http://lod.bco-dmo.org/id/dataset/768011
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
2019-05-15
ISO 19115-2 Geographic Information - Metadata - Part 2: Extensions for Imagery and Gridded Data
ISO 19115-2:2009(E)
Microstructure profiles at Station AT55 in Lake Michigan from 2017, 2018 and 2019.
2021-08-17
publication
2021-08-17
revision
Marine Biological Laboratory/Woods Hole Oceanographic Institution Library (MBLWHOI DLA)
2019-05-20
publication
https://doi.org/10.1575/1912/bco-dmo.768011.1
Cary Troy
Purdue University
principalInvestigator
Harvey Bootsma
University of Wisconsin
principalInvestigator
David Cannon
Purdue University
principalInvestigator
Qian Liao
University of Wisconsin
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: Cannon, D., Troy, C., Bootsma, H., Liao, Q. (2021) Microstructure profiles at Station AT55 in Lake Michigan from 2017, 2018 and 2019. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 2) Version Date 2021-08-17 [if applicable, indicate subset used]. doi:10.26008/1912/bco-dmo.768011.2 [access date]
MCTD Lake Michigan 2017/2018/2019 Dataset Description: <p>Turbulent microstructure profiles were collected near Milwaukee, WI, during 2017 (August 1 - August 16), 2018 (April 5 – April 20), and 2019 (May 13 - May 14) at a 55m depth site. Microstructure measurements were collected using an RSI MicroCTD (Rockland Scientific International, Inc.), which measures velocity shear, temperature, turbidity, and chlorophyll concentrations. High resolution velocity shear (512 Hz) measurements were used to estimate turbulent kinetic energy dissipation throughout the water column. Microstructure profiles were collected during fair weather conditions on each day of sampling.</p> Methods and Sampling: <div>Microstructure profiles were taken over 3 years:</div>
<ul>
<li>2017: 176 microstructure profiles were collected over six days (August 1<sup>st</sup>, 2<sup>nd</sup>, 9<sup>th</sup>, 10<sup>th</sup>, 15<sup>th</sup>, and 16<sup>th</sup>).<em> </em></li>
<li>2018: 129 microstructure profiles were collected over three days (April 5th, 12th, and 20th).</li>
<li>2019: 78 microstructure profiles were collected over three days (May 13<sup>th</sup> and 14<sup>th</sup>).</li>
</ul>
<p>Measurements were collected using an RSI MicroCTD (Rockland Scientific International, Inc.) which sampled shear and temperature microstructure at 512Hz, free-falling at a velocity of 0.8 m/s (vertical resolution: ~1.5mm). Shear microstructure was analyzed to obtain turbulent kinetic energy dissipation (see data processing). Velocity shear was measured using two velocity shear probes (RSI; accuracy: 5%) oriented perpendicularly to collect orthogonal shear components. Microstructure temperatures were collected using 2 FP07 probes (accuracy: 0.005 <img src="///C:/Users/ksoenen/AppData/Local/Packages/oice_16_974fa576_32c1d314_2eb2/AC/Temp/msohtmlclip1/01/clip_image002.png" />), with the resulting measurements averaged to produce the single temperature estimate included in the attached files. Turbidity (accuracy: 2%) and fluorescence (accuracy: 1%) measurements were collected using a JAC-CLTU sensor (JFE Advantech Co., Ltd).&nbsp;&nbsp;</p>
<p>Microstructure profiles were collected manually by letting the instrument free fall through the water column. Profiles were timed and manually stopped to prevent the instrument from crashing into the bed and damaging sensors.</p>
Funding provided by NSF Division of Ocean Sciences (NSF OCE) Award Number: OCE-1658390 Award URL: https://www.nsf.gov/awardsearch/show-award?AWD_ID=1658390
completed
Cary Troy
Purdue University
765-494-3844
Lyles School of Civil Engineering
West Lafayette
IN
47907
USA
troy@purdue.edu
pointOfContact
Harvey Bootsma
University of Wisconsin
414-251-9231
School of Freshwater Sciences 600 E. Greenfield Ave.
