Journal cover Journal topic
Biogeosciences An interactive open-access journal of the European Geosciences Union
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Volume 14, issue 19
Biogeosciences, 14, 4499–4531, 2017
https://doi.org/10.5194/bg-14-4499-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Biogeosciences, 14, 4499–4531, 2017
https://doi.org/10.5194/bg-14-4499-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 12 Oct 2017

Research article | 12 Oct 2017

The acclimative biogeochemical model of the southern North Sea

Onur Kerimoglu1, Richard Hofmeister1, Joeran Maerz1,a, Rolf Riethmüller1, and Kai W. Wirtz1 Onur Kerimoglu et al.
  • 1Institute of Coastal Research, Helmholtz-Zentrum Geesthacht, Geesthacht, Germany
  • anow at: Max Planck Institute for Meteorology, Hamburg, Germany

Abstract. Ecosystem models often rely on heuristic descriptions of autotrophic growth that fail to reproduce various stationary and dynamic states of phytoplankton cellular composition observed in laboratory experiments. Here, we present the integration of an advanced phytoplankton growth model within a coupled three-dimensional physical–biogeochemical model and the application of the model system to the southern North Sea (SNS) defined on a relatively high resolution (∼ 1.5–4.5 km) curvilinear grid. The autotrophic growth model, recently introduced by Wirtz and Kerimoglu (2016), is based on a set of novel concepts for the allocation of internal resources and operation of cellular metabolism. The coupled model system consists of the General Estuarine Transport Model (GETM) as the hydrodynamical driver, a lower-trophic-level model and a simple sediment diagenesis model. We force the model system with realistic atmospheric and riverine fluxes, background turbidity caused by suspended particulate matter (SPM) and open ocean boundary conditions. For a simulation for the period 2000–2010, we show that the model system satisfactorily reproduces the physical and biogeochemical states of the system within the German Bight characterized by steep salinity; nutrient and chlorophyll (Chl) gradients, as inferred from comparisons against observation data from long-term monitoring stations; sparse in situ measurements; continuous transects; and satellites. The model also displays skill in capturing the formation of thin chlorophyll layers at the pycnocline, which is frequently observed within the stratified regions during summer. A sensitivity analysis reveals that the vertical distributions of phytoplankton concentrations estimated by the model can be qualitatively sensitive to the description of the light climate and dependence of sinking rates on the internal nutrient reserves. A non-acclimative (fixed-physiology) version of the model predicted entirely different vertical profiles, suggesting that accounting for physiological flexibility might be relevant for a consistent representation of the vertical distribution of phytoplankton biomass. Our results point to significant variability in the cellular chlorophyll-to-carbon ratio (Chl : C) across seasons and the coastal to offshore transition. Up to 3-fold-higher Chl : C at the coastal areas in comparison to those at the offshore areas contribute to the steepness of the chlorophyll gradient. The model also predicts much higher phytoplankton concentrations at the coastal areas in comparison to its non-acclimative equivalent. Hence, findings of this study provide evidence for the relevance of physiological flexibility, here reflected by spatial and seasonal variations in Chl : C, for a realistic description of biogeochemical fluxes, particularly in the environments displaying strong resource gradients.

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In this study, we present a coupled physical–biogeochemical model, in which the acclimation of autotrophs to their resource environment is resolved based on optimality arguments. The model is implemented in the southern North Sea, a shallow coastal system. Based on comparisons with multiple data sources, we show that the model can reproduce the variability in the system for the period 2000–2010 and analyze the mechanisms driving the large-scale, persistent coastal gradients in the system.
In this study, we present a coupled physical–biogeochemical model, in which the acclimation of...
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