Contributors | Affiliation | Role |
---|---|---|
Montoya, Joseph | Georgia Institute of Technology (GA Tech) | Principal Investigator |
Subramaniam, Ajit | Lamont-Doherty Earth Observatory (LDEO) | Co-Principal Investigator |
Rauch, Shannon | Woods Hole Oceanographic Institution (WHOI BCO-DMO) | BCO-DMO Data Manager |
Hydrographic data and water samples were collected during casts with a CTD-rosette system (SBE11plus equipped with a fluorometer, transmissometer, oxygen sensor, and a PAR sensor).
Water samples for dissolved, inorganic nutrient analysis were collected in duplicate directly from Niskin bottles attached to the CTD-rosette system (listed above). Sampling tubes were rinsed with sample water three times before collection. After collection, one set of samples was placed in a fridge to be analyzed within 48hrs aboard the vessel while the duplicate set of samples was placed immediately in a freezer for later analysis. Analysis was completed on a Lachat Quickchem 8500 Series 2 nutrient analyzer, according to standard methods listed below:
PO4: 31-115-01-I
Si: 31-114-27-1-B
NO3/NO2: 31-107-04-1-A
NO2: 31-107-05-1-A
Method details available at: https://support.hach.com/app/answers/answer_view/a_id/1004798
Data Processing:
Hydrographic data were processed using SeaSave v 7.26.7.121. Please see the "EN640_Nutrients_Processing_Notes.pdf" Supplemental File for data processing details. Nutrient data were processed using Omnion 3.0 Software.
BCO-DMO Processing:
- renamed fields to comply with BCO-DMO naming conventions;
- converted date to YYYY-MM-DD format;
- added date-time field in ISO8601 format.
File |
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EN640_Nutrients.csv (Comma Separated Values (.csv), 149.23 KB) MD5:9d976d58668a465493ae70cc8ebc6464 Primary data file for dataset ID 861378 |
File |
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EN640_Nutrients_Processing_Notes.pdf (Portable Document Format (.pdf), 777.34 KB) MD5:6529d636c356d947e0a0c98e37ec1d9f Processing notes for the EN640 Nutrients data, including representative SeaBird header file. |
Parameter | Description | Units |
FileName | Original name of data file | unitless |
Cruise | Cruise identifier | unitless |
Station | Station number | unitless |
StnEvent | Numeric identifier for each deployment in the format SSS.EE, where SSS is the station number and EE identifies the specific sampling event | unitless |
BottleID | Bottle identifier (station, event, bottle) | unitless |
Bottle | Bottle number | unitless |
ISO_DateTime_UTC | Date and time (UTC) in ISO8601 format: YYYY-MM-DDThh:mm:ssZ | unitless |
Date | Date (UTC) in format YYYY-MM-DD | unitless |
Time | Time (UTC) in format hh:mm:ss | unitless |
Sal00 | Salinity, Practical | PSU |
Sal11 | Salinity, Practical, 2 | PSU |
Sigma_t00 | Density [sigma-theta] | kilograms per cubic meter (kg/m^3) |
Sigma_t11 | Density, 2 [sigma-theta] | kilograms per cubic meter (kg/m^3) |
Oxsat | O2 saturation | Mm/Kg |
Sbeox0 | Oxygen, SBE 43, WS = 2 | micromoles per liter (umol/L) |
Sbeox1 | Oxygen, SBE 43, 2, WS = 2 | micromoles per liter (umol/L) |
Potemp090 | Potential Temperature [ITS-90] | degrees Celsius |
Potemp190 | Potential Temperature, 2 [ITS-90] | degrees Celsius |
SvCM | Sound Velocity [Chen-Millero] | meters per second (m/s) |
SvCM1 | Sound Velocity, 2 [Chen-Millero] | meters per second (m/s) |
Scan | Scan count | unitless |
Scan_SD | Standard deviation of Scan | unitless |
TimeJ | Julian day (UTC) | unitless |
TimeJ_SD | Standard deviation of TimeJ | unitless |
TimeS | Time elapsed | seconds |
TimeS_SD | Standard deviation of TimeS | seconds |
PrDM | Pressure, Digiquartz | decibars (db) |
PrDM_SD | Standard deviation of PrDM | decibars (db) |
DepSM | Depth [salt water, m] | meters (m) |
DepSM_SD | Standard deviation of DepSM | meters (m) |
T090C | Temperature [ITS-90] | degrees Celsius |
T090C_SD | Standard deviation of T090C | degrees Celsius |
T190C | Temperature, 2 [ITS-90] | degrees Celsius |
T190C_SD | Standard deviation of T190C | degrees Celsius |
T2_T190C | Temperature Difference, 2 - 1 [ITS-90] | degrees Celsius |
T2_T190C_SD | Standard deviation of T2_T190C | degrees Celsius |
C0S | Conductivity | Siemens per meter (S/m) |
C0S_SD | Standard deviation of C0S | Siemens per meter (S/m) |
C1S | Conductivity, 2 | Siemens per meter (S/m) |
C1S_SD | Standard deviation of C1S | Siemens per meter (S/m) |
C2_C1 | Conductivity Difference, 2 - 1 | Siemens per meter (S/m) |
C2_C1_SD | Standard deviation of C2_C1 | Siemens per meter (S/m) |
V0 | Voltage 0 | volts (V) |
V0_SD | Standard deviation of V0 | volts (V) |
CStarAt0 | Beam Attenuation, WET Labs C-Star | reciprocal meters (1/m) |
CStarAt0_SD | Standard deviation of CStarAt0 | reciprocal meters (1/m) |
CStarTr0 | Beam Transmission, WET Labs C-Star | percent (%) |
CStarTr0_SD | Standard deviation of CStarTr0 | percent (%) |
V1 | Voltage 1 | volts (V) |
