Onur Kerimoglu

Role of phytoplankton cell size on the competition for nutrients and light in incompletely mixed systems

We investigate the effects of algal cell size on the competition for nutrients and light in an incompletely mixed water column, employing a spatially explicit variable internal stores approach and previously published allometric scaling relationships for modeling phytoplankton growth. We analyze the interplay between the size-dependent vertical assimilation and uptake profiles and the role of environmental settings such as mixing intensity, nutrient loading and background turbidity for the outcome of competition. Our results suggest that a potentially beneficial factor for resource competition in spatially heterogeneous systems is a low ratio of subsistence nutrient quota to the maximal quota, q(min)/q(max), which is a decreasing function of cell size according to allometric relationships. Environmental parameters such as mixing intensity and nutrient availability are shown to modulate the relevance of the q(min)/q(max) ratio for the competitive outcome and thereby have non-monotonic impacts on the algal size selection. The outcome of competition further depends on the temporal and spatial variability of mixing. In particular, the presence of a metalimnion with low diffusivity and periodic perturbation of the depth of the metalimnion strongly influences the relative success of differently sized algae. This suggests that the anticipated reduction in wind induced mixing events due to climate warming will have context-dependent consequences for algal size selection.

Blue-Green Algae in a “Greenhouse Century”? New Insights from Field Data on Climate Change Impacts on Cyanobacteria Abundance

Climate warming is likely to impact phytoplankton communities by providing a habitat in which cyanobacteria have competitive advantage over other phytoplankton taxa. We used extreme hot weather periods to investigate the potential impact of climate change on cyanobacteria abundance in three large and deep peri-alpine lakes, Lakes Geneva, Annecy, and Bourget. Between 2000 and 2011, there were four extreme warm weather periods: spring and summer 2003, autumn 2006 and winter 2007. We found that the consequences of extreme air temperatures on cyanobacteria abundance and phytoplankton composition depend on the time of year in which the extreme temperatures occur. In all three lakes studied, a warm summer did not clearly promote cyanobacteria blooms, whereas a warm autumn promoted cyanobacteria growth in the mesotrophic Lakes Geneva and Bourget, but not in the oligotrophic Lake Annecy. A warm winter was associated with high cyanobacteria abundance and a high contribution of cyanobacteria to total phytoplankton biomass. Our results reinforce the idea that lakes have an ecological memory by showing that a warm winter can influence subsequent seasonal succession in the cyanobacteria community. In both mesotrophic lakes studied, cyanobacteria abundance was strongly influenced by phosphorus concentrations and winter air temperatures. We conclude that although extreme hot weather periods can be used to analyze various aspects of the impacts of climate change, they are of limited value in forecasting the structure of phytoplankton communities in a warmer future.

Implications of seasonal mixing for phytoplankton production and bloom development

Based on a 1D model considering phytoplankton and nutrients in a vertical water column, we investigate the consequences of temporal and spatial variations in turbulent mixing for phytoplankton production and biomass. We show that in seasonally mixed systems, the processes controlling phytoplankton production and the sensitivity of phytoplankton abundance to ambient light, trophic state and mixed-layer depth differ substantially from those at steady state in systems with time-constant diffusivities. In seasonally mixed systems, the annually replenished nutrient pool in the euphotic zone is an important factor for phytoplankton production supporting bloom development, whereas without winter mixing, production mainly depends on the diffusive nutrient flux during stratified conditions. Seasonal changes in water column production are predominantly determined by seasonal changes in phytoplankton abundance, but also by seasonal changes in specific production resulting from the transport of nutrients, the exploitation of the nutrient pool and the increase in light shading associated with phytoplankton growth. The interplay between seasonal mixing and the vertical distribution of mixing intensities is a key factor determining the relative importance of the processes controlling phytoplankton production and the sensitivity of the size and timing of the annual maximum phytoplankton abundance to the abiotic conditions.

Trophic mismatch requires seasonal heterogeneity of warming

Climate warming has been shown to advance the phenology of species. Asynchronous changes in phenology between interacting species may disrupt feeding interactions (phenological mismatch), which could have tremendous consequences for ecosystem functioning. Long-term field observations have suggested asynchronous shifts in phenology with warming, whereas experimental studies have not been conclusive. Using proxy-based modeling of three trophic levels (algae, herbivores, and fish), we .show that asynchronous changes in phenology only occur if warming is seasonally heterogeneous, but not if warming is constant throughout the year. If warming is seasonally heterogeneous, the degree and even direction of asynchrony depends on the specific seasonality of the warming. Conclusions about phenological mismatches in food web interactions may therefore produce controversial results if the analyses do not distinguish between seasonally constant and seasonal specific warming. Furthermore, our results suggest that predicting asynchrony between interacting species requires reliable warming predictions that resolve sub-seasonal time scales.

The large-scale impact of offshore wind farm structures on pelagic primary productivity in the southern North Sea

The increasing demand for renewable energy is projected to result in a 40-fold increase in offshore wind electricity in the European Union by 2030. Despite a great number of local impact studies for selected marine populations, the regional ecosystem impacts of offshore wind farm (OWF) structures are not yet well assessed nor understood. Our study investigates whether the accumulation of epifauna, dominated by the filter feeder Mytilus edulis (blue mussel), on turbine structures affects pelagic primary productivity and ecosystem functioning in the southern North Sea. We estimate the anthropogenically increased potential distribution based on the current projections of turbine locations and reported patterns of M. edulis settlement. This distribution is integrated through the Modular Coupling System for Shelves and Coasts to state-of-the-art hydrodynamic and ecosystem models. Our simulations reveal non-negligible potential changes in regional annual primary productivity of up to 8% within the OWF area, and induced maximal increases of the same magnitude in daily productivity also far from the wind farms. Our setup and modular coupling are effective tools for system scale studies of other environmental changes arising from large-scale offshore wind farming such as ocean physics and distributions of pelagic top predators.

Modular System for Shelves and Coasts (MOSSCO v1.0) – a flexible and multi-component framework for coupled coastal ocean ecosystem modelling

Abstract. Shelf and coastal sea processes extend from the atmosphere through the water column and into the seabed. These processes reflect intimate interactions between physical, chemical, and biological states on multiple scales. As a consequence, coastal system modelling requires a high and flexible degree of process and domain integration; this has so far hardly been achieved by current model systems. The lack of modularity and flexibility in integrated models hinders the exchange of data and model components and has historically imposed the supremacy of specific physical driver models. We present the Modular System for Shelves and Coasts (MOSSCO; http://www.mossco.de ), a novel domain and process coupling system tailored but not limited to the coupling challenges of and applications in the coastal ocean. MOSSCO builds on the Earth System Modeling Framework (ESMF) and on the Framework for Aquatic Biogeochemical Models (FABM). It goes beyond existing technologies by creating a unique level of modularity in both domain and process coupling, including a clear separation of component and basic model interfaces, flexible scheduling of several tens of models, and facilitation of iterative development at the lab and the station and on the coastal ocean scale. MOSSCO is rich in metadata and its concepts are also applicable outside the coastal domain. For coastal modelling, it contains dozens of example coupling configurations and tested set-ups for coupled applications. Thus, MOSSCO addresses the technology needs of a growing marine coastal Earth system community that encompasses very different disciplines, numerical tools, and research questions.