Table of Contents

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

Sampling at the sediment-water interface was carried out using a benthic lander called Susane built at IFREMER by Joel Knoery (Knoery et al., 2019). It was deployed using a 0.322 cable from the port side squirt boom on the Oceanus. The lander was deployed at the seafloor and syringes sampled water at 10-centimeter (cm) intervals while it sat on the seafloor. Transfer of sampled water to the analytical system is described below.

Water column samples were collected using a Seabird Rosette equipped with an SBE50 pressure sensor and an autofire module. It was pre-programmed and deployed on amsteel cable and fired at select depths). Bottles were 5 liter (L) Niskin-style acquired from Ocean Test Equipment. They were teflon-coated and had external teflon-coated springs.

All iron (Fe) samples were filtered using Pall Gelman Supor 0.45 micrometer (μm) polyethersulfone filters with either Millipore Swinnex polypropylene 25-millimeter (mm) filter holders or Advantec-MFS type PP47 47 mm polypropylene inline filter holders, as recommended by the GEOTRACES Cookbook version 3.0 (Cutter et al., 2017). Nitrogen (N2) gas was used to pressurize the Go-Flo bottles during filtration. Filtered fractions for Fe(II) measurement were transferred to a syringe using a three-way Luer-lock adaptor to prevent the introduction of air, then measured immediately. Fe(II) was measured via chemiluminescence with luminol, consisting of a continuous 2 milliliters per minute (mL min-1) flow of sample and luminol solution at a 1:1 ratio into a standard quartz flow cell with a Hamamatsu HC135 photon counter via a peristaltic pump. The signal value for each sample was determined as the mean of the signal for 30 seconds (n=50), once the signal reached a plateau. Because luminol chemiluminescence is not selective for Fe(II), each sample was also treated with diethylenetriamine pentaacetate (DTPA), a selective Fe(II) chelator used as a masking ligand. The DTPA-treated samples, with a final concentration of 0.5 millimolar (mM) DTPA, serve to correct for chemiluminescence caused by compounds besides Fe(II). DTPA-treated samples were processed with the exact same analytical train as untreated Fe(II) samples. The order of sample measurement was randomized to prevent systematic error due to sample oxidation. Fe(II) calibration was performed each time the system was powered on and calibration curves consisted of six or more concentrations within the appropriate working range of the measured Fe(II). These concentrations were created by spiking a seawater solution that aged for at least 24 hours in an amber bottle with an appropriate volume of 1 micromole (μM) Fe(II) working stock in milliQ water. This working stock was created fresh before calibration from a 0.01 mole (M) Fe(II) standard solution at pH 2, prepared monthly by dissolving Optima grade hydrochloric acid (Fisher) and ammonium ferrous sulfate (Fluka) in milliQ water. Luminol solutions were prepared first using a stock solution with 0.796 grams (g) of sodium luminol (Sigma), 250 mL of Optima grade ammonium hydroxide (Fisher), approximately 45 mL of Optima grade hydrochloric acid (Fisher), and milliQ water. The working luminol reagent was produced by diluting this stock to one-fourth of its starting concentration, then heating it at 50º Celsius for 9 to 12 hours. The DTPA solution was created by diluting 2.4584 g of DTPA (Millipore-Sigma) with sodium hydroxide (Aldrich, trace metal basis) in milliQ water for a final concentration of 50 mM DTPA and 200 mM NaOH. Additional details of this method including reagent preparation, instrumental settings, and procedures have been previously reported (Bolster et al., 2018).

Total dissolved Fe (dFe) samples were collected into 500 mL LDPE bottles. Within one month of collection, these samples were acidified to a pH of approximately 1.7 by adding 1 mL of hydrochloric acid (Optima, Fisher Scientific) per 500 mL of seawater. After one year of storage, samples were prepared in triplicate using the seaFAST-pico (Elemental Scientific) offline method, where 10 mL of acidified sample was added to a Nobias resin chelation column and then eluted with ultra-pure, distilled 5% nitric acid (Optima, Fisher Scientific) for a final volume of 0.5 mL. This method is similar to the method described in Jackson et al. (2018) and Rapp et al. (2017). Fe concentrations were quantified with a Finnegan Element 2 (Thermo Scientific) Inductively Coupled Plasma-Mass Spectrometer and Apex desolvation system in medium resolution. A 1 part per billion (ppb) indium eluent is used during sample preparation as an internal standard to correct for instrument drift. Instrument optimization and tuning are performed daily with a 1 ppb indium and uranium tuning solution. Procedural blanks were prepared in triplicate from pH 1.7 hydrochloric acid to correct for contamination during acidification of samples. Sample concentration of Fe was determined via the isotopic dilution method in which acidified samples were spiked with a multi-element standard, including 57Fe, enriching it over the natural isotopic abundances.

