Table of Contents

• Coverage
• Dataset Description
  • Methods & Sampling
  • Data Processing Description
  • BCO-DMO Processing Description
  • Problem Description
• Related Publications
• Parameters
• Instruments
• Deployments
• Project Information
• Funding

Methods + Sampling:

Shipboard Protocol:

Whole water samples of either 13mL or 45mL were collected in 15mL or 50mL Falcon tubes, respectively, on deck at the rosette. Samples were fixed by adding borate-buffered formaldehyde (2% final concen.) and stored at 4 °C.

Laboratory Protocol:

Storage: Samples were stored at 4°C before processing.

Sample Processing: Black-stained (Millipore Sigma) polycarbonate membrane filters (0.2 µm pore size, 25 mm diameter) were washed with dd-H2­O then briefly dipped into very dilute Triton X-100 detergent for better cell dispersion (range between 0­.001-0.01%). Washed membranes were placed on top of moistened glass fiber backing filters (Whatman GF/C) on the filtration base and funnel was secured. 14-16mL of sample was filtered, vacuum was applied until approx. 2 mL of the sample remained in funnel. Samples were then stained with DAPI (1µg/ml final concen.) and incubated for 5 min. The remaining 2mL of stained sample was passed through the filter and rinsed with ~5mL distilled water. Filters were dried for >15 minutes at room temperature. Filters were mounted on slides with 4:1 Citifluor:Vectashield. Before enumeration, slides were stored at -20 °C. Separate reagent blanks were prepared during each filtration session.

Slide Enumeration: At least 10 grids and >300 cells were enumerated per filter to minimize analytical error (Kirchman et al., 1982). Individual fields/grids were randomly selected along north-south and east-west transects before viewing to minimize operator bias. Manual counting and statistical calculations were facilitated by our NewCount macro within Excel which, once initialized, transforms a computer keyboard into blind data entry portal that tallies a single count from any keystroke (except two control keys), recognizes end of a single field count and tabulates cell concentrations, S.D., S.E., C.O.V. and 95% confidence limits once designated number of fields is counted (developed by G. Taylor and D. Zheng; available upon request). Cells/L were calculated by using the following formula, where dilution factor compensates for the volume of formaldehyde fixative, and multiplication factor is the constant required to convert average grid/field count to the total count for the entire filter area exposed to sample: (((adjusted mean cells per grid)/(dilution factor*mL filtered))*multiplication factor)*1000 = cells/L. Coefficient of variation was calculated using the following formula: (standard error(cells/L)*100)/average(cells/L)=CoV. Total prokaryotic counts were corrected for storage decay between sample collection and filter preparation via the following exponential decay curve: Ncorr=Nobs/e-0.000605(ts-tc), where Ncor is the corrected cell abundance at the time of sample collection, Nobs is the observed cell abundance after sample preparation, ts is date of sample preparation, and tc is date of sample collection. Raw cell count data available from N. Butkevich or G. Taylor by request. The correction factor is based on empirical observations of stored samples from the CARIACO time series. Details are available within Scranton and Taylor (2019) BCO-DMO repository metadata.

Total prokaryotic counts were corrected for storage decay between sample collection and filter preparation via the following exponential decay curve: Ncorr=Nobs/e-0.000605(ts-tc), where Ncor is the corrected cell abundance at the time of sample collection, Nobs is the observed cell abundance after sample preparation, ts is date of sample preparation, and tc is date of sample collection. Raw cell count data available from N. Butkevich or G. Taylor by request. The correction factor is based on empirical observations of stored samples from the CARIACO time series. Details are available within Scranton and Taylor (2019) BCO-DMO repository metadata.

