Our research topics can be broadly classified into the following areas, for which we provide examples of topics with selected references below (click hyperlink for details on referenced publications):
 

• Community and food web ecotoxicology

  • Responses of freshwater and riparian communities/food webs (invertebrates and microorganisms) and ecosystem functions to toxicants in real world ecosystems (e.g. Link et al. 2022, Liess et al. 2021, Graf et al. 2020, Fernandez et al. 2015, Beketov et al. 2013) and in controlled experiments (e.g. Schreiner et al. 2018, Graf et al. 2017, Uhl et al. 2015) to test hypotheses and assess risks.

  • Theoretical and conceptual advances in the prediction of the response to toxicants and multiple stressors (e.g. Weisner et al. 2021, Orr et al. 2020, Schäfer 2019, Bracewell et al. 2019, Schäfer & Piggott 2018)

  • Characterisation of toxicant exposure in ecosystems (e.g. Halbach et al. 2022, Schreiner et al. 2021a, Schreiner et al. 2021b, Steinmetz et al. 2017, Fernandez et al. 2014)
     

• Computational ecotoxicology and data analysis

  • Analysis of complex ecological and environmental data to identify large scale patterns of toxicant exposure and effects as well as sensitivity distributions (e.g. Zubrod et al. 2019, Szöcs et al. 2017, Malaj et al. 2014)

  • Development of software (e.g. R packages) for processing chemical and ecotoxicological data (e.g. Szöcs et al. 2020, Scharmüller et al. 2020, Schreiner et al. 2020, Fernandez et al. 2014)

  • Cross-species extrapolation of species sensitivity to stressors based on phylogenetic data and species traits (e.g. Malaj et al. 2016)

  • Evaluation of eco(toxico)logical statistical methods (e.g. Jupke & Schäfer 2020, Malaj et al. 2016, Szöcs et al. 2015, Szöcs and Schäfer 2015)
     

• Modelling of stressors and using models to predict the stress responses of populations, communities and food webs

  • Using process-based models to predict the response of individuals and populations of different organism groups to stressors including toxicants considering spatiotemporal dynamics (e.g. Turschwell et al. 2022, Streib et al. 2022, Streib et al. 2020, Schäfer et al. 2017, Ashauer et al. 2016)

  • Network, food web and ecosystem modelling from a systems perspective (e.g. Osakpolor 2021, Heer et al. 2021, Heer et al. 2019)

  • Spatial modelling of the distribution of stressors such as toxicants on a larger scale and development of software algorithms (e.g. Kattwinkel et al. 2020, Le et al. 2019, Le et al. 2017, Bhowmik, Metz & Schäfer 2015)
     

• Stress ecology: Analying and predicting the response of communities and ecosystem functions to non-chemical stressors

  • Response of freshwater microbial and invertebrate communities and ecosystem functions to stressors associated with land use and climate change (e.g. Streib et al. 2022, Hamilton et al. 2020, Wenisch et al. 2017, Voß and Schäfer 2017)

  • Using aquatic invertebrate species traits to predict community responses to stressors and ecosystem functioning (e.g. Kunz et al. 2022, Hamilton et al. 2020, Wenisch et al. 2017, Voß and Schäfer 2017)

  • Establishing conceptual frameworks and trait databases for stress ecology (e.g. Kunz et al. 2022, Hamilton et al. 2020, Kefford et al. 2020, Schäfer et al. 2011)
     

• Ecosystem management and linking ecosystem status to human well-being

  • Frameworks and suggestions to improve ecosystem management (e.g. Jupke et al. 2022, Weisner et al. 2022, Maasri et al. 2022, Schäfer et al. 2019, Schäfer et al. 2018, Jähnig et al. 2019, Brack et al. 2017, Cañedo-Argüelles et al. 2016)

  • Using ecosystem services to link ecosystem status and human well-being (e.g. Berger et al. 2021, Ullah et al. 2020, Bruins et al. 2017, Schäfer et al. 2012)