Table of Contents

• Coverage
• Dataset Description
  • Methods & Sampling
  • Data Processing Description
• Data Files
• Related Publications
• Related Datasets
• Parameters
• Instruments
• Deployments
• Project Information
• Funding

POM concentrations for carbon, nitrogen, phosphorus, and chemical oxygen from GO-SHIP Line P18 Legs 1 and 2 in 2016 and 2017.

These data will be published in Moreno et al. (in press).

POM sample collection

General equipment preparation in the lab before shipment included an HCl bath (1.0 M HCl overnight) and milli-Q rinse for the 8 L carboys, tubing, and filter holders. Additionally, the carboys were autoclaved. The 25 mm, 0.7 µm GF/F filters and aluminum foil used to wrap the filters were combusted (500 °C for 5 hours) in aluminum foil packets to remove any traces of carbon present. The forceps that came in contact with the samples were wiped with 70% ethanol before and between uses.
Seawater for the POM samples was collected from the onboard flow through underway system. The underway intake was located off the bow of the ship at a depth of approximately 5.3 m from the sea surface and the length of the pipe from the intake location to the output lab was 11.8 m. A 30 µm nylon mesh pre-filter was attached to the underway outlet for all standard samples to remove large plankton and particulates. Before sampling, the carboys used were rinsed twice with the pre-filtered underway seawater. Triplicate sampling occurred roughly at four-hour intervals with a shift forward of one hour each day. For example, if samples were taken at 01:00, 05:00, and 09:00 on one day, samples would be taken at 02:00, 06:00, and 10:00 the following day to avoid any diurnal bias. The water was vacuum filtered through combusted GF/F filters and the volume of seawater filtered was determined on a per station basis, ranging from 3-8 L. The volume was raised if the previous stations’ filtration times exhibited a decreasing trend and lowered if filtration time exhibited an increasing trend in an attempt to normalize the amount of collected material. The large sampling volume and initial rinsing steps limit the effect of a time delay from underway inlet to sampling station. Additional “total POM” samples were taken in the Southern Ocean by removing the 30 µm pre-filter during the rinse and sample collection steps. After filtration, all POP triplicates were rinsed with approximately 2-5 mL of a 0.17 M Na2SO4 solution to remove dissolved phosphorus. All POM samples were folded in half with the top sides toward each other, sealed inside pieces of combusted aluminum foil, and stored in a -20 C freezer until analysis.

POP assay

The POP data were obtained using an ash/hydrolysis method and comparing the samples to a set of standard phosphorus concentrations (Lomas et al., 2010). The sample filters were unfolded and placed face up into acid-bathed and combusted scintillation vials. Along with each set of samples, 10 different volumes (ranging 0 - 0.5 mL) of 0.1 M KH2PO4 solution were added to scintillation vials. 2 mL of a 0.017 M MgSO4 drying solution was added to each scintillation vial and then all vials were placed into an 80-90 °C oven overnight to dry. After drying, the vials were heated at 500 °C for 2 hours, then left to cool before adding 5 mL of 0.2 M HCl to each vial and being returned to the 80-90 °C oven for 30 minutes after being brought up to temperature. The solutions were then transferred to 15 mL glass centrifuge tubes (prepared in the same way as the scintillation vials). The sample vials were rinsed with 5 mL of milli-Q each, which was also added to the centrifuge tubes. 1 mL of a mixed reagent containing 2:5:1:2 parts Ammonium Molybdate ((NH4)6Mo7O24), 5.0 N H2SO4, Potassium Antimonyl Tartrate (C8H4K2O12Sb2), and Ascorbic Acid (C6H8O6) respectively was added to each centrifuge tube in 30-second intervals. Each of the sample tubes was centrifuged to isolate any glass fibers that could interfere with the absorbance reading. Lastly, after allowing the mixed reagent to react for exactly 30 min, the standards and samples were analyzed in 30-second intervals in a spectrophotometer at an 885 nm wavelength using a blank of ~0.1 M HCl solution and rinsing the cuvette with the blank solution between measurements.

