http://lod.bco-dmo.org/id/dataset/856942
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
2021-08-02
ISO 19115-2 Geographic Information - Metadata - Part 2: Extensions for Imagery and Gridded Data
ISO 19115-2:2009(E)
Global reconstructions of particle biovolume, size distribution, and carbon export flux from the seasonal euphotic zone and maximum winter time mixed layer from particle profiles conducted during cruises from 2008 to 2020
2023-02-02
publication
2023-02-02
revision
Marine Biological Laboratory/Woods Hole Oceanographic Institution Library (MBLWHOI DLA)
2021-11-17
publication
https://doi.org/10.26008/1912/bco-dmo.856942.1
Daniele Bianchi
University of California-Los Angeles
principalInvestigator
Daniel Clements
University of California-Los Angeles
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: Bianchi, D., Clements, D. (2023) Global reconstructions of particle biovolume, size distribution, and carbon export flux from the seasonal euphotic zone and maximum winter time mixed layer from particle profiles conducted during cruises from 2008 to 2020. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 2) Version Date 2023-02-02 [if applicable, indicate subset used]. doi:10.26008/1912/bco-dmo.856942.2 [access date]
Methods and Sampling: <p><strong>Methodology:</strong></p>
<p>This work is based on the compilation of over 6800 profiles of particulate matter observations from Underwater Vision Profilers (UVP5) (Rainer, 2021).&nbsp;The biovolume of the particle size distribution is calculated as the equivalent spherical volume of the particle size distribution &nbsp;(PSD), by summing the product of particle counts time particle volume in each size class. The slope of the PSD is calculated assuming a power law distribution for the particle abundance, by linear least square fit of the log of particle counts vs. the log of particle size. These quantities are estimated from two different depth horizons, the mixed layer depth (MLD_Export.nc) and the euphotic zone depth (Euphotic_Export.nc). To convert sparse observations to a global climatology, we trained 100 ensembles of regressions trees (Random Forests, RF) to predict biovolume and slope based on their relationship to well-sampled physical and biogeochemical predictors.</p>
<p>We calculate the particle sinking speed and carbon content by combining PSD reconstruction (biovolume and slope) with an empirical relationship between particle size, carbon content and sinking speed, the parameters of which are optimized to match in situ particle flux observations (Bisson et al. 2018). The flux values are calculated as the sum of the PSD time the sinking carbon parameters, for each grid cell. The error for reconstructed quantities is given by the standard deviation of 100 independent realizations of the RF reconstructions.</p>
<p><strong>Sampling and analytical procedures:&nbsp;</strong><br />
<br />
This dataset contains a compilation of data from multiple sources. &nbsp;A list of all datasets and the associated information, including cruise name, is included.</p>
<p>Observations of Particle size and biovolume are made via the UVP5 camera, which is lowered in the water column on a CTD rosette. Images are captured at up to 30 images per second while the instrument is lowered at 1m/s. Images are analyzed and the pixel size of each particle is translated into a particle size, and the abundance calculated, following the method described by Picheral et al. (2010).
<br />
<br />
The data is compiled from multiple sources published and unpublished, and was accessed from EcoPart, the particle module of EcoTaxa&nbsp;https://ecotaxa.obs-vlfr.fr/part/ (Picheral et al., 2017).<br />
<br />
<strong>Instruments</strong>:&nbsp;</p>
<p>Observations of particle abundance and biovolume were made with the Underwater Vision Profiler, version 5 (UVP5).</p>
Funding provided by NSF Division of Ocean Sciences (NSF OCE) Award Number: OCE-1635632 Award URL: https://www.nsf.gov/awardsearch/show-award?AWD_ID=1635632
completed
Daniele Bianchi
University of California-Los Angeles
310-825-6936
UCLA Atmospheric & Oceanic Sciences Box 951565
Los Angeles
CA
90095
USA
dbianchi@atmos.ucla.edu
pointOfContact
Daniel Clements
University of California-Los Angeles
dclements@bigelow.org
pointOfContact
asNeeded
Dataset Version: 2
Unknown
nderwater Vision Profiler, version 5 (UVP5)
theme
None, User defined
Underwater Vision Profiler 5
instrument
BCO-DMO Standard Instruments
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: Understanding the distribution and biogeochemical role of anaerobic microenvironments in the ocean
https://osprey.bco-dmo.org/project/846645
Collaborative Research: Understanding the distribution and biogeochemical role of anaerobic microenvironments in the ocean
<p><em>NSF Award Abstract:</em><br />
Until recently, organic matter decomposition (respiration) was thought to occur primarily in oxygenated seawater; however, evidence has surfaced that respiration can occur under low oxygen conditions (anaerobic) similar to those found within microenvironments of suspended particles. As such, the possibility exists that these anaerobic reactions are more widespread than previously thought and could play a significant role in the cycling of sulfur, nitrogen, and some trace metals. Researchers from the University of California-Los Angeles and the University of Washington plan to study these reactions by developing a particle-redox model to simulate the biogeochemistry of anaerobic microenvironments and make predictions which can be tested against available ocean data (GEOTRACES program). The study is intended to understand the conditions needed to cycle nitrogen and sulfur in these particle microenvironments, the scavenging of trace metals during sulfide precipitations, and develop a tracer for particle bound denitrification (removal of nitrogen by microbes). This project will be the first funding support for two tenure-track faculty who are dedicated to education and public outreach to help broaden involvement in ocean sciences. One of the investigators will be involved as a youth educator in the "Students on Ice" program which conducts workshops that allows youth to gain experience at sea learning about oceanography, whereas the other would organize a series of workshops to engage students from the Rochester City School District in science.</p>
