A model-based projection of historical state of a coastal ecosystem: Relevance of phytoplankton stoichiometry

Highlights: • A model-based reconstruction of the historical state of the German Bight is analyzed. • Historical nutrient concentrations are >50% lower than the control (2000–2010) state. • Differences in chlorophyll a (Chl) are less pronounced than that in nutrients. • Chl:C of phytoplankton is estimated to be lower in historic state. • Physiological flexibility of phytoplankton is relevant for their (in)sensitivity. We employed a coupled physical-biogeochemical modelling framework for the reconstruction of the historic (H), pre-industrial state of a coastal system, the German Bight (southeastern North Sea), and we investigated its differences with the recent, control (C) state of the system. According to our findings: i) average winter concentrations of dissolved inorganic nitrogen and phosphorus (DIN and DIP) concentrations at the surface are ∼70–90% and ∼50–70% lower in the H state than in the C state within the nearshore waters, and differences gradually diminish towards off-shore waters; ii) differences in average growing season chlorophyll a (Chl) concentrations at the surface between the two states are mostly less than 50%; iii) in the off-shore areas, Chl concentrations in the deeper layers are affected less than in the surface layers; iv) reductions in phytoplankton carbon (C) biomass under the H state are weaker than those in Chl, due to the generally lower Chl:C ratios; v) in some areas the differences in growth rates between the two states are negligible, due to the compensation by lower light limitation under the H state, which in turn explains the lower Chl:C ratios; vi) zooplankton biomass, and hence the grazing pressure on phytoplankton is lower under the H state. This trophic decoupling is caused by the low nutritional quality (i.e., low N:C and P:C) of phytoplankton. These results call for increased attention to the relevance of the acclimation capacity and stoichiometric flexibility of phytoplankton for the prediction of their response to environmental change.