Milwaukee
WI
53204
USA
hbootsma@uwm.edu
pointOfContact
David Cannon
Purdue University
2195102668
550 Stadium Mall Drive
West Lafayette
IN
47907
cannond@purdue.edu
pointOfContact
Qian Liao
University of Wisconsin
414-229-4228
Department of Civil and Environmental Engineering P.O. Box 413
Milwaukee
WI
53201
USA
liao@uwm.edu
pointOfContact
asNeeded
Dataset Version: 2
Unknown
pressure
temp
S2
turb
chlor
dissipation
profile_name
DOY_GMT
latitude
longitude
ISO_DateTime_UTC
RSI MicroCTD (Rockland Scientific International, Inc.)
theme
None, User defined
water pressure
water temperature at measurement depth
No BCO-DMO term
turbidity
fluorescence
cast
latitude
longitude
ISO_DateTime_UTC
featureType
BCO-DMO Standard Parameters
CTD - profiler
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: Regulation of plankton and nutrient dynamics by hydrodynamics and profundal filter feeders
https://osprey.bco-dmo.org/project/670679
Collaborative Research: Regulation of plankton and nutrient dynamics by hydrodynamics and profundal filter feeders
<p><em>Overview:</em><br />
While benthic filter feeders are known to influence plankton and nutrient dynamics in shallow marine and freshwater systems, their role is generally considered to be minor in large, deep systems. However, recent evidence indicates that profundal quagga mussels (Dreissena rostriformis bugensis) have dramatically altered energy flow and nutrient cycling in the Laurentian Great Lakes and other larges aquatic systems, so that conventional nutrient-plankton paradigms no longer apply. Observed rates of phosphorus grazing by profundal quagga mussels in Lake Michigan exceed the passive settling rates by nearly an order of magnitude, even under stably stratified conditions. We hypothesize that the apparently enhanced particle deliver rate to the lake bottom results from high filtration capacity combined with vertical mixing processes that advect phytoplankton from the euphotic zone to the near-bottom layer. However, the role of hydrodynamics is unclear, because these processes are poorly characterized both within the hypolimnion as a whole and within the near-bottom layer. In addition, the implications for phytoplankton and nutrient dynamics are unclear, as mussels are also important nutrient recyclers. In the proposed interdisciplinary research project, state-of-the-art instruments and analytical tools will be deployed in Lake Michigan to quantify these critical dynamic processes, including boundary layer turbulence, mussel grazing, excretion and egestion, and benthic fluxes of carbon and phosphorus. Empirical data will be used to calibrate a 3D hydrodynamic-biogeochemical model to test our hypotheses.</p>
<p><em>Intellectual Merit:</em><br />
This collaborative biophysical project is structured around two primary questions: 1) What role do profundal dreissenid mussels play in large lake carbon and nutrient cycles? 2) How are mussel grazing and the fate of nutrients recycled by mussels modulated by hydrodynamics at scales ranging from mm (benthic boundary layer) to meters (entire water column)? The project will improve the ability to model nutrient and carbon dynamics in coastal and lacustrine waters where benthic filter-feeders are a significant portion of the biota. By so doing, it will address the overarching question of how plankton and nutrient dynamics in large, deep lakes with abundant profundal filter feeders differ from the conventional paradigm described by previous models. Additionally, the project will quantify and characterize boundary layer turbulence for benthic boundary layers in large, deep lakes, including near-bed turbulence produced by benthic filter feeders.</p>
<p><em>Broader Impacts:</em><br />