<p>This project seeks to investigate the evidence that has been coming out in recent years that anaerobic microenvironments within organic particles are widespread throughout the ocean and are a significant contributor to denitrification and sulfur reduction rates in otherwise oxygenated waters. To do so, the researchers plan to develop a new modeling framework to simulate the biogeochemistry of anaerobic microenvironments and make predictions which can be tested against available observations such as those from the GEOTRACES program. Overall the objectives of this research are to (1) understand the water column conditions and particle properties that lead to these anaerobic microenvironments, (2) test whether sulfate reduction rates are consistent with the metal precipitation signatures known for low oxygen water, and (3) predict the geochemical signature of particle bound denitrification and determine its rate from the large-scale distribution of nitrogen tracers. Understanding the anaerobic processes taking place within anaerobic microenvironments of organic particles in the water column is likely to update the biogeochemical cycles of nitrogen, sulfur, and trace metals.</p>
Ocean Particles and Microenvironments
largerWorkCitation
project
eng; USA
oceans
-180
180
-90
90
2008-01-01
2020-01-01
0
BCO-DMO catalogue of parameters from Global reconstructions of particle biovolume, size distribution, and carbon export flux from the seasonal euphotic zone and maximum winter time mixed layer from particle profiles conducted during cruises from 2008 to 2020
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
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
17076125
https://darchive.mblwhoilibrary.org/server/api/core/bitstreams/30071b04-acca-4dd5-bbca-e6b62d44c636/content
download
17896533
https://darchive.mblwhoilibrary.org/server/api/core/bitstreams/7d9f8837-3b3c-51f5-8c2a-23109921bb2d/content
download
https://doi.org/10.26008/1912/bco-dmo.856942.1
download
onLine
dataset
<p><strong>Methodology:</strong></p>
<p>This work is based on the compilation of over 6800 profiles of particulate matter observations from Underwater Vision Profilers (UVP5) (Rainer, 2021).&nbsp;The biovolume of the particle size distribution is calculated as the equivalent spherical volume of the particle size distribution &nbsp;(PSD), by summing the product of particle counts time particle volume in each size class. The slope of the PSD is calculated assuming a power law distribution for the particle abundance, by linear least square fit of the log of particle counts vs. the log of particle size. These quantities are estimated from two different depth horizons, the mixed layer depth (MLD_Export.nc) and the euphotic zone depth (Euphotic_Export.nc). To convert sparse observations to a global climatology, we trained 100 ensembles of regressions trees (Random Forests, RF) to predict biovolume and slope based on their relationship to well-sampled physical and biogeochemical predictors.</p>
<p>We calculate the particle sinking speed and carbon content by combining PSD reconstruction (biovolume and slope) with an empirical relationship between particle size, carbon content and sinking speed, the parameters of which are optimized to match in situ particle flux observations (Bisson et al. 2018). The flux values are calculated as the sum of the PSD time the sinking carbon parameters, for each grid cell. The error for reconstructed quantities is given by the standard deviation of 100 independent realizations of the RF reconstructions.</p>
<p><strong>Sampling and analytical procedures:&nbsp;</strong><br />
<br />
This dataset contains a compilation of data from multiple sources. &nbsp;A list of all datasets and the associated information, including cruise name, is included.</p>
<p>Observations of Particle size and biovolume are made via the UVP5 camera, which is lowered in the water column on a CTD rosette. Images are captured at up to 30 images per second while the instrument is lowered at 1m/s. Images are analyzed and the pixel size of each particle is translated into a particle size, and the abundance calculated, following the method described by Picheral et al. (2010).
<br />
<br />
The data is compiled from multiple sources published and unpublished, and was accessed from EcoPart, the particle module of EcoTaxa&nbsp;https://ecotaxa.obs-vlfr.fr/part/ (Picheral et al., 2017).<br />
<br />
<strong>Instruments</strong>:&nbsp;</p>
<p>Observations of particle abundance and biovolume were made with the Underwater Vision Profiler, version 5 (UVP5).</p>
Specified by the Principal Investigator(s)
<p>BCO-DMO Data Manager Processing Notes:<br />
* Version 2 added to replace Version 1 on 2023-02-02.&nbsp;&nbsp;&nbsp;The .nc files were changed after modifying the calculation of&nbsp;particle Flux from PSD, &nbsp;thus updated the flux fields to reflect the more robust estimates. Specifically, a Monte Carlo approach was used with injected randomness to robustly optimize the results.</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
nderwater Vision Profiler, version 5 (UVP5)
nderwater Vision Profiler, version 5 (UVP5)
PI Supplied Instrument Name: nderwater Vision Profiler, version 5 (UVP5) PI Supplied Instrument Description:Observations of particle abundance and biovolume were made with the Underwater Vision Profiler, version 5 (UVP5). Instrument Name: Underwater Vision Profiler 5 Instrument Short Name:UVP5 Instrument Description: A description of the UVP5 instrument can be found in the following publication: Picheral, M., L. Guidi, L. Stemmann, D. M. Karl, G. Iddaoud, and G. Gorsky. 2010. The Underwater Vision Profiler 5: An advanced instrument for high spatial resolution studies of particle size spectra and zooplankton. Limnol. Oceanogr. Meth. 8: 462-473. (doi: 10.4319/lom.2010.8.462)