Contributors | Affiliation | Role |
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Brzezinski, Mark A. | University of California-Santa Barbara (UCSB-MSI) | Principal Investigator |
Buck, Kristen Nicolle | University of South Florida (USF) | Co-Principal Investigator |
Jenkins, Bethany D. | University of Rhode Island (URI) | Co-Principal Investigator |
Jones, Janice L. | University of California-Santa Barbara (UCSB) | Contact |
Rauch, Shannon | BCO-DMO Data Manager |
Depth profiles in the euphotic zone of nutrient (nitrate, silicate, phosphate) concentrations, profiles of silicic acid uptake rates and assessment of limitation by Si and Fe on both silicic acid uptake and carbon fixation.
See related dataset: https://www.bco-dmo.org/dataset/786013
Seawater samples were collected using an epoxy coated CTD-rosette mounted with Go-Flo samplers and a Sea-Bird Electronics CTD (SBE9plus). Go-Flo bottles were transferred to a trace metal clean van for subsampling into polypropylene tubes (nutrients), polypropylene bottle (biogenic silica and particulate carbon and nitrogen) or TM acid-cleaned polycarbonate incubation bottles (Si-32 & C-14 incubation experiments).
Nutrient samples were filtered through 0.2 μm polycarbonate filters and frozen at -20°C. Samples for biogenic silica concentrations were size fractionated by serial filtration through 5 μm and 0.6 μm polycarbonate filters. Filters were stored frozen at -20°C. Particulate organic carbon and nitrogen were measured on samples from experiments examining the effect of added Fe and Si on carbon fixation. These samples were filtered through precombusted GFF filters placed in glass scintillation vials and frozen at -20°C.
Samples for silicic acid uptake profiles were spiked with the radioisotope Si-32. Nutrient limitation assays were performed on pairs of samples where rate of silicic acid uptake (Si-32) or carbon fixation (C-14 in paired light/dark bottles) were determined in unaltered controlled samples and in samples augmented with either silicic acid (20 μM) or iron chloride (1 nM). All samples were incubated on deck in simulated in situ incubators cooled with flowing surface seawater from 24 h. Profiles samples six depths from near surface to the 1% light level. Nutrient limitation assays were performed at the 40% and 10% light levels.
Particles from incubated samples were size fractionated by serial filtration through 5 μm and 0.6 μm 25 mm polycarbonate filters. For C-14 incubations, total radioactivity in each sample was determined by sampling 100 μl of sample seawater prior to filtration. Filters from Si-32 incubations were placed on plastic planchettes and dried before covering with mylar film and stored or analysis ashore using low level beta counters (Riso Inc). Filters from C-14 incubations were acidified in glass scintillation vials, scintillation cocktail (Ultima Gold XR) added followed by liquid scintillation counting. Total radioactivity samples received 100 μL of b-phenethylamine and 5 mL of scintillation cocktail prior to analysis at sea using a Beckman 8500 scintillation counter.
For more information, see the Protocol documents (under Supplemental Files).
Silicon uptake was calculated as the product of the fraction of total Si-32 radioactivity taken up and the ambient silicic acid concertation. Rates of primary production were calculated as the product of the fraction of total C-14 radioactivity taken up and a DIC value of 2132 μmol kg-1 correcting for isotope discrimination (x 1.05).
Nutrient concentrations were adjusted using certified JAMSTEC CRMs.
BCO-DMO Processing:
- formatted date to yyyy-mm-dd (was dd/mon/yy);
- modified parameter names (replaced spaces and symbols with underscores, removed units);
- replaced "~" and blanks with "nd" (no data);
- created ISO_DateTime_UTC field.