Curation Actions Performed on Data
- Loaded ENTP_Prokaryotic_Census_FINAL_nb.xlsx (sheet 1) as table 1005974_v1_ETNP_OMZ_AT50_Prokaryoplankton_Cell_Counts, using xlsx preserve_formatting enabled, floating point error adjustment enabled, header row 1, empty strings and "nd" set as missing values
- Combined columns "Cast Date" (format %m/%d/%y) and "Cast Time (UTC)" (format %H:%M:%S), interpreted as UTC, into new datetime column ISO_Cast_Start_DateTime_UTC formatted as %Y-%m-%dT%H:%M:%SZ
- Reformatted column "Cast Date" (format %m/%d/%y) into date column output as %Y-%m-%d, keeping the same column name
- Renamed columns: "CTD Cast filename" to CTD_Cast_filename, "Cast Date" to Cast_Date, "Cast Time (UTC)" to Cast_Time_UTC, "Average cells/L" to Average_cells_per_L, "Standard deviation" to Standard_deviation, "Standard error" to Standard_error, "Coefficient of Variation (percent)" to Coefficient_of_Variation_percent, "Grids counted" to Grids_counted
- Reordered columns to: Depth, Station, Lat, Long, CTD_Cast_filename, ISO_Cast_Start_DateTime_UTC, Cast_Date, Cast_Time_UTC, Average_cells_per_L, Standard_deviation, Standard_error, Coefficient_of_Variation_percent, Grids_counted
- Set column types and formats: Average_cells_per_L as number (scientific notation output), CTD_Cast_filename as string, Cast_Date as date (%Y-%m-%d), Cast_Time_UTC as time (%H:%M:%S), Coefficient_of_Variation_percent as number, Depth as number, Grids_counted as integer, ISO_Cast_Start_DateTime_UTC as datetime (%Y-%m-%dT%H:%M:%SZ), Lat as number, Long as number, Standard_deviation as number (scientific notation output), Standard_error as number (scientific notation output), Station as string
- Updated column metadata with descriptions, standard name IDs, supplied units, and primary parameter flags for all columns, including calculation formulas for Average_cells_per_L, Coefficient_of_Variation_percent, Standard_deviation, and Standard_error
- Dumped final table to CSV output, with unique lat/lon extraction enabled and pipeline specification saved

Curation Actions Performed on Metadata
- Standard metadata entry and text formatting steps were performed.

NSF Award Abstract:

Oxygen availability shapes the distributions and activities of marine organisms. Ongoing human activities and climate change are expected to lead to expansion and intensification of already large oxygen-stressed areas of the coastal and open ocean. Decreases in ocean oxygen have significant ecological consequences, including habitat loss for migratory and bottom-dwelling organisms, modification of the marine food web, and production of trace gases with pronounced feedbacks on climate, such as methane and nitrous oxide. Intense chemical cycling by microorganisms occurs in oxygen-depleted marine habitats. However, a full understanding of the consequences for marine ecosystems is hampered by limited knowledge of actual rates of key microbiological processes and dynamics of the microorganisms mediating them. This study combines novel methods and sampling techniques to understand how these processes are influenced by changes in oxygen concentration to inform predictions of important chemical exchanges within a changing ocean and its production of climate-active gases. This deeply collaborative project trains undergraduates (four of whom participate on the cruise), a graduate student and a postdoctoral fellow. Outreach takes place in middle and high schools and through social media. Data and samples from the cruise are integrated in coursework.

Oxygen depletion alters cycling of major elements (especially carbon, nitrogen, and sulfur) as well as food web functionality. This project addresses major gaps in our knowledge of oxygen minimum zone (OMZ) processes by applying in situ approaches to more accurately measure rates of several key microbial processes (chemoautotrophy, denitrification, anammox, sulfate reduction and sulfide oxidation) central to marine biogeochemical cycling. This work studies the Eastern Tropical North Pacific OMZ, the largest open ocean oxygen-depleted system, to 1) determine the in situ rates of microbial processes involved in carbon, nitrogen, and sulfur cycling, 2) reveal the genomic blueprint of active single cells involved in these processes, and 3) obtain estimates of the relative contributions of the dominant chemoautotrophic and heterotrophic groups to the measured rates. This work include applies cutting-edge equipment for in situ sampling and incubations that minimize artifacts associated with traditional water sampling approaches, allowing more accurate estimates of rates of important biogeochemical processes. Additionally, rate measurements of relatively undisturbed bulk and fractionated water samples make it easier to distinguish the potential role of particle-associated microorganisms in these OMZ processes. Single cell sorting of microorganisms using a fluorescent dye indicative of cell activity together with metatranscriptomics informs on metabolic pathways used for key processes by active microbial community members, as well as the potential coupling of chemoautotrophy and nitrogen or/and sulfur cycling. By combining stable isotope probing, fluorescence in situ hybridization and single cell Raman microspectrometry the relative activity levels of different microbial phylotypes involved in chemoautotrophic and heterotrophic elemental cycling are assessed.

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.