Large ecotoxicological effect database are available to us today describing the effects of thousands of chemicals on various standard test organisms. These test organisms should represent a wide array of species in natural environments. Hence, the present work will combine estimates about species taxonomic similarities and their sensitivity towards toxicants. Quantifying these potential links would allow extrapolating toxic effects for large parts of natural communities that are currently unknown.

Annual pesticide sales data on the national level are the most detailed data that most EU countries publish. However, this only enables large-scale and less specific evaluations about pesticide occurrence in ecosystems. Thus, it is urgently needed to gain a better (more detailed) understanding about the application of active ingredients in various regions and crops. One approach may be to link annual sales data with more detailed registration data to produce estimates of crop-specific and pest specific pesticide use statistics. Generating such a complex matrix provides further insight into the use of pesticides but also enables to simulate various scenarios (e.g., phase-outs, climatic and pest changes) and the possibility to optimize currently used pesticides according to their ecotoxicological footprint. The project requires good German skills.

High resolution crop distribution data has recently been made available for all of Europe. In addition, the MAGIC group is in possession of detailed, crop-specific pesticide use data for all of Europe covering more than 500 active ingredients. The topic will focus on describing the total applied toxicities in Europe for various crops, its temporal trends and effect on numerous aquatic and terrestrial organism groups.

Each year our ecotoxicological knowledge about the effects of chemicals improve. Consequently, substances that were once deemed safe may now be understood as noteworthy detriments to environments. The topic will analyze in detail how our understanding of ecotoxicological effects has changed over time using extensive ecotoxicity databases. Quantifying the degree by which some substances’ known toxicity has changed with time will enable more detail estimates about the reliability of ecotoxicity tests and the uncertainty associated with standard testing procedures.

Chemicals in surface waters rarely occur alone but rather they are present as complex mixtures in aquatic ecosystems. In addition, monitoring programs are unable to analyze the full spectrum of these chemicals, thus understading, describing and predicting the mixtures that may be present in surface waters is an essential task to safeguard these pivotal ecosystems. The work will use existing monitoring data to uncover spatiotemporal patterns of chemicals and estimate the likelihood of unmonitored chemicals being present at various locations.

Detailed pesticide use statistics for the last 20 years are available to the MAGIC research team. These data will be used in concert with extensive monitoring data (n > 5,000,000) from three federal states to describe the main drivers (e.g., upstream crop distribution, total applied toxicity) behind the occurrence of pesticides that impair aquatic ecosystems in Germany. The thesis will build upon two previously concluded master theses to this topic and expand them via geospatial analyses of the underlying land-use drivers.

Monitoring data describing the occurrence of >200 organic contaminants in surface waters of Baden-Württemberg, Germany, are available for analysis. The project will describe the occurrence and ecotoxicological risks for aquatic ecosystems as a result of these contaminations. Geospatial analyses of land-use will be used to further explain the occurrence of chemicals in surface waters. Additional focus can be put on the occurrence of these contaminants in protected water bodies such as those situated in nature protection areas.

Vegetative buffer strips (VBS) surrounding agricultural fields are important semi-natural areas able to retain pesticides. They serve as both habitat for beneficial insects but also as structures to which pesticides can adsorb to during heavy-rainfall events. Deriving VBS between aquatic systems and agricultural fields is an important spatial explanatory variable that can be used to link instream pesticide exposure with adjacent land-uses. The thesis will develop a method to derive VBS and non-vegetative buffer areas based on multiple land-use layers (e.g. satellite images, ATKIS data, vegetation data) so that they can be used in conjunction with surface water monitoring data. The final data will be used to further establish links of aquatic risks and agricultural land-use.