Species composition via MOCNESS and associated CTD information collected on R/V Hugh R. Sharp (HRS1316, HRS1317) in the Chesapeake Bay from August to September in 2013.

Website: https://www.bco-dmo.org/dataset/707094
Data Type: Cruise Results
Version: 1
Version Date: 2017-06-28

Project
» Copepod Population Dynamics in Hypoxic Coastal Waters: Physical and Behavioral Regulation of Resupply and Advective Losses (CopesPopDynHypoZone)
ContributorsAffiliationRole
Roman, Michael R.University of Maryland Center for Environmental Science (UMCES/HPL)Principal Investigator
Pierson, James J.University of Maryland Center for Environmental Science (UMCES/HPL)Co-Principal Investigator, Contact
Fitzgerald, CatherineUniversity of Maryland Center for Environmental Science (UMCES/HPL)Contact
Ake, HannahWoods Hole Oceanographic Institution (WHOI BCO-DMO)BCO-DMO Data Manager

Abstract
Species composition via MOCNESS and associated CTD information collected on R/V Hugh R. Sharp (HRS1316, HRS1317) in the Chesapeake Bay from August to September in 2013.


Coverage

Spatial Extent: N:38.5761 E:-76.2741 S:38.3589 W:-76.5103
Temporal Extent: 2013-08-25 - 2013-09-17

Dataset Description

Species composition via MOCNESS and associated CTD information


Acquisition Description

This abundance data was obtained from two week-long cruises (1301 in August and 1302 in September) during which MOCNESS samples were taken from the mid-bay of the Chesapeake from 9 stations in a box formation; 3 stations in a northern transect across the bay (N1-N3), 3 in a midline transect (M1-M3), and 3 in a southern transect (S1-S3).

The MOCNESS had a 0.5 meter square opening for each of 5 nets, which were 200um mesh. It was deployed from the aft A-frame of the RV Sharp, along with an array of sensors connected to the MOCNESS frame, including Sea-Bird temperature, salinity, and dissolved oxygen (SBE 43) sensors, a WetLabs FLNTU to measure chlorophyll a fluorescence and turbidity, and a LiCor 4π PAR sensor.

A CTD cast was done at each station prior to sampling with the MOCNESS. Sampling depths were determined based on the location of the pycnocline; the aim was to capture zooplankton below, within, and above the pycnocline. A drogue net (net 0) without a codend was used to deploy the MOCNESS to within 3m of the bottom. On the upcast, nets were triggered to close electronically from the wet lab so that they captured a depth range representing one of the three areas of interest.

Once brought on board, the nets were rinsed down with filtered seawater (provided by the Hugh R. Sharp) to collect plankton in the codend. Codends were filtered onto 64um sieves, then the samples were transferred to glass jars labeled on the inside and outside with the cast number, date, time, net number, and depth sampled. Sieves with 64um mesh were selected to catch all life stages of the copepod Acartia tonsa since Acartia tonsa eggs are about 75um in diameter and all subsequent life stages are larger. Buffered formalin was added to preserve the sample in a 4% solution, and then the jars were stores in labeled boxes.

After returning from the cruises, samples were stored indoors in climate-controlled laboratory space. To process the samples, the contents of the jars were filtered onto 64um mesh (to avoid loss of organisms), resuspended, and a subsample taken with a stemple pipette was transferred to a counting wheel where it was checked for density and diluted if necessary, the goal being at least 200 individuals of Acartia tonsa present but less than 300.

The sample was then examined for species composition under dissecting microscope with darkfield illumination. All organisms were identified to lowest possible taxonomic level. When species composition analysis was complete, the processed aliquot was photographed for size measurements and stored in 4% buffered formalin solution in a glass vial. The unused portion of the sample was returned to the original glass jar and returned to storage.

Abundance data were entered into Excel spreadsheets and checked for transcription errors, then imported into MatLab for data analysis.


Processing Description

MOCNESS electronic data was post processed using a series of MATLAB scripts to read the raw and processed data, and to calculate summary statistics for each net. These are usually generated from the MOCNESS software in a “.TAB” file for each cruise, but the MOCNESS program does not use the incoming GPS data for calculation of time and instead used computer time. The MOCNESS scripts calculate time and location using GPS and also include the time from the computer.

Zooplankton samples were sorted under a stereo dissecting microscope within two years of collection. Sub samples were taken with a stempel pipet such that a minimum of 200 individuals were counted from each sample. Zooplankton were identified to lowest possible taxonomic level, to species where possible for copepods, and copepod adults were sexed.

