Process-based modeling to assess the nutrient removal efficiency of two endangered hydrophytes: Linking nutrient-cycle with a multiple-quotas approach

Hydrophytes have been widely used to reduce nutrient levels in aquatic ecosystems, but only limited species with high nutrient removal efficiencies have been implemented. Thus, it is necessary to continually explore new candidate species with high nutrient removal efficiencies. To effectively explore the nutrient removal ability of hydrophytes, a new process-based model combining the multiple-quotas approach and nutrient-cycle model was developed. The multiple-quotas approach provides a theoretical framework to conceptually explain the uptake and response of autotrophs to multiple nutrients. The developed process-based model was validated using observational data from microcosm experiments with two emergent hydrophytes, Menyanthes trifoliata and Cicuta virosa. The results showed that both M. trifoliata and C. virosa effectively reduced nitrogen (N) and phosphorus (P) in both water and sediment layers, but M. trifoliata showed a higher removal efficiency for both nutrients than C. virosa, particularly for total ammonia + ammonium-nitrogen (NH_x-N) and nitrate-nitrogen (NO₃-N) in the sediment layer (M. trifoliata: 0.579-0.976 for NH_x-N, 0.567-0.702 for NO₃-N; C. virosa: 0.212-0.501 for NH_x-N, 0.466-0.560 for NO₃-N). In addition, M. trifoliata achieved the maximum removal efficiency for N and P at higher nutrient exposure levels than C. virosa (M. trifoliata: exposure level of 0.725-0.775; C. virosa: exposure level of 0.550-0.575). The developed model well simulated the species-specific growth patterns of hydrophytes depending on the nutrient exposure level as well as the N and P dynamics in the water and sediment layers. The approach adopted in this study provides a useful tool for discovering candidate species to improve hydrophyte diversity and effectively remove nutrients from aquatic ecosystems.

Vertical migration by bulk phytoplankton sustains biodiversity and nutrient input to the surface ocean

Phytoplankton subsumes the great variety of unicellular photoautotrophs that perform roughly half of Earth's primary production. They achieve this despite their challenging oceanic habitat, with opposing vertical gradients of nutrients (which often limit their growth near the surface) and light (which becomes limiting with increasing depth). Most phytoplankton species are commonly assumed to be incapable of moving actively between the zones of light and nutrient availability, which are separated vertically by from 30-120 m. Here we propose that a considerable fraction of phytoplankton vertically traverse these gradients over time scales from hours to weeks, employing variations of a common migration strategy to acquire multiple resources. We present a mechanistic Lagrangian model resolving phytoplankton growth linked to optimal migration behaviour and demonstrate unprecedented agreement of its calculated vertical CHL-a distributions with 773 profiles observed at five prominent marine time-series stations. Our simulations reveal that vertically cycling phytoplankton can pump up enough nutrient to sustain as much as half of oceanic Net Primary Production (NPP). Active locomotion is therefore a plausible mechanism enabling relatively high NPP in the oligotrophic surface ocean. Our simulations also predict similar fitness for a variety of very different migration strategies, which helps to explain the puzzling diversity of phytoplankton observed in the ocean.

A 1-Dimensional Sympagic–Pelagic–Benthic Transport Model (SPBM): Coupled Simulation of Ice, Water Column, and Sediment Biogeochemistry, Suitable for Arctic Applications

Marine biogeochemical processes can strongly interact with processes occurring in adjacent ice and sediments. This is especially likely in areas with shallow water and frequent ice cover, both of which are common in the Arctic. Modeling tools are therefore required to simulate coupled biogeochemical systems in ice, water, and sediment domains. We developed a 1D sympagic–pelagic–benthic transport model (SPBM) which uses input from physical model simulations to describe hydrodynamics and ice growth and modules from the Framework for Aquatic Biogeochemical Models (FABM) to construct a user-defined biogeochemical model. SPBM coupled with a biogeochemical model simulates the processes of vertical diffusion, sinking/burial, and biogeochemical transformations within and between the three domains. The potential utility of SPBM is demonstrated herein with two test runs using modules from the European regional seas ecosystem model (ERSEM) and the bottom-redox model biogeochemistry (BROM-biogeochemistry). The first run simulates multiple phytoplankton functional groups inhabiting the ice and water domains, while the second simulates detailed redox biogeochemistry in the ice, water, and sediments. SPBM is a flexible tool for integrated simulation of ice, water, and sediment biogeochemistry, and as such may help in producing well-parameterized biogeochemical models for regions with strong sympagic–pelagic–benthic interactions.

Physics or biology? Persistent chlorophyll accumulation in a shallow coastal sea explained by pathogens and carnivorous grazing

One of the most striking patterns at the land–ocean interface is the massive increase of chlorophyll-a (CHL) from continental shelves towards the coast, a phenomenon that is classically linked to physical features. Here I propose that the coastal–offshore CHL gradient in a shallow sea has biological origins related to phytoplankton mortality that are neglected in state-of-the-art biogeochemical models. I integrate a trait-based ecosystem model into a modular coupling framework that is applied to the southern North Sea (SNS). The coupled model very well reproduces daily, seasonal and inter-annual (2000-2014) dynamics and meso-scale patterns in macronutrients, zooplankton biomass, and CHL as observed in situ and by remote sensors. Numerical experiments reveal that coast–offshore CHL gradients may predominantly arise from a trophic effect as resolved by an increase in carnivorous grazing towards shallow waters. This carnivory gradient reflects higher near-coast abundance of juvenile fish and benthic filter feeders. Furthermore, the temporal evolution of CHL can be much affected by viral infection as a fast-responding loss process at intermediate to high phytoplankton concentrations. Viral control in the model also prevents excessive and unrealistic blooms during late spring. Herbivores as often only ecological factor considered for explaining the spatio-temporal phytoplankton distribution are in this study supplemented by pathogens as well as pelagic and benthic carnivores as powerful agents, which are barely represented in current modeling but can mediate physical drivers of coastal ecosystems.

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

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.