Contributors | Affiliation | Role |
---|---|---|
McGillicuddy, Dennis J. | Woods Hole Oceanographic Institution (WHOI) | Principal Investigator |
Zhang, Weifeng Gordon | Woods Hole Oceanographic Institution (WHOI) | Co-Principal Investigator |
Kosnyrev, Olga | Woods Hole Oceanographic Institution (WHOI) | Data Manager |
Biddle, Mathew | Woods Hole Oceanographic Institution (WHOI BCO-DMO) | BCO-DMO Data Manager |
York, Amber D. | Woods Hole Oceanographic Institution (WHOI BCO-DMO) | BCO-DMO Data Manager |
Standard CTD cast. Water sampling bottle data (up casts) from standard station CTD profiles. Bottle numbers are [140, 141, 142, 143]
Sea-Bird Software:
Data acquisition: SBE Seasave, version 7.23.2
Data processing: SBE Data Processing, version 7.26.7.114
BCO-DMO Processing Notes:
- added conventional header with dataset name, PI name, version date
- modified parameter names to conform with BCO-DMO naming conventions
- converted latitude and longitude coordinates to decimal degrees in the lat and lon columns
- concatenated all seabird data bottle files into one dataset.
- added ISO_DateTime_UTC, latitude, and longitude fields
File |
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btl.csv (Comma Separated Values (.csv), 15.14 KB) MD5:4d15b79ea9561924f58d260b8432c8c9 Primary data file for dataset ID 815450 |
Parameter | Description | Units |
file_name | file name for the bottle file | unitless |
latitude | Latitude of station location with positive values indicating North | decimal degrees |
longitude | Longitude of station location with negative values indicating West | decimal degrees |
ISO_DateTime_UTC | Date and time of observations following ISO8601 format | unitless |
Bottle | Bottle number | unitless |
SvCM1_avg | Average Sound Velocity Chen-Millero 2 | meter per second (m/s) |
PrDM_avg | Average Pressure | decibar (db) |
T090C_avg | Average Temperature ITS-90 | degrees Celsius (C) |
T190C_avg | Average Temperature 2 ITS-90 | degrees Celsius (C) |
C0S_m_avg | Average conductivity | Siemens per meter (S/m) |
C1S_m_avg | Average conductivity 2 | Siemens per meter (S/m) |
Sbeox0V_avg | Average Oxygen raw SBE 43 | volts (V) |
Sal00_avg | Average practical salinity | unitless |
Spar_avg | Average SPAR Biospherical/Licor | microEinsteins per meter squared per second (uE/m2/s) |
Par_avg | Average PAR/Irradiance Biospherical/Licor | microEinsteins per meter squared per second (uE/m2/s) |
Cpar_avg | Average CPAR/Corrected Irradiance | percent (%) |
Scan_avg | scan count for average | unitless |
Sigma_e00_avg | Average Density sigma-theta | kilogram per meter cubed (kg/m3) |
Sigma_e11_avg | Average Density 2 sigma-theta | kilogram per meter cubed (kg/m3) |
Sbeox0ML_L_avg | Average Oxygen concentration | milliliter per liter (mL/L) |
OxsolMm_Kg_avg | Average Oxygen saturation | mikroMol per kilogram (mkMol/kg) |
Sbox0Mm_Kg_avg | Average Oxygen concentration | mikroMol per kilogram (mkMol/kg) |
Potemp090C_avg | Average potential temperature | degrees Celsius (C) |
Potemp190C_avg | Average potential temperature 2 | degrees Celsius (C) |
Sal11_avg | Average practical salinity 2 | unitless |
Density00_avg | Average density | unknown |
Density11_avg | Average density 2 | unknown |
SvCM_avg | Average Sound Velocity Chen-Millero | meter per second (m/s) |
FlECO_AFL_avg | Average Fluorescence WET Labs ECO-AFL/FL | milligrams per meter cubed (mg/m3) |
TurbWETntu0_avg | Average Turbidity WET Labs ECO | NTU |
C0S_m_max | Maximum conductivity | Siemens per meter (S/m) |
C1S_m_max | Maximum conductivity 2 | Siemens per meter (S/m) |
Cpar_max | Maximum CPAR/Corrected Irradiance | percent (%) |
FlECO_AFL_max | Maximum Fluorescence WET Labs ECO-AFL/FL | milligrams per meter cubed (mg/m3) |
Par_max | Maximum PAR/Irradiance Biospherical/Licor | microEinsteins per meter squared per second (uE/m2/s) |
PrDM_max | Maximum pressue | decibar (db) |
