square meter per day (mmol C m^-2 d^-1)
Description: <p>modeled carbon flux by rhizaria cells</p>
http://lod.bco-dmo.org/id/dataset-parameter/848543.rdf
Name: agg_Cflux
Units: millimole of carbon per square meter per day (mmol C m^-2 d^-1)
Description: <p>modeled carbon flux by aggregates</p>
http://lod.bco-dmo.org/id/dataset-parameter/848544.rdf
Name: dense_Cflux
Units: millimole of carbon per square meter per day (mmol C m^-2 d^-1)
Description: <p>modeled carbon flux by dense detritus</p>
http://lod.bco-dmo.org/id/dataset-parameter/848545.rdf
Name: large_fp_Cflux
Units: millimole of carbon per square meter per day (mmol C m^-2 d^-1)
Description: <p>modeled carbon flux by large-loose fecal pellets</p>
http://lod.bco-dmo.org/id/dataset-parameter/848546.rdf
Name: long_fp_Cflux_uncertainty
Units: millimole of carbon per square meter per day (mmol C m^-2 d^-1)
Description: <p>uncertainty of modeled carbon flux by long fecal pellets</p>
http://lod.bco-dmo.org/id/dataset-parameter/848547.rdf
Name: short_fp_Cflux_uncertainty
Units: millimole of carbon per square meter per day (mmol C m^-2 d^-1)
Description: <p>uncertainty of modeled carbon flux by short fecal pellets</p>
http://lod.bco-dmo.org/id/dataset-parameter/848548.rdf
Name: salp_fp_Cflux_uncertainty
Units: millimole of carbon per square meter per day (mmol C m^-2 d^-1)
Description: <p>uncertainty of modeled carbon flux by salp fecal pellets</p>
http://lod.bco-dmo.org/id/dataset-parameter/848549.rdf
Name: mini_fp_Cflux_uncertainty
Units: millimole of carbon per square meter per day (mmol C m^-2 d^-1)
Description: <p>uncertainty of modeled carbon flux by mini pellets</p>
http://lod.bco-dmo.org/id/dataset-parameter/848550.rdf
Name: phytoplankton_Cflux_uncertainty
Units: millimole of carbon per square meter per day (mmol C m^-2 d^-1)
Description: <p>uncertainty of modeled carbon flux by phytoplankton cells</p>
http://lod.bco-dmo.org/id/dataset-parameter/848551.rdf
Name: rhizaria_Cflux_uncertainty
Units: millimole of carbon per square meter per day (mmol C m^-2 d^-1)
Description: <p>uncertainty of modeled carbon flux by rhizaria cells</p>
http://lod.bco-dmo.org/id/dataset-parameter/848552.rdf
Name: agg_Cflux_uncertainty
Units: millimole of carbon per square meter per day (mmol C m^-2 d^-1)
Description: <p>uncertainty of modeled carbon flux by aggregates</p>
http://lod.bco-dmo.org/id/dataset-parameter/848553.rdf
Name: dense_Cflux_uncertainty
Units: millimole of carbon per square meter per day (mmol C m^-2 d^-1)
Description: <p>uncertainty of modeled carbon flux by dense detritus</p>
http://lod.bco-dmo.org/id/dataset-parameter/848554.rdf
Name: large_fp_Cflux_uncertainty
Units: millimole of carbon per square meter per day (mmol C m^-2 d^-1)
Description: <p>uncertainty of modeled carbon flux by large-loose fecal pellets</p>
http://lod.bco-dmo.org/id/dataset-parameter/848555.rdf
Name: long_fp_Vflux
Units: cubic millimeters per square meter per day (mm^3 m^-2 d^-1)
Description: <p>modeled volume flux by long fecal pellets</p>
http://lod.bco-dmo.org/id/dataset-parameter/848556.rdf
Name: short_fp_Vflux
Units: cubic millimeters per square meter per day (mm^3 m^-2 d^-1)
Description: <p>modeled volume flux by short fecal pellets</p>
http://lod.bco-dmo.org/id/dataset-parameter/848557.rdf
Name: salp_fp_Vflux
Units: cubic millimeters per square meter per day (mm^3 m^-2 d^-1)
Description: <p>modeled volume flux by salp fecal pellets</p>
http://lod.bco-dmo.org/id/dataset-parameter/848558.rdf
Name: mini_fp_Vflux
Units: cubic millimeters per square meter per day (mm^3 m^-2 d^-1)
Description: <p>modeled volume flux by mini pellets</p>
http://lod.bco-dmo.org/id/dataset-parameter/848559.rdf
Name: phytoplankton_Vflux
Units: cubic millimeters per square meter per day (mm^3 m^-2 d^-1)
Description: <p>modeled volume flux by phytoplankton cells</p>
http://lod.bco-dmo.org/id/dataset-parameter/848560.rdf
Name: rhizaria_Vflux
Units: cubic millimeters per square meter per day (mm^3 m^-2 d^-1)
Description: <p>modeled volume flux by rhizaria cells</p>
http://lod.bco-dmo.org/id/dataset-parameter/848561.rdf
Name: agg_Vflux
Units: cubic millimeters per square meter per day (mm^3 m^-2 d^-1)
Description: <p>modeled volume flux by aggregates</p>
http://lod.bco-dmo.org/id/dataset-parameter/848562.rdf
Name: dense_Vflux
Units: cubic millimeters per square meter per day (mm^3 m^-2 d^-1)
Description: <p>modeled volume flux by dense detritus</p>
http://lod.bco-dmo.org/id/dataset-parameter/848563.rdf
