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Biogeosciences An interactive open-access journal of the European Geosciences Union
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Volume 10, issue 6 | Copyright
Biogeosciences, 10, 4341-4356, 2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 27 Jun 2013

Research article | 27 Jun 2013

A model for variable phytoplankton stoichiometry based on cell protein regulation

J. A. Bonachela1, S. D. Allison2, A. C. Martiny2, and S. A. Levin1 J. A. Bonachela et al.
  • 1Department of Ecology and Evolutionary Biology, Princeton University, Princeton, New Jersey, 08544, USA
  • 2Department of Ecology and Evolutionary Biology & Department of Earth System Science, University of California, Irvine, California, 92697, USA

Abstract. The elemental ratios of marine phytoplankton emerge from complex interactions between the biotic and abiotic components of the ocean, and reflect the plastic response of individuals to changes in their environment. The stoichiometry of phytoplankton is, thus, dynamic and dependent on the physiological state of the cell. We present a theoretical model for the dynamics of the carbon, nitrogen and phosphorus contents of a phytoplankton population. By representing the regulatory processes controlling nutrient uptake, and focusing on the relation between nutrient content and protein synthesis, our model qualitatively replicates existing experimental observations for nutrient content and ratios. The population described by our model takes up nutrients in proportions that match the input ratios for a broad range of growth conditions. In addition, there are two zones of single-nutrient limitation separated by a wide zone of co-limitation. Within the co-limitation zone, a single point can be identified where nutrients are supplied in an optimal ratio. When different species compete, the existence of a wide co-limitation zone implies a more complex pattern of coexistence and exclusion compared to previous model predictions. However, additional comprehensive laboratory experiments are needed to test our predictions. Our model contributes to the understanding of the global cycles of oceanic nitrogen and phosphorus, as well as the elemental ratios of these nutrients in phytoplankton populations.

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