Articles | Volume 14, issue 7
Biogeosciences, 14, 1857–1882, 2017
Biogeosciences, 14, 1857–1882, 2017

Research article 06 Apr 2017

Research article | 06 Apr 2017

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

Shubham Krishna and Markus Schartau Shubham Krishna and Markus Schartau
  • GEOMAR Helmholtz Centre for Ocean Research Kiel, Düsternbrooker Weg 20, 24105 Kiel, Germany

Abstract. The effect of ocean acidification on growth and calcification of the marine algae Emiliania huxleyi was investigated in a series of mesocosm experiments where enclosed water volumes that comprised a natural plankton community were exposed to different carbon dioxide (CO2) concentrations. Calcification rates observed during those experiments were found to be highly variable, even among replicate mesocosms that were subject to similar CO2 perturbations. Here, data from an ocean acidification mesocosm experiment are reanalysed with an optimality-based dynamical plankton model. According to our model approach, cellular calcite formation is sensitive to variations in CO2 at the organism level. We investigate the temporal changes and variability in observations, with a focus on resolving observed differences in total alkalinity and particulate inorganic carbon (PIC). We explore how much of the variability in the data can be explained by variations of the initial conditions and by the level of CO2 perturbation. Nine mesocosms of one experiment were sorted into three groups of high, medium, and low calcification rates and analysed separately. The spread of the three optimised ensemble model solutions captures most of the observed variability. Our results show that small variations in initial abundance of coccolithophores and the prevailing physiological acclimation states generate differences in calcification that are larger than those induced by ocean acidification. Accordingly, large deviations between optimal mass flux estimates of carbon and of nitrogen are identified even between mesocosms that were subject to similar ocean acidification conditions. With our model-based data analysis we document how an ocean acidification response signal in calcification can be disentangled from the observed variability in PIC.

Short summary
This study combines experimental data with results from numerical modelling. Data of an ocean acidification mesocosm experiment are used to constrain parameter values of a plankton model. Three different intensities of calcification are resolved with ensembles of optimised model results. Observed variability in data can be well explained by these ensemble model solutions. The simulated ocean acidification effect on calcification is small compared to the spread of the ensemble model solutions.
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