File |
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32Si_profiles.csv (Comma Separated Values (.csv), 8.23 KB) MD5:2c998035b7f80879e18965bd0476ebf4 Primary data file for dataset ID 785856 |
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Brzezinski Lab 14C Primary Production Protocols filename: 14C_Primary_Production.pdf (Portable Document Format (.pdf), 287.04 KB) MD5:98b17db0d497db8baef492b6f642dd05 Brzezinski Lab 14C Primary Production Protocols |
Brzezinski Lab 32Si Sample Processing Protocols filename: 32Si_Sample_Processing.pdf (Portable Document Format (.pdf), 218.87 KB) MD5:a4958e873573df157b6a20b4a2028c35 Brzezinski Lab 32Si Sample Processing Protocols |
Brzezinski Lab bSi Protocols filename: bSi_Protocol.pdf (Portable Document Format (.pdf), 214.54 KB) MD5:32afa2b8fe4d9ce0cde6b78bc9687248 Brzezinski Lab bSi Protocols |
Brzezinski Lab dSi Analysis Protocols filename: dSi_Analysis.pdf (Portable Document Format (.pdf), 353.66 KB) MD5:4d0670cfab1c27d77e33dc865448f489 Brzezinski Lab dSi Analysis Protocols |
Parameter | Description | Units |
Cruise | cruise during which sample was collected | unitless |
Date_Zulu | UTC date; format: yyyy-mm-dd | unitless |
Time_Zulu | UTC time; format: HH:MM:SS | unitless |
Event_num | event number from R2R event log | unitless |
Activity | which instrument was used for sample collection | unitless |
Station | station identifier | unitless |
Cast | cast type (CTD or experiment) and number | unitless |
Latitude | latitude in decimal degrees | decimal degrees North |
Longitude | longitude in decimal degrees | decimal degrees East |
Rosette_Bottle | rosette bottle number | unitless |
Target_Depth | target depth for sample collection | meters |
pcnt_lo | percent light level (PAR sensor) | unitless (percent) |
PO4 | Macronutrients (PO4) - dissolved phosphate concentration in micromoles - analyzed in UCSB MSI Analytical lab | mmol m-3 |
PO4_flag | data flag set as 1 (good) 2 (manual badflag) 3 (below detection limit) 9 (missing) as per Norm Nelson and his Seabass submission | unitless |
SiO4 | Macronutrients (SiO4) - silicic acid concentration in micromoles (also known as dissolved silicon concentration or dSi) | mmol m-3 |
SiO4_flag | data flag set as 1 (good) 2 (manual badflag) 3 (below detection limit) 9 (missing) as per Norm Nelson and his Seabass submission | unitless |
NO2 | Macronutrients (NO2) - dissolved nitrite concentration in micromoles - analyzed in UCSB MSI Analytical lab | mmol m-3 |
NO2_flag | data flag set as 1 (good) 2 (manual badflag) 3 (below detection limit) 9 (missing) as per Norm Nelson and his Seabass submission | unitless |
NO2_NO3 | dissolved nitrate+nitrite concentration in micromoles - analyzed in UCSB MSI Analytical lab | mmol m-3 |
NO2_NO3_flag | data flag set as 1 (good) 2 (manual badflag) 3 (below detection limit) 9 (missing) as per Norm Nelson and his Seabass submission | unitless |
BSi_0_6umfilt_5umprefilt | particulate biogenic silica in nanomoles Si per litre - 0.6-5um fraction | umol m-3 |
BSi_5umfilt | particulate biogenic silica in nanomoles Si per litre - >5um fraction | umol m-3 |
rate_32Si_uptake_24hr_0_6umfilt_5umprefilt | size fractionated silicic acid 32Si uptake 0.6-5um fraction | nmol Si L-1 d-1 |
rate_32Si_uptake_specific_24hr_0_6umfilt_5umprefilt | size fractionated specific silicic acid 32Si uptake 0.6-5um fraction | d-1 |
rate_32Si_uptake_24hr_5umfilt | size fractionated silicic acid 32Si uptake >5um fraction | nmol Si L-1 d-1 |
rate_32Si_uptake_specific_24hr_5umfilt | size fractionated specific silicic acid 32Si uptake >5um fraction | d-1 |
ISO_DateTime_UTC | Date and time foramtted to ISO8601 standard; format: yyyy-mm-ddTHH:MM:SS | unitless |
Dataset-specific Instrument Name | Sea-Bird Electronics CTD (SBE9plus) |
Generic Instrument Name | CTD Sea-Bird 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 |
Dataset-specific Instrument Name | Lachat Instruments QuikChem 8500 Series 2 anayzer |
Generic Instrument Name | Flow Injection Analyzer |
Generic Instrument Description | An instrument that performs flow injection analysis. Flow injection analysis (FIA) is an approach to chemical analysis that is accomplished by injecting a plug of sample into a flowing carrier stream. FIA is an automated method in which a sample is injected into a continuous flow of a carrier solution that mixes with other continuously flowing solutions before reaching a detector. Precision is dramatically increased when FIA is used instead of manual injections and as a result very specific FIA systems have been developed for a wide array of analytical techniques. |
Dataset-specific Instrument Name | Go-Flo samplers |
Generic Instrument Name | GO-FLO Bottle |
Generic Instrument Description | GO-FLO bottle cast used to collect water samples for pigment, nutrient, plankton, etc. The GO-FLO sampling bottle is specially designed to avoid sample contamination at the surface, internal spring contamination, loss of sample on deck (internal seals), and exchange of water from different depths. |
Dataset-specific Instrument Name | |
Generic Instrument Name | Light-Dark Bottle |
Generic Instrument Description | The light/dark bottle is a way of measuring primary production by comparing before and after concentrations of dissolved oxygen. Bottles containing seawater samples with phytoplankton are incubated for a predetermined period of time under light and dark conditions. Incubation is preferably carried out in situ, at the depth from which the samples were collected. Alternatively, the light and dark bottles are incubated in a water trough on deck, and neutral density filters are used to approximate the light conditions at the collection depth.Rates of net and gross photosynthesis and respiration can be determined from measurements of dissolved oxygen concentration in the sample bottles. |
Website | |
Platform | R/V Roger Revelle |
Report | |
Start Date | 2018-08-10 |
End Date | 2018-09-12 |
Description | Additional cruise information is available from the Rolling Deck to Repository (R2R): https://www.rvdata.us/search/cruise/RR1813 |