BCO-DMO Data Processing Notes:

- replaced blank cells with nd
- reformatted column names to comply with BCO-DMO standards
- reformated dates to YYYY/MM/DD


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Parameters

ParameterDescriptionUnits
cruiseDesignation cruise 1301 or 1302; a week-long plankton survey in August and September respectively. unitless
MOCNumber ID of each MOCNESS cast as recorded by the MOCNESS software unitless
NETNumber ID of each net used during a MOCNESS cast as recorded by the MOCNESS software unitless
yearYear as recorded by the MOCNESS software; YYYY unitless
month_GMTGMT month as recorded by MOCNESS software; MM unitless
day_GMTGMT day as recorded by MOCNESS software; DD unitless
DOY_day_GMTNumeric day of year calculated from year, month, and day as recorded by MOCNESS software decimal day
hour_GMTGMT hour as recorded by MOCNESS software hours
minute_GMTGMT minute as recorded by MOCNESS software minutes
second_GMTGMT second as recorded by MOCNESS software seconds
DOY_GMTDay of year calculation using MOCNESS recorded GMT time decimal day
latAverage latitude traveled during collection for each net decimal degrees
lonAverage longitude traveled during collection for each net decimal degrees
volVolume filtered by each net during each cast, as recorded by MOCNESS software cubic meters
tempWater temperature recorded by MOCNESS sensors during each cast degrees Celsius
saltSalinity recorded by MOCNESS sensors during each cast Practical Salinity Units (PSU)
OxOxygen level recorded by MOCNESS sensors during each cast milligrams per liter
fluorFluorescence recorded by MOCNESS sensors during each cast milligrams per meter cubed
turbTurbidity recorded by MOCNESS sensors during each cast Nephelometric Turbidity Units (NTU)
PARPhotosynthetically active radiation recorded by MOCNESS sensors during each cast Watts/meters squared
startLatLatitude at the time the net opened decimal degrees
endLatLatitude at the time the same net closed decimal degrees
startLonLongitude at the time the net opened decimal degrees
endLonLongitude at the time the net closed decimal degrees
upDepthUpper limit of depth traversed while the net was open meters
lowDepth1Lower limit of the depth traversed while the net was open meters
angleThe angle of the tow line for the MOCNESS, with vertical being 0 and horizontal being 90 degrees
distanceHorizontal distance the ship traveled while the net was open meters
openAreaThe open area of the net face- calculated from the size of the net opening when held vertically and the angle of the tow line meters squared
idxUnique numeric ID for each row of data unitless
cruise2Designation cruise 1301 or 1302; a week-long plankton survey in August and September respectively unitless
date_EDTGergorian claendar date as recorded in the cruise log; YYYY/MM/DD unitless
stationStation ID as recorded in the cruise log unitless
time_EDTTime in EDT as recorded in the cruise log; HH:MM unitless
DOY_EDTDay of year calculation using cruise log EDT time decimal day
gearDescription of collection gear used. For this data set, only the MOCNESS was used unitless
mesh_sizeSize of pores in mesh of MOCENSS nets microns
cast_numNumber ID of each MOCNESS cast as recorded in cruise log unitless
netNumber ID of each net used during a MOCNESS cast as recorded in cruise log unitless
lowDepth2Lower limit of the depth traversed by a single net as recorded in cruise log meters
high_depthUpper limit of the depth traversed by a single net as recorded in cruise log meters
splitsNumber of times the sample gathered by the specific cast and net was split into two equal portions via plankton splitter count
dilutionAmount of water added to sample to reach the desired concentration of >= 200 Acartia/subsample milliliters
subsample_sizeAmount of sample (in diluted state, if applicable) examined for species composition milliliters
genusGenus or least specific identifier of organism in sample unitless
speciesSpecies or most specific identifier of organism in sample unitless
stageLife stage of organism in sample unitless
countTotal number of organism found in subsample number of organism/subsample
num_per_m3Concentration of organism per cubic meter calculated from dilutions, splits, and Volume_Filtered data number of organism/cubic meter
volume_filteredVolume filtered by each net during each cast, as recorded by MOCNESS software, augmented by record in operator log where necessary cubic meters
abundM3Concentration of organism per cubic meter calculated from dilutions, splits, and Vol data number of organism/cubic meter
abundM2Abundance of organism per meter squared calculated from AbundM3 and total depth traversed by net number of organism/ meter squared
CTD_numberNumber ID of each CTD cast corresponding to each MOCNESS tow unitless
CTD_DOY_GMTNumeric day of year calculated from year, month, and day as recorded by CTD decimal day
CTD_temperatureWater temperature recorded by CTD sensors during each cast; binned into 0.5m depths and then averaged over the depth range of the MOCNESS net degrees Celsius
CTD_salinitySalinity recorded by CTD sensors during each cast; binned into 0.5m depths and then averaged over the depth range of the MOCNESS net PSU
CTD_sigma_tDensity recorded by CTD sensors during each cast; binned into 0.5m depths and then averaged over the depth range of the MOCNESS net milligrams per liter
CTD_Ox__mgperLDissolved oxygen recorded by CTD sensors during each cast; binned into 0.5m depths and then averaged over the depth range of the MOCNESS net milligrams per liter
CTD_fluorescenceFluorescence recorded by CTD sensors during each cast; binned into 0.5m depths and then averaged over the depth range of the MOCNESS net milligrams per meter cubed
CTD_depthDepth recorded by CTD sensors during each cast; binned into 0.5m depths and then averaged over the depth range of the MOCNESS net meters
commentsComments from sample counter regarding sample processing unitless


