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 1, comparison among species) is available through BCO-DMO at https://www.bco-dmo.org/dataset/922818.

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 and oxygen were measured using a multiparameter meter (HQ40D, Hach Lange). Discrete water samples were acquired from each tank for analysis of pH and total alkalinity (AT) that were run the same day of the experiment. Seawater pH of the discrete water samples was determined on the total scale as per Dickson et al. 2007 with a high-precision spectrophotometer (Agilent Cary 8454 with PCB 1500 Water Peliter System) using unpurified m-cresol purple dye (Alfa Aesar A180025-06). Water samples were kept in a temperature-controlled water bath at 20°C before analysis, and during analysis using a thermostatic cell holder, to minimize temperature-induced errors in absorbance measurements. The spectrophotometer was validated by analyzing TRIS buffer revealing that the system was accurate to within 0.005 pH units. Seawater AT was measured using a CONTROS HydroFIA TA® instrument (4H-Jena GmbH, Jena Germany), which performed a single-point titration of seawater with 0.1N HCl, using bromocresol green as the indicator for spectrophotometric pH detection. HCl titrant was calibrated with Certified Reference Material (Batch 172) from A. Dickson’s laboratory. 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_exp2.csv into Laminar (BCO-DMO data file processor)

The first column of the submitted dataset file, data_to_publish_exp2.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.

Replaced periods with underscores in the parameter names to follow BCO-DMO parameter naming guidelines.

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

Replaced NA values with blanks in the Inflow_pH, delta_DIC, delta_pH, and delta_omega_ar columns.

Added a Species parameter value with ‘Saccharina latissima’ and ‘Control’ whenever the row value of Kelp_Control is ‘Control’. This is to join on the parameter Species in a data manager created metadata table with the columns of Species, and lat, lon.

Joined a metadata table created by the data manager to the submitted dataset on the parameter Species to include metadata in the primary dataset file.

Converted the date format to the ISO 8601 format %Y-%m-%d

Reordered the parameters so 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_2.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