Oxygen (O2) concentrations from the benthic boundary gradient sampler were measured less than an hour from recovery using a Presens TX-3 microoptode in a flow cell fitted to the sampling syringe outlets. Between each O2 measurement, brief flushes of nitrogen gas were also used to check for calibration shifts and remove contamination between samples. The order of sample measurement was randomized to reduce the influence of any contamination post-recovery.

Data Processing:
MATLAB R2018B (The MathWorks, Inc., 2018) was used to read in and average signal values for Fe(II) measurement. The calibration curve for Fe(II) using this method follows a second-order polynomial, so the "nllsqr" function (Glover et al., 2011) was used to fit this data. Sample concentrations were calculated by first subtracting the DTPA signal and then applying the "vpasolve" command with the given calibration curve. The uncertainty in measured Fe(II) concentrations was calculated using the standard error of the signal plateau (n=50). For Fe(II) samples measured in duplicate, the uncertainty consists of this standard error and the standard deviation of the two measurements added in quadrature.

- Imported the original Excel file "Processed Fe2 data_OC2107A.xlsx" into the BCO-DMO system.
- Removed 'NaN' as the missing data identifier (missing values are blank in the final CSV file).
- Separated the Cruise ID from the "Fe Only" column.
- Renamed fields to comply with BCO-DMO naming conventions.
- PI Moffett provided a revised file "fe2_oc2107a_with dates.csv" including dates.
- Converted the Date field to YYYY-MM-DD format.
- Changed years of "2023" to "2021".
- PI Moffett provided a revised file "894761_v1_benthic_iron_oregon_AF.csv", which included additional dissolved Fe data.
- Removed 'N/A' as the missing data identifier (missing values are blank in the final CSV file).
- Saved the final file as "894761_v1_benthic_iron_oregon.csv".

NSF Award Abstract:
The boundary between productive coastal waters and relatively non-productive offshore waters is not a simple function of distance from the coast, but is determined by a complex interplay between biology, chemistry, and ocean physics. This interplay is a fundamental property that controls the oceanic contribution to the food supply and the global carbon cycle. During summer months when waters are warmer with low oxygen, biological decomposition near the seafloor consumes available oxygen and releases iron from sediments into overlying seawater. In deeper parts of the ocean, canyons and other rugged surface features influence currents and create turbulence that rapidly moves iron from the shelf offshore. This iron in turn can enhance biological productivity miles away. This project will investigate (1) how decomposition processes on the continental shelf seafloor release elements like iron required for ocean life and (2) how ocean currents interact with the continental shelf and slope to move waters overlying the shelf offshore to enhance productivity. Based on model simulations from the California and Oregon coasts done over 20 years that show transport of iron via plumes from the shelf to the open ocean, scientists will collect and analyze samples for iron and iodine to prove the findings of the model. Iodine has been included in the study because it can track inputs from low oxygen sediments to the shelf. In addition, results from the study will be used to improve assumptions used in the current model. The project will support the research in whole or in part of four graduate students and several undergraduate students. The scientists are involved with High School student mentoring, through Project COOL (Chemical Oceanography Outside the Lab) and the Students on Ice Foundation.

Scientists from the University of Southern California and the University of California, Los Angeles will study iron (Fe) and iodine (I) geochemistry along the Washington and Oregon Coasts, where high organic matter oxidation rates, low dissolved oxygen concentrations, and high sedimentary Fe fluxes on the continental shelf occur. This project hypothesizes that a shelf-to-basin shuttle controls the supply of Fe from the Fe-rich shelf into the interior of the North Pacific Ocean. Simulations of a Regional Oceanic Modeling System (ROMS) coupled with the Biogeochemical Elemental Cycling model (BEC) run between 2007-2017 showed that this coastline is a major source of Fe to the ocean basin, exhibiting both deep and shallow Fe plumes that arise from subsurface eddies generated by poleward undercurrents. Results from this model will be used to predict how the distribution of Fe evolves seasonally and guide sampling during two cruises in 2021 to the region. According to the ROMS-BEC model, the Fe inventory is highest in late summer, when bottom water oxygen is lowest, and the inventory is lowest in winter and early spring. Model-generated deep plumes resemble those reported off Namibia, Peru and the Gulf of Alaska. This work will sample depths up to 4500m and look for such plumes. Deep plumes are important in global Fe budgets and because they may outcrop in high latitude waters that are Fe limited. Iodine will also be measured because, like Fe, it accumulates at the sediment water interface and is released under reducing conditions. Plumes of iodine arising from shelf sediments will be used as a semi-conservative tracer for lateral Fe advection. The cruises will also assess the relative importance of direct inputs from rivers (especially the Columbia River) versus reducing sediments, since these inputs are decoupled seasonally

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.