Sal00_max | Maximum practical salinity | unitless |
Sbeox0V_max | Maximum Oxygen raw SBE 43 | volts (V) |
Scan_max | scan count for maximum | unitless |
Spar_max | Maximum SPAR Biospherical/Licor | microEinsteins per meter squared per second (uE/m2/s) |
T090C_max | Maximum Temperature ITS-90 | degrees Celsius (C) |
T190C_max | Maximum Temperature 2 ITS-90 | degrees Celsius (C) |
TurbWETntu0_max | Maximum Turbidity WET Labs ECO | NTU |
C0S_m_min | Minimum conductivity | Siemens per meter (S/m) |
C1S_m_min | Minimum conductivity 2 | Siemens per meter (S/m) |
Cpar_min | Minimum CPAR/Corrected Irradiance | percent (%) |
FlECO_AFL_min | Minimum Fluorescence WET Labs ECO-AFL/FL | milligrams per meter cubed (mg/m3) |
Par_min | Minimum PAR/Irradiance Biospherical/Licor | microEinsteins per meter squared per second (uE/m2/s) |
PrDM_min | Minimum pressure | decibar (db) |
Sal00_min | Minimum practical salinity | unitless |
Sbeox0V_min | Minimum Oxygen raw SBE 43 | volts (V) |
Scan_min | scan count for minimum | unitless |
Spar_min | Minimum SPAR Biospherical/Licor | microEinsteins per meter squared per second (uE/m2/s) |
T090C_min | Minimum Temperature ITS-90 | degrees Celsius (C) |
T190C_min | Minimum Temperature 2 ITS-90 | degrees Celsius (C) |
TurbWETntu0_min | Minimum Turbidity WET Labs ECO | NTU |
C0S_m_sdev | Standard Deviation of conductivity | Siemens per meter (S/m) |
C1S_m_sdev | Standard Deviation of conductivity | Siemens per meter (S/m) |
Cpar_sdev | Standard Deviation of CPAR/Corrected Irradiance | percent (%) |
FlECO_AFL_sdev | Standard Deviation of Fluorescence WET Labs ECO-AFL/FL | milligrams per meter cubed (mg/m3) |
Par_sdev | Standard Deviation of PAR/Irradiance Biospherical/Licor | microEinsteins per meter squared per second (uE/m2/s) |
PrDM_sdev | Standard Deviation of pressure | decibar (db) |
Sal00_sdev | Standard Deviation of practical salinity | unitless |
Sbeox0V_sdev | Standard Deviation of Oxygen raw SBE 43 | volts (V) |
Scan_sdev | scan count for Standard Deviation | unitless |
Spar_sdev | Standard Deviation of SPAR Biospherical/Licor | microEinsteins per meter squared per second (uE/m2/s) |
T090C_sdev | Standard Deviation of Temperature ITS-90 | degrees Celsius (C) |
T190C_sdev | Standard Deviation of Temperature 2 ITS-90 | degrees Celsius (C) |
TurbWETntu0_sdev | Standard Deviation of Turbidity WET Labs ECO | NTU |
Dataset-specific Instrument Name | Sea-Bird SBE 9 |
Generic Instrument Name | CTD Sea-Bird 9 |
Dataset-specific Description | Sea-Bird SBE 9 |
Generic Instrument Description | The Sea-Bird SBE 9 is a type of CTD instrument package. The SBE 9 is the Underwater Unit and is most often combined with the SBE 11 Deck Unit (for real-time readout using conductive wire) when deployed from a research vessel. The combination of the SBE 9 and SBE 11 is called a SBE 911. The SBE 9 uses Sea-Bird's standard modular temperature and conductivity sensors (SBE 3 and SBE 4). The SBE 9 CTD can be configured with auxiliary sensors to measure other parameters including dissolved oxygen, pH, turbidity, fluorometer, altimeter, etc.). Note that in most cases, it is more accurate to specify SBE 911 than SBE 9 since it is likely a SBE 11 deck unit was used. more information from Sea-Bird Electronics |
Website | |
Platform | R/V Neil Armstrong |
Start Date | 2018-04-16 |
End Date | 2018-04-29 |
NSF award abstract:
