Contributors | Affiliation | Role |
---|---|---|
Maas, Amy | Bermuda Institute of Ocean Sciences (BIOS) | Principal Investigator |
Blanco-Bercial, Leocadio | Bermuda Institute of Ocean Sciences (BIOS) | Co-Principal Investigator |
Tarrant, Ann M. | Woods Hole Oceanographic Institution (WHOI) | Co-Principal Investigator |
Rauch, Shannon | Woods Hole Oceanographic Institution (WHOI BCO-DMO) | BCO-DMO Data Manager |
The CTD + 24 bottle sampling rosette was run using standard operating procedures. The bottles were fired on the up cast, 30 seconds after the unit was stopped.
Data were processed with provided config file (1377_27APR2019_McGreal.xmlcon). CTD data were binned by pressure and the bottle files extracted using SBEDataProcessing software.
BCO-DMO Processing:
- used awk script to re-format bottle files (moving avg and stdevs to columns);
- aggregated data from separate casts into one dataset;
- added lat and lon from file headers: NMEA Latitude, NMEA Longitude (converted to decimal degrees);
- added ISO date-time column.
File |
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AE1910_Bottles.csv (Comma Separated Values (.csv), 43.59 KB) MD5:c0124b5f84a4d631f6a227ab47ee00c8 Primary data file for dataset ID 774859 |
File |
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AE1910 CTD XMLCON file filename: 1377_27APR2019_McGreal.xmlcon (Extensible Markup Language (.xml), 10.65 KB) MD5:d289c14a2d83029272fa75566134af73 AE1910 CTD XMLCON file |
Parameter | Description | Units |
cast | CTD cast number (based on file name) | unitless |
latitude | NMEA Latitude from bottle file header; positive values = North | decimal degrees |
longitude | NMEA Longitude from bottle file header; positive values = East | decimal degrees |
Bottle | Bottle number | unitless |
Year | Four digit year; format: YYYY | unitless |
Month | One digit month (5 = May) | unitless |
Day | Two digit day of month | unitless |
Hours | Two digit hours portion of time | unitless |
Minutes | Two digit minutes portion of time | unitless |
Seconds | Two digit seconds portion of time | unitless |
DepSM_avg | Depth average | meters (m) |
DepSM_stdev | Depth standard deviation | meters (m) |
AltM_avg | Altimeter average | meters (m) |
AltM_stdev | Altimeter standard deviation | meters (m) |
CStarTr0_avg | Beam transmission (WET Labs C-Star) average | reciprocal meters (1/m) |
CStarTr0_stdev | Beam transmission (WET Labs C-Star) standard deviation | reciprocal meters (1/m) |
C0S_m_avg | Conductivity average | siemens per meter (S/m) |
C0S_m_stdev | Conductivity standard deviation | siemens per meter (S/m) |
FlC_avg | Fluorescence (Chelsea Aqua 3) average | micrograms per liter (ug/L) |
FlC_stdev | Fluorescence (Chelsea Aqua 3) standard deviation | micrograms per liter (ug/L) |
Sbeox0_avg | Oxygen (SBE 43) average (Named "Sbeox0Mm/Kg in original CTD file; renamed to avoid confusion because units of measurement are actually umol/kg.) | micromoles per kilogram (umol/kg) |
Sbeox0_stdev | Oxygen (SBE 43) standard deviation. (Named "Sbeox0Mm/Kg in original CTD file; renamed to avoid confusion because units of measurement are actually umol/kg.) | micromoles per kilogram (umol/kg) |
Par_avg | PAR/Irradiance (Biospherical/Licor) average | umol photons m-2 s-1 |
Par_stdev | PAR/Irradiance (Biospherical/Licor) standard deviation | umol photons m-2 s-1 |
PrDE_avg | Pressure average | psi |
PrDE_stdev | Pressure standard deviation | psi |
Sal00_avg | Salinity average | PSU |
Sal00_stdev | Salinity standard deviation | PSU |
T090C_avg | Temperature average | ITS-90, degrees C |
T090C_stdev | Temperature standard deviation | ITS-90, degrees C |
Sigma_e00_avg | Density [sigma-theta] average | kilograms per cubic meter (kg/m^3) |
Sigma_e00_stdev | Density [sigma-theta] standard deviation | kilograms per cubic meter (kg/m^3) |
Scan_avg | Scan number average | unitless |
Scan_stdev | Scan number standard deviation | unitless |
ISO_DateTime_UTC | Date and time (UTC) formatted to ISO8601 standard; format: YYYY-mm-ddTHH:MM:SSZ | unitless |
Dataset-specific Instrument Name | Sea-Bird SBE 9 11+ V 5.2 |
Generic Instrument Name | CTD Sea-Bird SBE 911plus |
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 | |
