Experiment Overview:
The effect of strontium (Sr) on the coccolithophore Scyphosphaera apsteinii calcification was assessed over a 10 d period. This species of coccolithophore has unusually high levels of Sr in its calcite coccoliths as detected with Energy-dispersive X-ray spectroscopy (EDS), whereas Si levels are undetectable with EDS. The goal of the experiment was to determine whether Sr in seawater plays a significant role in coccolith production and/or coccolith crystal morphology. S. apsteinii was acclimated and grown in a range of Sr concentrations (deplete: 0.33 mmol/mol Sr/Ca, ambient: 9 mmol/mol Sr/Ca, and higher than ambient: 36 and 72 mmol/mol Sr/Ca). All treatments had four replicate flasks. Aliquots of cultures for cell counts and Fv/Fm were taken every two days between the start (T0 for cell counts, T4 for Fv/Fm) and end (T10) of the experiment. When cells were at mid-exponential phase (T4-T6) aliquots were collected for scanning electron microscopy (SEM) and EDS analysis to observe morphology and determine Sr incorporation into calcite coccoliths, respectively.

The laboratory experiments were conducted in March 2019 at the University of North Carolina - Wilmington. SEM/EDS analysis was done at the Analytical Instrumentation Facility at NC State from April 19th to May 9th, 2019.

Scanning Electron Microscopy (SEM) and Energy-dispersive X-ray Spectroscopy (EDS):
For EDS analysis, 1-3 mL of culture were filtered onto 13 mm 0.4 um isopore filters (Merck Millipore Ltd.) and rinsed with Nanopure water buffered to pH 8.0 with 1 mM HEPES to remove salts. Filters were air-dried and mounted onto a SEM stub with carbon adhesive tabs before coating with 10 nm Pt/Pd. EDS analysis was performed at North Carolina State University (FEI Verios 460L SEM, with an Oxford Xmax silicon drift EDS detector and AZtec acquisition and analysis software). A minimum of 500,000 counts were collected, between 2,000 – 8,000 cps with an average deadtime < 5%. Standardless quantification was used to determine atomic % and weight % for each element.

sr_morphology.csv