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Regular ecological investigations usually on a fortnightly basis have been carried out at the Saidenbach Reservoir (SE Germany) and its tributaries since 1975. The data show a sudden decrease in the phosphorus import of over 60% in 1990, resulting in the abrupt change of the trophic state from eutrophic to weakly mesotrophic. Contrary to expectations, the average annual phytoplankton abundance did not decrease but almost doubled on average over the years after 1990. This was primarily due to mostly warmer winters after 1990 causing longer spring overturns, which minimized sedimentation losses, enabled better utilization of the phosphorus reserves, and resulted in higher yields of the diatom-dominated phytoplankton spring mass development. In the summers after 1990, the mass growth of the diatom Fragilaria crotonensis, which in the past used to dominate in this season and effectively transported phosphorus to the sediment by settling, was considerably reduced because of lower P supply and stronger stratification. However, the decrease in the biomass of Fragilaria was overcompensated by the increased abundance of cyanobacteria. They benefitted not only from declining phosphorus competition by Fragilaria but also from higher thermal stability and temperature in the epilimnion. Hence, even higher summer biomasses were observed despite considerably lowered phosphorus import. The analysis of the long-term dataset clearly illustrates the deciding impact of hydrophysical factors on the phytoplankton growth, also under nutrient deficient conditions. The altered mixing and stratification pattern caused by climate change did not only prevent the re-oligotrophication of the reservoir but even enhanced the phytoplankton production. It seems that global warming modifies the interplay between physical and nutrient limitation mechanisms and the limits and models used in the past to classify trophic-state levels have to be verified. The study shows the enormous significance and indispensability of uninterrupted ecological long-term datasets, including reliable data of the ecosystem's organismic structure, for research about the consequences of climate change. |
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