Table of Contents

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

Data from a related experiment (experiment 2, residence time and irradiance) on Saccharina latissima is available through BCO-DMO at https://www.bco-dmo.org/dataset/922819.

Methodology summary: The experiment in aquaria measured changes in dissolved oxygen, pH, and total alkalinity, and derived resultant changes to dissolved inorganic carbon (DIC) and calcium carbonate saturation state (Ω).

Values of temperature, salinity, oxygen and pH were recorded in all the chambers using a multiparameter meter (HQ40D, Hach Lange) calibrated before measurements with TRIS buffer, from A. Dickson laboratory, with an accuracy of 0.01 pH units. Discrete water samples were acquired from three representative chambers from each CO₂ level per species for analysis of total alkalinity (AT). Seawater AT was measured using open-cell titration with triplicate samples (Metrohm 855 Robotic Titrosampler, Metrohm, USA) using 0.1 N HCl (Fisher Chemical) diluted to a nominal concentration of 0.0125 M. Acid was calibrated by analyzing Certified Reference Material (CRM Batch 138) from A. Dickson’s laboratory. For each set of triplicate analyses, the median value was considered. Instrumental precision was within 5 µmol kg -1.

See detailed methodology described in the manuscript: Optimizing marine macrophyte capacity to locally ameliorate ocean acidification under variable light and flow regimes: Insights from an experimental approach (Ricart, A. M. et al. 2023).

DIC and Ω, as aragonite saturation state, were calculated from pH and AT.

Carbonate system calculations were performed using the seacarb R package and assuming published values for constants K1 and K2, KF, and KS. Uncertainties of the derived parameters (DIC, pCO2, and Ω) were quantified using a Monte Carlo analysis (100 simulations). For each simulation, normally distributed errors were introduced into pH (± 0.01) and AT (± 5 μmol kg−1). The overall uncertainties of the derived parameters were calculated as one standard deviation of the simulations. On average, uncertainties for DIC were 0.28 %, for pCO2 were 2.5 % and for Ω 0.01 %. For pCO2, uncertainty is higher at lower pCO2, whereas uncertainty is lower for Ω at lower Ω. The uncertainty for DIC was similar to the uncertainty in AT, that is ± 5 μmol kg−1.

Loaded the submitted file data_to_publish_exp1.csv into Laminar (BCO-DMO data file processor)

The first column of the submitted dataset file, data_to_publish_exp1.csv, did not have a parameter name, and it stood for the row number of each line of the file. Removed this parameter column from the final dataset since a spreadsheet viewer will show the row numbers.

Removed units from the parameter names since these units will be noted in the parameters section of the dataset page.

Replaced NA values with blanks in the dry_weight column.

Renamed Ulva to Ulva lactuca to match the pattern of the other species entries in the dataset.

Renamed Z.marina to Zostera marina to match the format of the other species entries in the dataset.

Joined a metadata table created by the data manager to the submitted dataset on the parameter name Species to include metadata in the primary dataset file. The metadata table has columns of Species, lat, lon, date_start, date_end.

Reordered the parameters so that the metadata is at the front of the dataset.

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Checked taxonomy of dataset.

Checked that all the species names in the dataset file matched those found in WoRMS.

Created a Species WoRMS taxonomy file species_list_experiment_1.csv by using the WoRMS website to create a table of the species name with the following columns: ScientificName, AphiaID, LSID, Authority, Kingdom, Phylum, Class, Order, Family, Genus, Species.

NSF Award Abstract:

Bigelow Laboratory for Ocean Sciences, in West Boothbay Harbor - Maine, plans to implement an REU site that will support 10 students each year, for the next 5 years. This REU program will combine group learning and guided individual research to help students address societal issues concerning the oceans. The goals of this REU Program are i) to provide undergraduate students from around the United States mentoring and access to high quality, hands on research opportunities in Oceanography and the opportunity to understand its interdisciplinary nature, ii) improve the capability and confidence of students to learn independently, iii) help to prepare undergraduates for their professional careers, and iv) increase the participation of underrepresented minorities in marine science careers. REU students will be incorporated into research groups consisting of technicians, post-docs, and junior and senior scientists, gaining exposure to the suite of activities and personalities involved in a science career. The recruitment goal is to engage students from all groups underrepresented in ocean sciences, such that cohorts are ~ 40% underrepresented students (including 1st generation college students). To achieve the recruitment goals, the principal investigator will work with partner organizations, like the Institute for Broadening Participation and Maine Community College System. Program content and delivery will continually be refined based on feedback from students and mentors in the form of pre-program, midpoint and final evaluations.

As a group, students will participate in a sampling cruise on the local estuary, and attend weekly meetings to learn the fundamentals of the scientific process, such as how to form testable hypotheses, critically evaluate data, and present information in a scientific manner to their peers and to the public. Students will attend an ethics in science discussion, a laboratory safety course with risk assessment training and a concept mapping workshop during the early stages of their project. Students participate in and become familiar with public outreach through attendance at Bigelow's weekly Café Scientifique talks (for the general public), participation in the Lab's Open House and frequent public tours.

Continuing Award