From communities to individuals: Development of an early warning system to assess the relationship between climate warming and pollution in European freshwater ecosystems (PARAWARM)

The project addresses the interaction between parasitism and pollution in the context of climate change using parasites in freshwater fish as a model early warning system for altered environmental conditions by the application of a two-fold approach. First, a comparative assessment of the effect of temperature on parasite population and community structure dynamics will be carried out using matched pairs control-impact design in a natural experiment setup to test the parasite numerical response hypothesis. Simultaneously, structural patterns in a free-living freshwater system, macrozoobentic communities, will be evaluated. Secondly, using the same sampling design the hypothesis of temperature-mediated alteration of pollutant metabolism will be tested by a comparative evaluation of the rates of toxic metal accumulation in selected dominant parasite and benthic invertebrate species. Identification of temporal and spatial patterns of abundance and community structure at different thermal regimes is the key to forecast the impacts of climate change on parasite communities in fish in European freshwater ecosystems. Further, linking ecological data to pollutant metabolism will provide novel insights on the response of parasite communities to environmental change which may help predict possible outcomes of host-parasite interaction and forecast minimum index values to detect pollution in the context of the effect of global warming. The novelty of the proposed research lies in its trans-disciplinary approach linking advanced ecology and ecotoxicology concepts and methods. The quantification of the response to increased ambient temperature of the model organism groups relates not solely to issues fundamental to assessment of climate-mediated community level alterations and host-parasite interactions but to wider conceptual and applied domains such as synergism and/or antagonism among multiple stressors and pollution risk analysis using model indicator systems.