Name: large_fp_Vflux
Units: cubic millimeters per square meter per day (mm^3 m^-2 d^-1)
Description: <p>modeled volume flux by large-loose fecal pellets</p>
GB/NERC/BODC > British Oceanographic Data Centre, Natural Environment Research Council, United Kingdom
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact
277961
https://darchive.mblwhoilibrary.org/bitstream/1912/26923/1/dataset-847036_particle-flux__v1.tsv
download
https://doi.org/10.26008/1912/bco-dmo.847036.1
download
onLine
dataset
<p><strong>Image Acquisition</strong>:<br />
For more information on sediment trap deployment and image acquisition, see the related dataset "Geltrap micrographs" (<a href="https://www.bco-dmo.org/dataset/749412" target="_blank">https://www.bco-dmo.org/dataset/749412</a>). In brief, sediment trap collector tubes were deployed on various platform designs, including a neutrally-buoyant sediment trap (NBST), a surface tethered sediment trap (STST), and a Wire Walker (WW) trap. Trap tubes were filled with filtered water overlying a jar containing a polyacrylamide gel layer (Durkin et al. 2015). Upon recovery, collection tubes were allowed to settle for at least 1 hour before the overlying water was siphoned off. Jars containing polyacrylamide gel were removed from trap tubes and the remaining overlying water was carefully pipetted off the gel. Gels were stored at 4 degrees C and imaged within the following 2 days before being stored at -80 degrees C.</p>
<p>Polyacrylamide gel layers were imaged on a dissecting microscope (Olympus SZX16) with either a Luminera Infinity 2 (FK170124) or an Allied Vision Technologies StingRay (EN572 and EN581) camera attachment. Particles collected in gel layers during EN572 and EN581 were imaged under brightfield illumination. Particles collected in gel layers during FK170124 were imaged under both brightfield and oblique illumination, producing two separate sets of images for each sample. EN572 gel layers were imaged with a transparent grid to assist in tracking gel location during imaging. The grid was not used when imaging samples collected during subsequent cruises because the pronounced grid lines complicated image analysis. All gel layers were imaged at 4 increasing magnifications, though the combination of magnifications varied by cruise. To determine whether measured particle properties changed if gel layers are frozen, samples collected during FK170124 were thawed after being stored for approximately 1 year at -80 degrees C and imaged again under both brightfield and oblique illumination</p>
<p><strong>Determination of Particle Flux:</strong><br />
Particles in gel images were quantified with an image processing protocol created using functions available in python’s Sci-Kit Image. Particles present in each micrograph were detected through a series of image transformation steps that maximize the detection of entire particle areas while minimizing the detection of imaging noise. The background was removed, a brightness threshold was applied, and an edge-detection kernel transformation was used to identify the in-focus particles. Duplicate particles detected in multiple focal planes were removed and the remaining particles were counted and measured.<br />
<br />
Particles were categorized into 9 different sinking particle classes. Identities were assigned by manually identifying particle images. Aggregates were defined as loosely packed detritus with irregular edges. Dense detritus was defined as densely packed amorphous material, often brown or golden in color. Large, loose pellets were similar to dense detritus but were also elongated like a fecal pellet. Long fecal pellets were defined as long, thin, cylindrical fecal pellets with a smooth edge, such as the chitin-encased pellets produced by euphausiids. Short fecal pellets were also smooth-edged pellets but with an oval or ellipsoid shape, such as those produced by larvaceans. Mini pellets were defined as small (usually &lt;100 micrometer ESD), spheres such as those produced by rhizarians and microzooplankton (Gowing &amp; Silver, 1985). A small number of individual organisms considered to be passively sinking were also detected, including Rhizarians, primarily Phaeodaria, and various phytoplankton, usually diatoms. Pteropods, copepods, amphipods, foraminifera, and other zooplankton that probably swam into the gel and human-produced fibers were also detected but not considered passive flux and not included in the categories of sinking particles. Unidentifiable objects were also detected and were likely caused by out-of-focus particles, shadows, smudges, or noise detected by the image processing steps that are sensitive to the particular thresholds used.</p>
