Linking Multiple Stressors to Adverse Ecological Responses Across Watersheds
PI: Mark Servos, University of Waterloo
Co-I's: Wayne Parker; Paul Craig, University of Waterloo
The project will support improved monitoring and risk assessment programmes through the development of models and tools that can be employed to predict the impacts of contaminants related to changing urban environments and climate on aquatic ecosystems. This work will focus on creating and applying knowledge necessary for predicting and interpreting the impacts of urbanization (e.g. wastewater, storm water, population growth) in the context of variability (natural and anthropogenic) at the watershed scale. This will form the foundation for building frameworks for consideration of multiple stressors that are a major challenge for watershed management, especially in the face of global environmental change.
The integration of contaminant fate modelling (including hydrologic variability) with measured biological outcomes has rarely been done, especially in the context of evaluating multiple stressors and natural variability at the watershed scale. This is partly due to the need to have site specific information as well as the need for an intra-disciplinary approach (e.g. environmental chemistry, biology, engineering, etc.). The proposed project will contribute to this rapidly emerging area of research related to predicting exposure and effects of contaminants in watersheds and supporting the development of approaches for improved environmental assessments and remediation. The project will use a well-developed case study to build on past and current efforts to measure and model contaminants and their impacts in the Grand River watershed (a major focus of GWF), to validate models and then extend them towards other watersheds and conditions nationally. With major wastewater infrastructure investments being made in this watershed to improve water quality it is an ideal opportunity to explore how ecosystems change in response to remedial actions. This prior work has generated a unique data set spanning over more than a decade that has included sampling of effluent, waters (e.g. chemistry) and biological responses in a sentinel fish species (e.g. effects) across the watershed. It has characterized site specific and cumulative exposure and effects in fish across several levels of biological organization (genes to populations) and included numerous reference sites.
An exposure and effects model will be built and tested using this unique data set as the basis to predict spatial and temporal changes. This will contribute to building adverse outcome pathways for contaminants and complex mixtures that are currently not well developed. The current predictive exposure and effects models are currently not well linked or validated with actual field based observations. The proposed project will focus initially on well-documented endpoints (e.g. estrogenicity) but will also extend to new chemicals and biological endpoints (e.g. metabolism, epigenetics) that may become important tools for assessing change in the near future. The long term goal is to provide a robust multi-stressor modelling platform that could be transferable to other watersheds across Canada.