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An experimentally validated nitrate–ammonium–phytoplankton model including effects of starvation length and ammonium inhibition on nitrate uptake

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  • Malerba, Martino E.
  • Connolly, Sean R.
  • Heimann, Kirsten

Abstract

Nitrate and ammonium are the two most important ionic forms of inorganic nitrogen driving biomass production in marine and freshwater aquatic systems. The performance of plants and algae often changes when reared with either of these two forms of nitrogen individually, as well as when they are both present, or when cells have experienced previous periods of nitrogen starvation. Current functional responses quantifying how ambient nitrogen drives changes in population density are unable to capture interacting and transient effects of nitrate and ammonium. Hence, in this paper we formulate, calibrate, and test a new nitrate–ammonium quota model that accounts for nitrate and ammonium uptake, as well as the effects of nitrogen starvation length and ammonium-induced nitrate uptake inhibition. We fit the model with several time-series from the green alga Chlorella sp. reared in laboratory batch cultures under multiple initial conditions. We show that a single set of calibrated model parameters can capture time-series collected from experiments inoculated at 12 different initial concentrations of nitrate, ammonium, and biomass. The model also performed well when validated against time-series from two novel initial conditions withheld from model calibration. Our model therefore provides a framework for evaluating the potential broader ecological and environmental consequences of ambient nitrate and ammonium regimes for phytoplankton communities in nature and aquaculture.

Suggested Citation

  • Malerba, Martino E. & Connolly, Sean R. & Heimann, Kirsten, 2015. "An experimentally validated nitrate–ammonium–phytoplankton model including effects of starvation length and ammonium inhibition on nitrate uptake," Ecological Modelling, Elsevier, vol. 317(C), pages 30-40.
  • Handle: RePEc:eee:ecomod:v:317:y:2015:i:c:p:30-40
    DOI: 10.1016/j.ecolmodel.2015.08.024
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