The project will provide new insight into the impacts of invasive dreissenid mussels, which are now threatening many large lakes and reservoirs across the United States. Dreissenid mussels appear to be responsible for a number of major changes that have occurred in the Great Lakes, including declines of pelagic plankton populations, declines in fish populations, and, ironically, nuisance algal blooms in the nearshore zone. As a result, conventional management models no longer apply, and managers are uncertain about appropriate nutrient loading targets and fish stocking levels. The data and models resulting from this project will help to guide those decisions. Additionally, the project will provide insight to bottom boundary layer physics, with applicability to other large lakes, atidal coastal seas, and the deep ocean. The project will leverage the collaboration and promote interdisciplinary education for undergraduate and graduate students from two universities (UW-Milwaukee and Purdue). The project will support 3 Ph.D. students and provide structured research experiences to undergraduates through a summer research program. The project will also promote education of future aquatic scientists by hosting a Biophysical Coupling Workshop for graduate students who participate in the annual IAGLR conferences, and the workshop lectures will be published for general access through ASLO e-Lectures and on an open-access project website.</p>
<p><em>Background publications are available at:</em><br />
<a href="http://onlinelibrary.wiley.com/doi/10.1002/2014JC010506/full" target="_blank">http://onlinelibrary.wiley.com/doi/10.1002/2014JC010506/full</a><br />
<a href="http://link.springer.com/article/10.1007/s00348-012-1265-9" target="_blank">http://link.springer.com/article/10.1007/s00348-012-1265-9</a><br />
<a href="http://aslo.net/lomethods/free/2009/0169.pdf" target="_blank">http://aslo.net/lomethods/free/2009/0169.pdf</a><br />
<a href="http://www.sciencedirect.com/science/article/pii/S0380133015001458" target="_blank">http://www.sciencedirect.com/science/article/pii/S0380133015001458</a></p>
<p><em>Note: </em>This is an NSF Collaborative Research Project.</p>
Filter Feeders Physics and Phosphorus
largerWorkCitation
project
eng; USA
oceans
-87.753217
-87.753217
43.069917
43.069917
2017-08-01
2019-05-14
Lake Michigan
0
BCO-DMO catalogue of parameters from Microstructure profiles at Station AT55 in Lake Michigan from 2017, 2018 and 2019.
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/768015.rdf
Name: pressure
Units: decibar (dbar)
Description: <p>average pressure at measurement location</p>
http://lod.bco-dmo.org/id/dataset-parameter/768016.rdf
Name: temp
Units: degrees Celsius
Description: <p>average temperature</p>
http://lod.bco-dmo.org/id/dataset-parameter/768017.rdf
Name: S2
Units: 1/s2
Description: <p>average total velocity shear (S2=[dU/dz]2+[dV/dz]2</p>
http://lod.bco-dmo.org/id/dataset-parameter/768018.rdf
Name: turb
Units: FTU
Description: <p>average turbidity</p>
http://lod.bco-dmo.org/id/dataset-parameter/768019.rdf
Name: chlor
Units: ppb
Description: <p>average fluorescence</p>
http://lod.bco-dmo.org/id/dataset-parameter/768020.rdf
Name: dissipation
Units: Watts per kilogram (W/kg)
Description: <p>turbulent kinetic energy dissipation calculated from shear signal</p>
http://lod.bco-dmo.org/id/dataset-parameter/768021.rdf
Name: profile_name
Units: unitless
Description: <p>profile name extracted from submitted file name</p>
http://lod.bco-dmo.org/id/dataset-parameter/768022.rdf
Name: DOY_GMT
Units: unitless
Description: <p>time corresponding to each profile name. Times are taken as the average of measurement times for a given profile. Time units are days in GMT.</p>
http://lod.bco-dmo.org/id/dataset-parameter/768023.rdf
Name: latitude
Units: decimal degrees
Description: <p>latitude with positive values northward</p>
http://lod.bco-dmo.org/id/dataset-parameter/768024.rdf
Name: longitude
Units: decimal degrees
Description: <p>longituide with positive values eastward</p>
http://lod.bco-dmo.org/id/dataset-parameter/768025.rdf
Name: ISO_DateTime_UTC
Units: unitless
Description: <p>Date and time formatted following ISO8601 convention</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
3741611
https://darchive.mblwhoilibrary.org/bitstream/1912/27458/1/dataset-768011_mctd-lake-michigan-2017-2018-2019__v2.tsv
download
1247160
https://darchive.mblwhoilibrary.org/bitstream/1912/24151/1/dataset-768011_mctd-lake-michigan__v1.tsv
download
https://doi.org/10.1575/1912/bco-dmo.768011.1
download
onLine
dataset
<div>Microstructure profiles were taken over 3 years:</div>
<ul>
<li>2017: 176 microstructure profiles were collected over six days (August 1<sup>st</sup>, 2<sup>nd</sup>, 9<sup>th</sup>, 10<sup>th</sup>, 15<sup>th</sup>, and 16<sup>th</sup>).<em> </em></li>
<li>2018: 129 microstructure profiles were collected over three days (April 5th, 12th, and 20th).</li>