POC/PON assay

POC and PON measurements were analyzed both in-lab at UCI and at the UC Santa Barbara Marine Science Institute Analytical Lab. An ANOVA analysis determined that the two methods did not produce significantly different results. The preparation for all samples was the same; the samples were each removed from their foil packets and placed into acid-bathed and combusted scintillation vials and dried in a 55 °C oven overnight. The scintillation vials were then placed in a desiccator containing a beaker of 12 M HCl overnight before being dried at 55 °C at least overnight once more. Samples sent to UCSB were then capped and shipped to the lab. Samples analyzed at UCI were packed into tin packets alongside Atropine (C17H23NO3) standards (ranging 0.2-1.5 mg) and measured using a Flash EA elemental analyzer.

PCOD assay

Particulate chemical oxygen demand was quantified using a modified assay for sea water (Moreno et al. 2020). GF/F filters for PCOD were dried at 55°C overnight, before oxidizing the filters plus 2ml milli-Q in HACH COD HR+ reagent vials (Product # 241915) at 150°C for 2 h. Mercuric sulfate was added to reagent vials mixture to prevent chloride ion interference. Next, silver chloride was precipitated out with an additional 92.1 μL of 9.5 M NaCl for consistent precipitation. Precipitate was removed by centrifuging for 30 min at 2500 rpm. The residual potassium dichromate was quantified by absorbance at 600 nm against HACH certified phthalate-based COD standards.

Note about data columns: Rep 1-6 indicate replicates collected separately at same timepoint.

Associated CLIVAR P18 underway and bottle datasets can be found on the National Centers for Environmental Information (NCEI) CLIVAR Repeat Section P18 page: https://www.nodc.noaa.gov/ocads/oceans/RepeatSections/clivar_p18.html

BCO-DMO Data Manager Processing Notes:
* Data submitted as Excel file P18-POM.xlsx extracted to csv file.
* added a conventional header with dataset name, PI name, version date
* modified parameter names to conform with BCO-DMO naming conventions (spaces, +, and - changed to underscores).  Units in parentheses removed and added to Parameter Description metadata section.
* blank values in this dataset are displayed as "nd" for "no data."  nd is the default missing data identifier in the BCO-DMO system.
* asterisk removed from Volume values for samples P18-134 and  P18-136.  Indicated additional notes taken (not provided).
* Timestamp converted to ISO 8601 format yyyy-mm-ddTHH:MMZ

NSF Award Abstract:
Due to their sheer abundance and high activity, microorganisms have the potential to greatly influence how ecosystems are affected by changes in their environment. However, descriptions of microbial physiology and diversity are local and highly complex and thus rarely considered in Earth System Models. Thus, the researchers focus on a convergence research framework that can qualitatively and quantitatively integrate eco-evolutionary changes in microorganisms with global biogeochemistry. Here, the investigators will develop an approach that integrates the knowledge and tools of biologists, mathematicians, engineers, and geoscientists to understand the link between the ocean nutrient and carbon cycles. The integration of data and knowledge from diverse fields will provide a robust, biologically rich, and computationally efficient prediction for the variation in plankton resource requirements and the biogeochemical implications, addressing a fundamental challenge in ocean science. In addition, the project can serve as a road map for many other research groups facing a similar lack of convergence between biology and geoscience.

Traditionally, the cellular elemental ratios of Carbon, Nitrogen, and Phosphorus (C:N:P) of marine communities have been considered static at Redfield proportions but recent studies have demonstrated strong latitudinal variation. Such regional variation may have large - but poorly constrained - implications for marine biodiversity, biogeochemical functioning, and atmospheric carbon dioxide levels. As such, variations in ocean community C:N:P may represent an important biological feedback. Here, the investigators propose a convergence research framework integrating cellular and ecological processes controlling microbial resource allocations with an Earth System model. The approach combines culture experiments and omics measurements to provide a molecular understanding of cellular resource allocations. Using a mathematical framework of increasing complexity describing communicating, moving demes, the team will quantify the extent to which local mixing, environmental heterogeneity and evolution lead to systematic deviations in plankton resource allocations and C:N:P. Optimization tools from engineering science will be used to facilitate the quantitative integration of models and observations across a range of scales and complexity levels. Finally, global ocean modeling will enable understanding of how plankton resource use impacts Earth System processes. By integrating data and knowledge across fields, scales and complexity, the investigators will develop a robust link between variation in plankton C:N:P and global biogeochemical cycles.