Table of Contents

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

CTD packages with Niskin rosettes were deployed to 300 meters with the exception of two deep casts: C01 to 2000 meters (where PAR sensor was removed) and C13 to 1000 meters. All deployments began with a 4-5 minute soak at 15m to initialize the pumps and stabilize instrument readings. Casts are identified by two-digit ids preceded by a C, so that C01 is the first cast and C10 is the tenth cast etc.

Data Processing:
Data were converted from .hex files to .cnv files using SeaSave on default parameters. Then, each file was read using the seabird python library (https://github.com/castelao/seabird), and cast latitude, longitude, and deployment time were retrieved. For further calculations, pressure, temperature (primary sensor), conductivity (primary sensor), oxygen (primary sensor), beam attenuation, ECO chlorophyll fluorescence, PAR, corrected PAR, and instrument time were retained. Due to a choppy sea state, data from the upper 5 db were trimmed as the measurements were noisy. Then, all scans from the first 4.5 minutes of the cast were removed as these data were associated with the initializing soak at 15m before profiling. Finally, the upcast was removed to retain the downcast.

Using the python implementation of the Gibbs SeaWater oceanographic toolbox from TEOS-10 (https://www.teos-10.org/pubs/gsw/html/gsw_front_page.html), the following thermodynamic calculations were conducted. A corrected depth (height relative to sea surface, meaning a negative number) was calculated from the pressure and latitude. Then, potential salinity was calculated using conductivity, temperature, and pressure. Absolute salinity was calculated from potential salinity, and conservative temperature was calculated from absolute salinity, temperature, and pressure. Density in terms of sigma-theta was calculated using absolute salinity and conservative temperature. Then, oxygen solubility was calculated using the GSW oxygen solubility function with absolute salinity, conservative temperature, pressure, latitude, and longitude. Oxygen saturation was estimated for each scan using the primary oxygen sensor and the derived oxygen solubility. The outputs for the transformed data for each retained scan are contained in the file [first file]. Then, to remove additional instrument noise and standardize profiles across casts, data were smoothed and interpolated to every 0.5 dbar of pressure with a Nadaraya-Watson kernel estimator using a bandwidth of 5 meters. Using the smoothed and binned outputs, the mixed layer depth was calculated using the criterion of an increase in sigma-theta above 0.125 from 10dbar. Then, the DCM depth was calculated by identifying the depth corresponding to the highest chlorophyll fluorescence below the mixed layer depth. The derived mixed layer and dcm depths, as well as the smoothed and 0.5 dbar binned values for the above mentioned variables are included in the file [file 2].

BCO-DMO Processing:
- replaced "NA" with "nd" to indicate "no data";
- converted date/time field to ISO8601 format;
- removed the "id" field (identical to "cast").

NSF Award Abstract:
Viral infections of marine microbes can transform the fate of microbial populations that fuel global ocean biogeochemical cycles. For example, viral infections of microbes lead to the release of carbon and nutrients back into the environment. This regeneration of carbon and nutrients stimulates the activity of other microbes and diverts carbon and nutrients from larger organisms in marine food webs. Because virus-microbe infections are relatively specific, it is critical to identify those pairs of viruses and microbes that may disproportionally contribute to the turnover of carbon and nutrients in the ocean. This project will develop quantitative approaches and tools to quantify which viruses infect which microbes and to use these data to quantify how viral infections of microbes collectively shape nutrient and carbon cycles in the North Atlantic Ocean. The project will analyze virus-microbe interactions in mesocosms at the Bigelow Laboratory for Ocean Sciences in mid-coast Maine and during open ocean expeditions to the Bermuda Atlantic Time-Series Study (BATS) site. An interdisciplinary team will leverage recent advances in molecular biology, computational biology, and mathematical modeling to identify virus-host partners and their impact on the movement of elements through marine systems. This project will support three graduate students, six undergraduate students and one postdoctoral researcher in an interdisciplinary context. Research advances will be translated into reproducible software methods to be disseminated via the community cyberinfrastructure platform iVirus, with additional training materials presented as part of a viral methods and informatics workshop held at The Ohio State University. The translation of discoveries to the public will be furthered by the involvement of journalism undergraduate students at the University of Tennessee-Knoxville.

This project builds upon advances in the molecular toolkit of viromics to develop an integrated approach to characterize lineage-specific rates of infection, lysis, and nutrient release induced by marine viruses in open ocean ecosystems. It will combine theory, in vitro experiments, and in situ sampling to (i) extend a robust inference method for estimating virus-microbe cross-infection networks from time-series data; (ii) establish and characterize in-vitro protocols for inferring cross-infectivity in complex communities using culture-independent methods; (iii) estimate lineage-specific rates of lysis and regeneration of nutrients in marine systems, including applications to coastal and open ocean ecosystems. Project aims focus on quantifying the extent to which virus-induced lysis and regeneration of carbon and nutrients is heterogeneously distributed across microbial populations. To do so, the project will incorporate time series measurements of abundance information (via metagenomes) and activity information (via metatranscriptomes). In so doing, it will advance efforts to understand community-scale interactions rather than those amongst a single virus-host pair. Theoretical methods and in vitro protocols will directly infer lineage-specific infection, lysis, and nutrient release rates in coastal- and open-ocean ecosystems in the North Atlantic Ocean. Results will be used to identify key links that disproportionately influence bulk nutrient release. A novel PCR-based approach will augment and validate the core inference approach. Overall, the project aims to enhance our understanding of how viruses contribute to marine ecosystem function.

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.