<li>2019: 78 microstructure profiles were collected over three days (May 13<sup>th</sup> and 14<sup>th</sup>).</li>
</ul>
<p>Measurements were collected using an RSI MicroCTD (Rockland Scientific International, Inc.) which sampled shear and temperature microstructure at 512Hz, free-falling at a velocity of 0.8 m/s (vertical resolution: ~1.5mm). Shear microstructure was analyzed to obtain turbulent kinetic energy dissipation (see data processing). Velocity shear was measured using two velocity shear probes (RSI; accuracy: 5%) oriented perpendicularly to collect orthogonal shear components. Microstructure temperatures were collected using 2 FP07 probes (accuracy: 0.005 <img src="///C:/Users/ksoenen/AppData/Local/Packages/oice_16_974fa576_32c1d314_2eb2/AC/Temp/msohtmlclip1/01/clip_image002.png" />), with the resulting measurements averaged to produce the single temperature estimate included in the attached files. Turbidity (accuracy: 2%) and fluorescence (accuracy: 1%) measurements were collected using a JAC-CLTU sensor (JFE Advantech Co., Ltd).&nbsp;&nbsp;</p>
<p>Microstructure profiles were collected manually by letting the instrument free fall through the water column. Profiles were timed and manually stopped to prevent the instrument from crashing into the bed and damaging sensors.</p>
Specified by the Principal Investigator(s)
<p>Data were downloaded from the instrument and converted to physical units using Matlab software provided by the manufacturer. The energy spectra of vertical velocity shear were used to estimate turbulent kinetic energy dissipation using a combination of power spectral density function integration and Nasmyth empirical spectrum fitting (manufacturer-provided algorithms; see attached TN_028_Dissipation.pdf).</p>
<p>Energy spectra were calculated from 2s (1024 sample) measurement intervals overlapped by 50% (vertical resolution: 0.8m), with corrections for both instrument accelerations and probe-induced spatial averaging (see attached TN_028_Dissipation.pdf).</p>
<p>The mean absolute deviation (MAD) was used to identify and discard all observed spectra that were effected by anisotropy or deviated significantly from the shape of the model spectrum, with a rejection criteria of MAD&gt;2(2/d)1/2, where d is degrees of freedom of the observed spectra.&nbsp;</p>
<p>BCO-DMO Processing Notes:<br />
-&nbsp;added conventional header with dataset name, PI name, version date<br />
- modified parameter names to conform with BCO-DMO naming conventions<br />
- added ISO_DateTime_UTC column with converted DOY_GMT into ISO 8601 format.<br />
- added "profile_name" column to contain information about the name of the profile.<br />
- added columns&nbsp;'DOY_GMT', 'latitude', 'longitude'&nbsp; from supplementary file, using the "profile_name" column as the join key.</p>
<p>&nbsp;</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
RSI MicroCTD (Rockland Scientific International, Inc.)
RSI MicroCTD (Rockland Scientific International, Inc.)
PI Supplied Instrument Name: RSI MicroCTD (Rockland Scientific International, Inc.) PI Supplied Instrument Description:Measurements were collected using an RSI MicroCTD (Rockland Scientific International, Inc.) which sampled shear and temperature microstructure at 512Hz, free-falling at a velocity of 0.8 m/s (vertical resolution: ~1.5mm). Instrument Name: CTD - profiler Instrument Short Name: Instrument Description: The Conductivity, Temperature, Depth (CTD) unit is an integrated instrument package designed to measure the conductivity, temperature, and pressure (depth) of the water column. The instrument is lowered via cable through the water column. It permits scientists to observe the physical properties in real-time via a conducting cable, which is typically connected to a CTD to a deck unit and computer on a ship. The CTD is often configured with additional optional sensors including fluorometers, transmissometers and/or radiometers. It is often combined with a Rosette of water sampling bottles (e.g. Niskin, GO-FLO) for collecting discrete water samples during the cast.
This term applies to profiling CTDs. For fixed CTDs, see https://www.bco-dmo.org/instrument/869934. Community Standard Description: http://vocab.nerc.ac.uk/collection/L05/current/130/