Cyanobakterienblüten in der Ostsee verstehen
Zusammenfassung der Projektergebnisse
In the Baltic Sea, cyanobacteria species regularly form massive surface scums or blooms in late summer. Cyanobacteria can produce toxins (that are suspected to enter the food web) and supply the already overfertilized system with additional bioavailable nitrogen. This input can be substantial and thus cyanobacteria have the potential to counteract management decisions to limit eutrophication. Despite their crucial importance, cyanobacteria blooms are surprisingly little understood which is reflected in major difficulties to model and forecast blooms accurately. To explore the status-quo of common model assumptions and biological knowledge this project summarized the current understanding from the literature. Our review illustrates that there is consensus between five dissected biogeochemical models and biologists in that cyanobacteria have an advantage over other functional groups under nitrate-depleted conditions. Further, there is consensus that the growth of cyanobacteria can be controlled by the availability of light and phosphate and that cyanobacteria grow mostly slower than diatoms and other phytoplankton. Other than that, the specific formulations of the underlying model assumptions strongly diverge. Particularly uncertain are loss processes, such as grazing, the impact of viruses and programmed cell death, but also to temperature dependent growth and minimal P-requirements. Further, the project proposed to systematically explore the predictive skill of a suite of potentially important factors that are suggested to trigger cyanobacteria bloom formations. In contrast to existing studies we focused on controls during the early stages of bloom formation rather than focusing on the bloom peaks to improve the current understanding of cyanobacteria blooms in the Baltic Sea. The respective analyses were based on a combination of high resolution ocean circulation model output and observational data. During the project we retraced cyanobacteria blooms to identify and analyse the origin and conditioning of cyanobacteria blooms. One major focus has been set on abiotic factors, such as photosynthetically active radiation, surface salinity, sea surface temperature and surface mixed layer depth during bloom formation. When retracing cyanobacteria booms and analysing the environmental conditions preceding bloom manifestations, these factors had surprisingly little impact and we could not dissect explanatory power in radiative conditions and sea surface temperature other than that blooming occurs in spring and summer. Further, we failed to confirm the hypothesis that blooms may be triggered by strong wind-induced mixing events. The only apparent difference between bloom forming waters and other water masses in our analysis is the distance to the coast: trajectories that end in blooms are situated further offshore than those that fail to bloom. Because coastal and offshore waters have different biogeochemical characteristics this provides a clue as for what may trigger the blooms. Specifically we find that comparably oligotrophic conditions prevail offshore. In this context, however, we have to stress that the results have to be considered with some caution due to the diversity and sparsity of the available nutrient observations. Also our studies indicated that unresolved factors, such as grazing, viruses and species competition might need more consideration. Still we regard our result of major importance for numerical models because the respective nutrient thresholds have to be prescribed and we illustrate how the respective values can strongly impact the results of projections. We conclude that the remaining model uncertainties should be considered in political decision making support.
Projektbezogene Publikationen (Auswahl)
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(2020) Contrasting juxtaposition of two paradigms for diazotrophy in an Earth System Model of intermediate complexity. Biogeosciences Discussions
Löptien, U. and Dietze, H.
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(2021) Cyanobacteria Blooms in the Baltic Sea: A Review of Models and Facts. Biogeosciences 18, 2347-2378
Munkes, B., Löptien, U. and Dietze, H.
