| A D A G I O |
| (AciDification effects of AGgregation In the Ocean) |
2010 Chemostat Experiment
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Set up with CO2 controlled chemostats at the Alfred Wegener Institute. |
In January through March, 2010, we grew phytoplankton in controlled chemostats, and then measured aggregate formation in roller tables (Fig. 1).
Chemostat Experiment Participants Chemostat Data
Hypothesis 1: Gel particles enhance aggregate formation. The production of gel particles increases with ocean acidification, and thus export increases.
Hypothesis 2: Biomineral ballast (particularly calcium carbonate) is an important factor in carbon export in the ocean. Lower pH will decrease ballast-particle interactions, and export consequently decreases.
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| Fig. 1. Schematic of chemostat and mesocosm experimental set-ups. |
Chemostat experiments with Emiliania huxleyi were conducted at naturally low phytoplankton cell abundances (<105 ml-1, Lampert et al. 2002) to prevent unrealistic effects of biological processes on the seawater carbonate system and to allow for a better control of pH. To describe changes in the seawater carbonate system due to biogenic calcification, three variables of the carbonate system, i.e., pH, DIC and total alkalinity, were determined during all experiments.
Acidification effects were investigated in the chemostats at 180, 380, and 750 ppm CO2 partial pressure. Three chemostats (180ppm, 380ppm, 750ppm) were operated at a temperature of 10°C. The flow rate was set at 0.1 d-1, because we previously observed high rates of calcification and gel particle formation at this low growth rate. Chemostats were sampled three times within a 3-week period. Samples will be taken for parameters as described in Table 1. The pH and temperature in the chemostats were continuously monitored during the experiment by means of pH and temperature electrodes coupled with data logger units. On each sampling occasion, additional samples were taken to conduct roller table experiments.
Samples from the chemostats grown at three different CO2 levels as described above were subjected to aggregate formation using roller tables (Shanks and Edmondson, 1989). Samples were divided and transferred to cylindrical Plexiglas tanks and kept in the dark at 10°C. All tanks were placed on roller tables that rotate at 0.66 rpm so that aggregates could form under conditions that allow for continuous particle settling. To simulate the sinking of aggregates into deeper and hence more dilute waters, the concentration of suspended cells was lowered before the actual experiment began. Samples were taken directly after aggregate formation (day 2-4) and after 1 week for chemical analyses of the aggregates and of the suspended particles in the seawater surrounding the aggregates. To determine the size and abundance of aggregates, as well as the time of their formation, the roller tanks were monitored using a video camera as described in Engel et al. (2008). Aggregates from the tanks will be collected and chemically analyzed as above. In addition to the measurement of settling velocity, TEP, CSP, lipophilic gel tracer, and the bulk parameters POC, PN, DOC, DON, we will follow degradation of the particulate fraction by measuring amino acids and pigments as in Engel et al. (2008b).
Expected Results (H1): If hypothesis 1 is correct, we expect cell numbers and Chl a to be similar in each of the chemostats with different levels of CO2 since the phytoplankton abundance will be determined by the nutrient levels. However, TEP, CSP, and LSP should be higher in experiments with higher CO2 since from past studies we expect gel production to be higher. The ratio of TEP:CSP (or (C:N) in the gel particles will be higher with higher CO2 since N will be limiting. If H1 is correct, in experiments with higher CO2, POC should increase as more gels are formed, and PIC should decrease as calcification slows down. Because of higher phytoplankton exudation, DOC should be higher in experiments with higher CO2, but will decrease once gel formation begins.
Expected Results (H2): If hypothesis 2 is correct, then we expect to find the number of aggregates higher in tanks with higher CO2. Aggregates at higher CO2 should have lower PIC:POC ratios. They should have lower settling velocities as lower CaCO3 due to less ballast. DOC and DON will depend on the balance between microbial uptake and phytoplankton exudation. Particulate amino acids and carbohydrate compositions and amounts will demonstrate that there is more decomposition at higher CO2 because the CaCO3 that protects the organic matter at will be reduced.
Table 1 summarizes the methods and instruments that were or will be used. All analyses will be conducted in replicate.
| Parameter | Method | Reference |
| DIC | Photometry | Stoll et al. 2001 |
| Total Alkalinity | Gran Titration | Gran 1952 |
| pH/T | Electrochemical detection | WTW Operation Protocol |
| CO2 gas | Infrared Analyzer | Li-Cor Operation Protocol |
| Inorganic Nutrients | Colorimety | Koroleff and Grasshof 1983 |
| POC, PN | Combustion, CHN analyzer | JGOFS Protocoll 1994 |
| DOC, DON | High Temperature combustion | JGOFS Protocoll 1994 |
| Cell abundance | Flow Cytometry | Vaulot 1989 |
| Bacterial abundance | Flow Cytometry | Vaulot 1989 |
| TEP concentration and size distribution | Microscopy and Colorimetry after staining with Alcian Blue | Passow and Alldredge 1995, Engel 2008 |
| CSP concentration and size distribution | Microscopy after staining with Coomassie Blue |
Long and Azam 1996, Engel 2008 |
| Dissolved CHO | High Performance Anion Exchange Chromatography with Pulsed Amperometric Detection (HPAEC-PAD) | Mopper et al 1992, Engel and Händel 2008 |
| Total CHO | HPAEC-PAD | Mopper et al 1992, Engel and Händel 2008 |
| Dissolved AA | HPLC following derivatization | Lee et al 2000 |
| Total AA | HPLC following derivatization | Lee et al 2000 |
| Coccolith morphology | Scanning Electron Microscopy (SEM) | Paerl and Shimp 1973 |
| Aggregate size | Video-imaging and Image analysis | Engel et al 2008 |
| Aggregate settling velocity | Video-imaging and Image analysis | Engel et al 2008 |
| Lipid classes | Iatroscan (Madeleine Goutx – see support letter) | Striby et al. 1999 |