V1_SD | Standard deviation of V1 | volts (V) |
FlECO_AFL | Fluorescence, WET Labs ECO-AFL/FL | milligrams per cubic meter (mg/m^3) |
FlECO_AFL_SD | Standard deviation of FlECO_AFL | milligrams per cubic meter (mg/m^3) |
V2 | Voltage 2 | volts (V) |
V2_SD | Standard deviation of V2 | volts (V) |
AltM | Altimeter | meters (m) |
AltM_SD | Standard deviation of AltM | meters (m) |
V3 | Voltage 3 | volts (V) |
V3_SD | Standard deviation of V3 | volts (V) |
Par | PAR/Irradiance, Biospherical/Licor | micromoles photons per square meter per second (umol photons/m^2/sec) |
Par_SD | Standard deviation of Par | micromoles photons per square meter per second (umol photons/m^2/sec) |
V4 | Voltage 4 | volts (V) |
V4_SD | Standard deviation of V4 | volts (V) |
Sbeox0V | Oxygen raw, SBE 43 | volts (V) |
Sbeox0V_SD | Standard deviation of Sbeox0V | volts (V) |
V5 | Voltage 5 | volts (V) |
V5_SD | Standard deviation of V5 | volts (V) |
Sbeox1V | Oxygen raw, SBE 43, 2 | volts (V) |
Sbeox1V_SD | Standard deviation of Sbeox1V | volts (V) |
V6 | Voltage 6 | volts (V) |
V6_SD | Standard deviation of V6 | volts (V) |
V7 | Voltage 7 | volts (V) |
V7_SD | Standard deviation of V7 | volts (V) |
Spar | SPAR Biospherical/Licor | micromoles photons per square meter per second (umol photons/m^2/sec) |
Spar_SD | Standard deviation of Spar | micromoles photons per square meter per second (umol photons/m^2/sec) |
Latitude | Latitude | degrees North |
Latitude_SD | Standard deviation of Latitude | degrees North |
Longitude | Longitude | degrees East |
Longitude_SD | Standard deviation of Longitude | degrees East |
Mean_PO4 | dissolved, inorganic phosphate | micromolar (uM) |
Mean_Si | dissolved, inorganic silicate | micromolar (uM) |
Mean_NO3_NO2 | dissolved, inorganic nitrate/nitrite | micromolar (uM) |
Mean_NO2 | dissolved, inorganic nitrite | micromolar (uM) |
Mean_N_star | deviation of NO3/NO2 relative to PO4 from the Redfield Ratio | unitless |
Dataset-specific Instrument Name | |
Generic Instrument Name | CTD Sea-Bird SBE 911plus |
Dataset-specific Description | Hydrographic data and water samples were collected during casts with a CTD-rosette system (SBE11plus equipped with a fluorometer, transmissometer, oxygen sensor, and a PAR sensor). Individual sensor details and calibration info provided in the "EN614_Nutrients_Processing_Notes.pdf" Supplemental File. |
Generic Instrument Description | The Sea-Bird SBE 911 plus is a type of CTD instrument package for continuous measurement of conductivity, temperature and pressure. The SBE 911 plus includes the SBE 9plus Underwater Unit and the SBE 11plus Deck Unit (for real-time readout using conductive wire) for deployment from a vessel. The combination of the SBE 9 plus and SBE 11 plus is called a SBE 911 plus. The SBE 9 plus uses Sea-Bird's standard modular temperature and conductivity sensors (SBE 3 plus and SBE 4). The SBE 9 plus CTD can be configured with up to eight auxiliary sensors to measure other parameters including dissolved oxygen, pH, turbidity, fluorescence, light (PAR), light transmission, etc.). more information from Sea-Bird Electronics |
Dataset-specific Instrument Name | Biospherical/Licor |
Generic Instrument Name | LI-COR Biospherical PAR Sensor |
Generic Instrument Description | The LI-COR Biospherical PAR Sensor is used to measure Photosynthetically Available Radiation (PAR) in the water column. This instrument designation is used when specific make and model are not known. |
Dataset-specific Instrument Name | Niskin bottles attached to CTD-rosette system |
Generic Instrument Name | Niskin bottle |
Generic Instrument Description | A Niskin bottle (a next generation water sampler based on the Nansen bottle) is a cylindrical, non-metallic water collection device with stoppers at both ends. The bottles can be attached individually on a hydrowire or deployed in 12, 24, or 36 bottle Rosette systems mounted on a frame and combined with a CTD. Niskin bottles are used to collect discrete water samples for a range of measurements including pigments, nutrients, plankton, etc. |
Dataset-specific Instrument Name | Lachat Quikchem 8500 Series 2 |
Generic Instrument Name | Nutrient Autoanalyzer |
Dataset-specific Description | Lachat Quikchem 8500 Series 2, with ASX-260 autosampler, manufactured by Lachat Instruments a Hach company brand |
Generic Instrument Description | Nutrient Autoanalyzer is a generic term used when specific type, make and model were not specified. In general, a Nutrient Autoanalyzer is an automated flow-thru system for doing nutrient analysis (nitrate, ammonium, orthophosphate, and silicate) on seawater samples. |
Dataset-specific Instrument Name | SBE 43 |
Generic Instrument Name | Sea-Bird SBE 43 Dissolved Oxygen Sensor |
Generic Instrument Description | The Sea-Bird SBE 43 dissolved oxygen sensor is a redesign of the Clark polarographic membrane type of dissolved oxygen sensors. more information from Sea-Bird Electronics |
