Table of Contents

• Coverage
• Dataset Description
  • Methods & Sampling
  • Data Processing Description
  • BCO-DMO Curation Notes
  • Problem Description
• Data Files
• Parameters
• Instruments
• Deployments
• Project Information
• Funding

During deployments, the CTD/Rosette with 24 10-liter (L) Niskin bottles was controlled from the console on a Windows PC, using the Sea-Bird SeaSave software (version 7.26.7.121). The CTD/Rosette was first lowered to 10 meters wire out for a 'soak' to let the oxygen and other sensors acclimate. Once the oxygen reading was stable and temperature and salinity differences of the dual sensors were minimal (usually 1-2 minutes), the CTD/Rosette was brought back to the surface and then sent down to the deepest sampling depth. The Niskin bottles were closed during the upcast. Once the CTD/Rosette reached a target depth, bottles were closed after waiting for 2-3 ship rolls or about 20-25 seconds. This resulted in the water that was being dragged up by the CTD/rosette to dissipate and ensured that the water collected in the bottle was representative of the undisturbed water at that depth. On casts where samples were collected 10 meters above the seafloor, the altimeter was used to determine the distance of the CTD/Rosette to the bottom. The altimeter normally kicked in at around 100 meters from the bottom.

After the cast was completed, the raw data was processed using the SBE Data Processing SeaSoft software (version 7.26.7).  The following processing modules were used in sequence:

1. DatCnv – converts raw binary data to engineering units using the sensor calibrations and outputs data in text format (.cnv files).

2. Filter – applies a low pass filter to smooth rapidly changing data.  The filter was applied to the following parameters: pressure (depth), oxygen and transmission.

3. AlignCTD – aligns slower responding sensors with pressure.  A 3 second offset was used for the oxygen sensor.

4. CellTM – removes conductivity cell thermal mass effects.

5. LoopEdit – removes effects of pressure reversals due to ship roll.  It was also used to remove the surface soak from the downcast.

6. Derive – uses pressure, temperature and conductivity from the sensors to derive parameters like salinity, density, potential temperature, etc.

7. BinAvg – bins the data.  Data was binned in 1 db pressure increments.

8. DataCnv for bottles – see above.

9. BottleSum – creates a bottle summary file that includes all sensor data around time of bottle closure.

- Imported the 32 original CTD cast files ("SR2508_S1_CTD01" through "SR2508_S4_CTD17") into the BCO-DMO data processing system.
- Parsed header row from row 12, with commas as delimiter.
- Skipped rows matching "END_DATA" and "DBAR" (units row) strings.
- Captured metadata values from skipped comment rows using regex patterns, creating new columns: STNNBR, CASTNO, DATE, TIME, LATITUDE, LONGITUDE, and DEPTH_BOTTOM.
- Flagged "-9.990e-29" as a missing data value (note that missing data values are empty/blank in the final CSV file).
- Concatenated all 32 files into a single table, adding a new "file_name" column capturing the source filename for each row.
- Renamed columns to comply with BCO-DMO naming conventions.
- Combined DATE (parsed as %Y%m%d) and TIME (parsed as %H%M) columns, both interpreted in UTC, into a new datetime column, ISO_DateTime_UTC, formatted as %Y-%m-%dT%H:%MZ.
- Saved the final file as "1004720_v1_sr2508_ctd_profiles.csv".

NSF Award Abstract:The deep sea, defined as deeper than 200 m, is the largest and least explored habitat on the surface of our planet. It covers nearly two-thirds of the Earth's surface, contains approximately 75% of marine water by volume, and is home to about 55% of all marine microorganisms. Deep-sea microorganisms can play important roles in shaping global chemistry and climate, for example producing and consuming greenhouse gases (e.g., carbon dioxide and nitrous oxide). However, the microbiology of deep-sea waters is understudied relative to that of the surface ocean. Recent data suggests a much more diverse and active microbial community at depth than previously thought, but much remains to be known. For instance, recent estimates suggest that approximately 60% of the microbial species in the deep sea are novel. This project investigates the metabolic activity of deep-sea microorganisms, focusing on chemoautotrophy and the carbon cycle. Chemoautotrophy is a microbial metabolism in which inorganic carbon (e.g., carbon dioxide) is converted to sugar and biomass using chemical energy. This project uses several state-of-the-art sampling and analyses techniques to determine which species conduct chemoautotrophy (who?), what types of chemical energy support it (how?), and at what rate it occurs (how much?) throughout the deep sea. Answering these questions provides insight into deep-sea microbial ecology and quantitative data on the sources and sinks of carbon in deep waters. Results will advance our understanding of the ability of our oceans to sequester carbon over long timescales. This work benefits society through the implications of its findings for our ability to predict and mitigate climate change, as well as its educational mission, which includes training high school, undergraduate, and graduate students in interdisciplinary, climate-relevant science through one-on-one mentorship, hands-on coursework, and the initiation of an annual regional symposium featuring student research.

This project investigates uncultured microorganisms' genetic potential and activity in the mesopelagic and bathypelagic oceanographic layers (200 to 4000 m water depth) to characterize deep-sea microbiology and address a discrepancy in the marine carbon cycle, namely, that respiration rates consistently exceed estimates of vertical inputs of carbon to the dark ocean. Chemoautotrophy may explain at least part of this discrepancy, but known types of chemoautotrophy (e.g., coupled to ammonia and nitrite oxidation) are insufficient to bridge the gap, suggesting novel chemoautotrophs and diverse coupled catabolisms. The overarching hypotheses are that (1) deep-sea microorganisms are more active than currently appreciated, (2) the organic carbon required to support this activity is provided, at least in part, by higher rates of endogenous inorganic carbon fixation, and (3) carbon fixation is performed by more phylogenetically and metabolically diverse chemoautotrophs/mixotrophs than currently known. This study uses high-pressure sampling containers during two deep-sea oceanographic expeditions, metagenomics, metatranscriptomics, and stable-isotope experiments coupled to single-cell isotope analyses via nanoSIMS to (1) quantify microbial anabolic activity in general and chemoautotrophy, mixotrophy, and heterotrophy specifically at bulk and single-cell levels, (2) characterize the diversity and distribution of genes and transcripts involved in chemoautotrophy and heterotrophy, (3) identify novel chemoautotrophs and mixotrophs and quantify their contribution to carbon cycling, and (4) investigate the ability of a major chemoautotrophic deep-sea lineage, the Marine Group I Thaumarchaeota, to utilize organic matter. The results have the potential to reveal novel functions in uncultured microbes and change our understanding of marine carbon cycling.

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.