A data-model synthesis to explain variability in calcification observed during a CO2 perturbation mesocosm experiment

A series of studies were conducted during the last two decades to investigate effects of ocean acidification (OA) on phytoplankton physiology, plankton ecology, and biogeochemical dynamics of marine ecosystems. Among those studies are experiments with tanks or bags called mesocosms, with some enclosed water volume that typically comprised a natural plankton community found in the surrounding environment. The Pelagic Ecosystem CO2 – Enrichment Study PeECE-I experiment is one such study, where mesocosms were perturbed and exposed to different carbon dioxide (CO2) concentrations to determine responses in growth dynamics of the coccolithophorid Emiliania huxleyi, a marine calcifying algae. The data from replicate mesocosms of PeECE-I show some natural variability and significant differences were revealed in the accumulation of particulate inorganic carbon (PIC) between mesocosms of similar CO2 treatments.

In our study we reanalyse PeECE-I data and apply an optimality-based model approach to understand most of the variability observed, with major focus on total alkalinity (TA) and calcification. We explore how much of the observed variability in data can be explained by variations of initial conditions and by the effect of CO2 perturbations. According to our model approach, changes in cellular calcite formation are resolved at the organism-level in response to variations in CO2. With a data assimilation (DA) method we obtain three distinctive ensembles of model solutions, with low, medium and high calcification rates. Optimised values of initial conditions turned out to be correlated with estimates physiological model parameters. The spread of ensemble model solutions captures most of the observed variability, corresponding to the combinations of parameter estimates. Optimised model solutions of the high CO2 treatment are shown to systematically overestimate observed PIC production. Thus, the simulated CO2 effect on calcification is likely too weak. At the same time our model results yield large differences in optimal mass flux estimates of carbon and of nitrogen even between mesocosms exposed to similar CO2 conditions.

Krishna S. & Schartau M., 2016. A data-model synthesis to explain variability in calcification observed during a CO2 perturbation mesocosm experiment. Biogeosciences Discussions 1-52. Article.

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