Dataset-specific Instrument Name | WET Labs ECO-AFL/FL |
Generic Instrument Name | Wet Labs ECO-AFL/FL Fluorometer |
Generic Instrument Description | The Environmental Characterization Optics (ECO) series of single channel fluorometers delivers both high resolution and wide ranges across the entire line of parameters using 14 bit digital processing. The ECO series excels in biological monitoring and dye trace studies. The potted optics block results in long term stability of the instrument and the optional anti-biofouling technology delivers truly long term field measurements.
more information from Wet Labs |
Dataset-specific Instrument Name | WET Labs C-Star |
Generic Instrument Name | WET Labs {Sea-Bird WETLabs} C-Star transmissometer |
Generic Instrument Description | The C-Star transmissometer has a novel monolithic housing with a highly intgrated opto-electronic design to provide a low cost, compact solution for underwater measurements of beam transmittance. The C-Star is capable of free space measurements or flow-through sampling when used with a pump and optical flow tubes. The sensor can be used in profiling, moored, or underway applications. Available with a 6000 m depth rating.
More information on Sea-Bird website: https://www.seabird.com/c-star-transmissometer/product?id=60762467717 |
Website | |
Platform | R/V Endeavor |
Start Date | 2019-06-13 |
End Date | 2019-07-08 |
Description | See more information from the Rolling Deck to Repository (R2R): https://www.rvdata.us/search/cruise/EN640 |
NSF Award Abstract:
This is a focused program of field research in waters of the Western Tropical North Atlantic influenced by the Amazon River Plume during the high river flow season. The Amazon Plume region supports diverse plankton communities in a dynamic system driven by nutrients supplied by transport from the river proper as well as nutrients entrained from offshore waters by physical mixing and upwelling. This creates strong interactions among physical, chemical, and biological processes across a range of spatial and temporal scales. The field program will link direct measurements of environmental properties with focused experimental studies of nutrient supply and nutrient limitation of phytoplankton, as well as the transfer of phytoplankton nitrogen to the zooplankton food web. The Amazon Plume exhibits a close juxtaposition of distinct communities during the high-flow season, making it an ideal site for evaluating how nutrient availability, nutrient supply, and habitat longevity interact to drive offshore ecosystem dynamics and function. This project will include German collaborators and will seamlessly integrate education and research efforts. The investigators and their institutions have a strong commitment to undergraduate and graduate education and to increasing the diversity of the ocean science community through active recruiting and training efforts. The team has a strong track record of involving both undergraduate and graduate students in their field and lab research. The two research cruises planned will provide opportunities for students and technicians to interact with an interdisciplinary and international research team.
The ultimate objectives of this project are to understand the processes and interactions that promote distinct communities of nitrogen-fixing organisms (diazotrophs) and other phytoplankton around the Amazon Plume and to explore the impacts of these diazotroph-rich communities on zooplankton biomass and production. The research team includes scientists with expertise in nutrient and stable isotope biogeochemistry, remote sensing as well as specialists in characterizing water mass origin and history using naturally occurring radium isotopes. This combination of approaches will provide a unique opportunity to address fundamental questions related to plankton community structure, primary production, and links to secondary production in pelagic ecosystems. The project will address the following key questions focused on fundamental issues in plankton ecology resulting from previous research in this region:
A. What mechanisms promote the preferential delivery of bioavailable phosphorus and the resulting strong nitrogen limitation associated with the northern reaches of the Amazon Plume during the high flow season?
B. What factors lead to the clear niche separation between diazotrophs within and around the Amazon Plume and how are the distinct diazotroph communities influenced by hydrographic and biogeochemical controls associated with the Amazon River Plume and offshore upwelling processes?
C. How does the nitrogen fixed by the different types of diazotrophs contribute to secondary production, and how efficiently does diazotroph nitrogen move through the food web?
Funding Source | Award |
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NSF Division of Ocean Sciences (NSF OCE) |