NSF Award Abstract:
This project focuses on a group of microscopic single-celled photosynthetic organisms in the ocean called diatoms. Diatoms float in the surface ocean as part of a group of organisms collectively called phytoplankton. There are thousands of different species of diatoms distributed across the global ocean. A famous oceanographer Henry Bigelow once said "All fish is diatoms" reflecting the importance of diatoms as the base of the food chain that supports the world's largest fisheries. Despite their small size, diatom photosynthesis produces 20% of the oxygen on earth each year. That's more than all of the tropical rain forests on land. The major objective of the research is to understand how the metabolic differences among diatom species affects the amount of diatom organic carbon that is carried, or exported, from the surface ocean to the deep ocean. As diatoms are photo-synthesizers like green plants, their biological carbon comes from converting carbon dioxide dissolved in seawater from the atmosphere into organic forms. Diatoms also require a series of other nurtrients supplied by the ocean such as nitrogen and phosphorous and, uniquely for diatoms, the silicon used to construct their glass shells. This research will investigate how genetic and physiological differences among diatoms influence how each species react to changes in nutrient levels in the ocean and how those shifts affect the export of diatom carbon to the deep sea. The link between diatoms' physiological response and their carbon export comes about because shifts in physiology affect diatom attributes like how fast they sink and how tasty they are to predators. So if we can relate the physiological condition of different diatoms to the food-web pathways followed by different species, we can ultimately use knowledge of diatom physiological status and food web structure to predict how much diatom carbon gets to the deep sea. The research involves investigators with expertise in the physiology and genomics of diatoms and in the ocean's chemistry. The work will initially take place in the subarctic North Pacific in conjunction with the NASA Export Processes in the Ocean from RemoTe Sensing (EXPORTS) field program. The EXPORTS program is using a wide variety of methods to quantify the export and fate of photo-synthetically fixed carbon in the upper ocean. The research supports the training of undergraduate students, graduate students and a postdoctoral scholar. The research will also serve as the basis for activities aimed at K-12 and junior high school students.
The research will broadly impact our understanding of the biology of the biological pump (the transport of photo-synthetically fixed organic carbon to the deep sea) by forming a mechanistic basis for predicting the export of diatom carbon. It is hypothesized that the type and degree of diatom physiological stress are vital aspects of ecosystem state that drive export. To test this hypothesis, the genetic composition, rates of nutrient use and growth response of diatom communities will be evaluated and supported with measurements of silicon and iron stress to evaluate stress as a predictor of the path of diatom carbon export. The subarctic N. Pacific ecosystem is characterized as high nutrient low chlorophyll (HNLC) due to low iron (Fe) levels that are primary controllers constraining phytoplankton utilization of other nutrients. It has been a paradigm in low Fe, HNLC systems that diatoms grow at elevated Si:C and Si:N ratios and should be efficiently exported as particles significantly enriched in Si relative to C. However, Fe limitation also alters diatoms species composition and the high Si demand imposed by low Fe can drive HNLC regions to Si limitation or Si/Fe co-limitation. Thus, the degree of Si and/or Fe stress in HNLC waters can all alter diatom taxonomic composition, the elemental composition of diatom cells, and the path cells follow through the food web ultimately altering diatom carbon export.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
EXport Processes in the Ocean from Remote Sensing (EXPORTS) is a large-scale NASA-led field campaign that will provide critical information for quantifying the export and fate of upper ocean net primary production (NPP) using satellite observations and state of the art ocean technologies.
Ocean ecosystems play a critical role in the Earth’s carbon cycle and the quantification of their impacts for both present conditions and for predictions into the future remains one of the greatest challenges in oceanography. The goal of the EXport Processes in the Ocean from Remote Sensing (EXPORTS) Science Plan is to develop a predictive understanding of the export and fate of global ocean net primary production (NPP) and its implications for present and future climates. The achievement of this goal requires a quantification of the mechanisms that control the export of carbon from the euphotic zone as well as its fate in the underlying "twilight zone" where some fraction of exported carbon will be sequestered in the ocean’s interior on time scales of months to millennia. In particular, EXPORTS will advance satellite diagnostic and numerical prognostic models by comparing relationships among the ecological, biogeochemical and physical oceanographic processes that control carbon cycling across a range of ecosystem and carbon cycling states. EXPORTS will achieve this through a combination of ship and robotic field sampling, satellite remote sensing and numerical modeling. Through a coordinated, process-oriented approach, EXPORTS will foster new insights on ocean carbon cycling that maximizes its societal relevance through the achievement of U.S. and International research agency goals and will be a key step towards our understanding of the Earth as an integrated system.
Funding Source | Award |
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NSF Division of Ocean Sciences (NSF OCE) |