The continental shelf break of the Middle Atlantic Bight supports a productive and diverse ecosystem. Current paradigms suggest that this productivity is driven by several upwelling mechanisms at the shelf break front. This upwelling supplies nutrients that stimulate primary production by phytoplankton, which in turn leads to enhanced production at higher trophic levels. Although local enhancement of phytoplankton biomass has been observed in some circumstances, such a feature is curiously absent from time-averaged measurements, both from satellites and shipboard sampling. Why would there not be a mean enhancement in phytoplankton biomass as a result of the upwelling? One hypothesis is that grazing by zooplankton prevents accumulation of biomass on seasonal and longer time scales, transferring the excess production to higher trophic levels and thereby contributing to the overall productivity of the ecosystem. However, another possibility is that the net impact of these highly intermittent processes is not adequately represented in long-term means of the observations, because of the relatively low resolution of the in-water measurements and the fact that the frontal enhancement can take place below the depth observable by satellite. The deployment of the Ocean Observatories Initiative (OOI) Pioneer Array south of New England has provided a unique opportunity to test these hypotheses. The combination of moored instrumentation and autonomous underwater vehicles will facilitate observations of the frontal system with unprecedented spatial and temporal resolution. This will provide an ideal four-dimensional (space-time) context in which to conduct a detailed study of frontal dynamics and plankton communities needed to examine mechanisms controlling phytoplankton populations in this frontal system. This project will also: (1) promote teaching, training and learning via participation of graduate and undergraduate students in the research , (2) provide a broad dissemination of information by means of outreach in public forums, printed media, and a video documentary of the field work, and (3) contribute to improving societal well-being and increased economic competitiveness by providing the knowledge needed for science-based stewardship of coastal ecosystems, with particular emphasis on connecting with the fishing industry through the Commercial Fisheries Research Foundation.
The investigators will conduct a set of three cruises to obtain cross-shelf sections of physical, chemical, and biological properties within the Pioneer Array. Nutrient distributions will be assayed together with hydrography to detect the signature of frontal upwelling and associated nutrient supply. The investigators expect that enhanced nutrient supply will lead to changes in the phytoplankton assemblage, which will be quantified with conventional flow cytometry, imaging flow cytometry (Imaging FlowCytobot, IFCB), optical imaging (Video Plankton Recorder, VPR), traditional microscopic methods, and pigment analysis. Zooplankton will be measured in size classes ranging from micro- to mesozooplankton with the IFCB and VPR, respectively, and also with microscopic analysis. Biological responses to upwelling will be assessed by measuring rates of primary productivity, zooplankton grazing, and net community production. These observations will be synthesized in the context of a coupled physical-biological model to test the two hypotheses that can potentially explain prior observations: (1) grazer-mediated control and (2) undersampling. Hindcast simulations will also be used to diagnose the relative importance of the various mechanisms of upwelling. The intellectual merit of this effort stems from our interdisciplinary approach, advanced observational techniques, and integrated analysis in the context of a state-of-the-art coupled model. The project will address longstanding questions regarding hydrodynamics and productivity of an important ecosystem, leading to improved understanding of physical-biological interactions in a complex continental shelf regime. Given the importance of frontal systems in the global coastal ocean, it is expected that knowledge gained will have broad applicability beyond the specific region being studied.
Funding Source | Award |
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NSF Division of Ocean Sciences (NSF OCE) |