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. |
Website | |
Platform | R/V Atlantic Explorer |
Report | |
Start Date | 2019-05-20 |
End Date | 2019-05-23 |
Description | Additional cruise data may be available from the Rolling Deck to Repository (R2R): https://www.rvdata.us/search/cruise/AE1910 |
NSF Award Abstract:
The daily vertical migration (DMV) of zooplankton and fish across hundreds of meters between shallow and deep waters is a predominant pattern in pelagic ecosystems. This migration has consequences for biogeochemical cycling as it moves a substantial portion of fixed carbon and nitrogen (an estimated 15 to 40 % of the total global organic export) from the surface directly to depth where it feeds the midwater food chain and sequesters nutrients away from atmospheric mixing. Estimates and predictions of these fluxes are, however, poorly understood at present. New observations have shown that one source of uncertainty is due to the assumption that metabolic rates and processes do not vary over the course of the day, except based on changes in temperature and oxygen availability. Rates are, however, also driven by differences in feeding, swimming behavior, and underlying circadian cycles. The objective of this project is to improve the ability of scientists to understand and predict zooplankton contributions to the movement of carbon and nitrogen in the ocean by detailing daily changes in physiological processes of these organisms. By producing a set of respiration and excretion measurements over a daily time series, paired with simultaneously collected gene and protein expression patterns for an abundant vertically migratory species, the investigators will provide unprecedented and predictive insight into how changes in the environment affect the contribution of zooplankton to biogeochemical fluxes. The sampling design of the project will advance discovery and understanding by providing hands-on training opportunities to at least two undergraduate researchers. The project will broaden dissemination of the research via development of an educational module, focusing on rhythms in the ocean. The module will initially be piloted with the Bermuda Institute of Ocean Sciences (BIOS) summer camp students and then disseminated through the BIOS Explorer program, the Teacher Resources Page on the BIOS website, and published in a peer-reviewed educational journal.
This project will characterize the metabolic consequences of daily physiological rhythms and DVM for a model zooplankton species, the abundant subtropical copepod Pleuromamma xiphias. Flux processes (oxygen consumption, carbon dioxide production, production of ammonium and fecal pellet production) will be interrogated using directed experiments testing the effects of temperature, feeding and circadian cycle. Circadian cycling will further be examined using transcriptomic and proteomic profiling. These experiments will be related to field samples taken at 6-h intervals over the course of the diel migration using an integrated suite of molecular and organismal metrics. Combined organismal, transcriptomic and proteomic profiles will provide an understanding of which metabolic pathways and associated flux products vary in relation to particular environmental variables (food, light cycle, temperature). Diel variation in metabolic rates will also be assessed across seasons and species using other important migratory groups (pteropod, euphausiid, and another copepod). The metabolic data will then be contextualized with abundance estimates from archived depth-stratified tows to allow scaling to community-level patterns and will be used to improve calculations of zooplankton contribution to particulate organic carbon, nitrogen and respiratory active flux. The results of this study will both improve our flux estimates and provide predictive insight into how various environmental variables influence the underlying physiological pathways generating carbon and nitrogen flux.
Cruise reports are available from the completed cruises:
SD031019
AE1910
AE1918
Funding Source | Award |
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NSF Division of Ocean Sciences (NSF OCE) | |
NSF Division of Ocean Sciences (NSF OCE) |