<p>Only identifiable, sinking particle classes from the dataset were considered in calculations of sinking flux. For each imaging magnification, particles were grouped by their equivalent spherical diameter (ESD) into logarithmically-scaled size bins. To calculate number fluxes at each magnification, the number of particles counted in each size bin was divided by the total imaged surface area of the gel and the trap collection time. Uncertainty of the number flux was estimated by applying these same calculations to the counting uncertainty (square root of the number of particles counted, ie. Poisson distribution).</p>
<p>The carbon flux by each particle type was determined by modeling particle volumes, calculating the carbon per unit volume, and multiplying the carbon per particle by the measured particle number fluxes in each size category.</p>
Specified by the Principal Investigator(s)
<p>BCO-DMO Processing:<br />
- Adjusted field/parameter names to comply with BCO-DMO naming conventions;<br />
- Concatenated data from separate files into one dataset;<br />
- Rounded "_flux" and "_uncertainty" columns to 3 decimal places,<br />
- Added a conventional header with dataset name, PI names, version date.</p>
Specified by the Principal Investigator(s)
asNeeded
7.x-1.1
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact
Luminera Infinity 2 microscope camera
Luminera Infinity 2 microscope camera
PI Supplied Instrument Name: Luminera Infinity 2 microscope camera PI Supplied Instrument Description:Polyacrylamide gel layers were imaged on a dissecting microscope (Olympus SZX16) with either a Luminera Infinity 2 (FK170124) or an Allied Vision Technologies StingRay (EN572 and EN581) camera attachment. Instrument Name: Camera Instrument Short Name:camera Instrument Description: All types of photographic equipment including stills, video, film and digital systems. Community Standard Description: http://vocab.nerc.ac.uk/collection/L05/current/311/
Olympus SZX16 Stereomicroscope
Olympus SZX16 Stereomicroscope
PI Supplied Instrument Name: Olympus SZX16 Stereomicroscope PI Supplied Instrument Description:Polyacrylamide gel layers were imaged on a dissecting microscope (Olympus SZX16) Instrument Name: Microscope - Optical Instrument Short Name: Instrument Description: 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". Community Standard Description: http://vocab.nerc.ac.uk/collection/L05/current/LAB05/
PI Supplied Instrument Name: PI Supplied Instrument Description:Sediment trap collector tubes were deployed on various platform designs, including a neutrally-buoyant sediment trap (NBST), a surface tethered sediment trap (STST), and a Wire Walker (WW) trap. Instrument Name: Sediment Trap Instrument Short Name:Sediment Trap Instrument Description: 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. In general a sediment trap has a jar at the bottom to collect the sample and a broad funnel-shaped opening at the top with baffles to keep out very large objects and help prevent the funnel from clogging. This designation is used when the specific type of sediment trap was not specified by the contributing investigator. Community Standard Description: http://vocab.nerc.ac.uk/collection/L05/current/33/
Cruise: EN572
EN572
R/V Endeavor
Community Standard Description
International Council for the Exploration of the Sea
R/V Endeavor
vessel
EN572
Melissa Omand
University of Rhode Island
Cruise: EN581
EN581
R/V Endeavor
Community Standard Description
International Council for the Exploration of the Sea
R/V Endeavor
vessel
EN581
Susanne Menden-Deuer
University of Rhode Island
Cruise: FK170124
FK170124
R/V Falkor
Community Standard Description
International Council for the Exploration of the Sea
R/V Falkor
vessel
FK170124
Ivona Cetinic
National Aeronautics and Space Administration
https://datadocs.bco-dmo.org/docs/302/EAGER_DNA_BioPump/data_docs/DurkinOmandEstapa_Cruise_report.pdf
Report describing FK170124
R/V Endeavor
Community Standard Description
International Council for the Exploration of the Sea
R/V Endeavor
vessel
R/V Falkor
Community Standard Description
International Council for the Exploration of the Sea
R/V Falkor
vessel