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Instruments

Dataset-specific Instrument Name
CTD MOCNESS
Generic Instrument Name
CTD MOCNESS
Dataset-specific Description
Used for water sampling
Generic Instrument Description
The CTD part of the MOCNESS includes 1) a pressure (depth) sensor which is a thermally isolated titanium strain gauge with a standard range of 0-5000 decibars full scale, 2) A Sea Bird temperature sensor whose frequency output is measured and sent to the surface for logging and conversion to temperature by the software in the MOCNESS computer (The system allows better than 1 milli-degree resolution at 10 Hz sampling rate), and 3) A Sea Bird conductivity sensor whose output frequency is measured and sent to the surface for logging and conversion to conductivity by the software in the computer (The system allows better than 1 micro mho/cm at 10 Hz sampling rate). The data rate depends on the speed of the computer and the quality of the cable. With a good cable, the system can operate at 2400 baud, sampling all variables at 2 times per second. One sample every 4 seconds is the default, although the hardware can operate much faster. (From The MOCNESS Manual)


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Deployments

HRS1316

Website
Platform
R/V Hugh R. Sharp
Report
Start Date
2013-08-25
End Date
2013-09-01
Description
R/V Hugh R Sharp 1316. Mid-bay of Chesapeake Bay, 38°N 76°W.

HRS1317

Website
Platform
R/V Hugh R. Sharp
Report
Start Date
2013-09-12
End Date
2013-09-17
Description
R/V Hugh R Sharp 1317. Mid-bay of Chesapeake Bay, 38°N 76°W.


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Project Information

Copepod Population Dynamics in Hypoxic Coastal Waters: Physical and Behavioral Regulation of Resupply and Advective Losses (CopesPopDynHypoZone)

Coverage: hypoxic zone of Chesapeake Bay


Description from NSF award abstract:
The PIs will develop a mechanistic understanding of how circulation interacts with hypoxia-induced behavioral and physiological changes to affect the population dynamics of coastal zooplankton. They will do this by assessing two potentially contrasting mechanisms influencing the dynamics of the copepod Acartia tonsa in the hypoxic zone of Chesapeake Bay. The first hypothesis is that maintenance of copepod populations in the hypoxic region requires replenishment by advection (immigration) of animals through wind-driven lateral transport processes. The second, counteractive, hypothesis is that bottom water hypoxia alters the vertical distribution of A. tonsa, thereby making them more susceptible to advective losses from the region (emigration) via surface water transport in the estuarine circulation. They will take advantage of a current NSF-funded physical oceanography research program in Chesapeake Bay that will comprehensively measure and model axial and lateral water exchanges in the mid-Bay region.

The present study will use the physical oceanography study site as a Controlled Volume (CV) in which the oceanographic exchanges of water and the driving mechanisms for those exchanges will be well defined. The PIs will conduct high-resolution spatial and temporal sampling of zooplankton and combine the data with measurements of copepod behavior, mortality and egg production in the hypoxic region. They will use an improved Individual-Based Model of the life history of A. tonsa coupled with the circulation to explore the combined effects of advection, behavior, egg production, and mortality on population dynamics. In addition to increasing our knowledge of the impacts of bottom water hypoxia on copepod populations in Chesapeake Bay, the study will improve our general understanding of the regulation of zooplankton populations by physical and biological processes and the impacts of hypoxia on secondary production and food webs in coastal waters.



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Funding

Funding SourceAward
NSF Division of Ocean Sciences (NSF OCE)

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