University of Waterloo
Exciting opportunity for a Ph.D. student to join the Lake Futures: Enhancing Adaptive Capacity and Resilience of Lakes and their Watersheds project, funded under the Global Water Futures.
The successful applicant will work in the laboratory of Rebecca Rooney (University of Waterloo) co-advised by Jan Ciborowski (University of Windsor) and will enroll in the Doctor of Philosophy (PhD) in Biology-Water graduate program under the Collaborative Water Program, supported by the Water Institute at the University of Waterloo.
Starting date: Jan 1, 2018
Our ability to effectively manage aquatic ecosystems is limited by our ability to monitor system inputs or to predict the complex environmental responses. Both conceptual and mechanistic models are important tools in helping to understand ecological relationships in aquatic ecosystems and to create hypotheses about causal pathways that can improve natural resource management. Fuzzy Cognitive Maps (FCMs) offer an approach that summarizes qualitative and semi-quantitative information.
The student will have the opportunity to evaluate, refine and develop FCM models to improve our understanding of the associations between land-based drivers of eutrophication (agriculture, rural and urban development) and biological manifestations of concern in Lake Erie (harmful algal blooms, hypoxia, Cladophora fouling, botulism).
The model pathways showing the strongest associations between drivers and biological response variables will identify candidate indicator variables whose association with drivers will be subsequently calibrated using machine learning algorithms. Identification of appropriate indicators is a major knowledge gap constraining management of eutrophication related issues in Lake Erie. This project offers a substantial opportunity for the student to work collaboratively the Lake Erie Management community to plan and undertake co-operative monitoring in Lake Erie and its watersheds.
To be eligible, applicants must have successfully defended and submitted their MSc thesis prior to the proposed start date. Applicants should have strong interests in quantitative ecology and a background in food webs or nutrient dynamics of aquatic ecosystems. They should be highly motivated, with the ability to work independently and collaboratively, and possess strong verbal and written communication skills.
Applications must include a cover letter, C.V., unofficial transcripts, and the contact information of three references. All documentation submitted must be assembled in a single PDF file and sent to: Dr. Rebecca Rooney, c/o Tatjana Milojevic at GWF-UW@uwaterloo.ca with PhD-LFWP3-YourName in the subject line.
Lake Erie has often been used as an example of the effectiveness of adaptive management approaches to resolving various manifestations of environmental problems. The recognition that phosphorus was the key factor responsible of Lake Erie’s eutrophication led to the implementation of pollution controls that resulted in a dramatic recovery by the 1990s. The first evidence of re-eutrophication was observed at a time when total phosphorus loading targets were being met. Although research at the time was insufficient to explain the underlying drivers, the International Joint Commission convened a series of workshops to identify possible causes. A panel of experts used a Fuzzy Cognitive Mapping approach to summarize key variables and relationships among components of the food web and identify the most likely factors. Several years of directed research resolved many of the uncertainties – re-eutrophication is now ascribed largely to greater nutrient loading (during wet springs) and to an increase the relative amount of bioavailable phosphorus entering Lake Erie. Current recommendations call for a 40% reduction in the annual load of phosphorus to western Lake Erie to minimize the frequency of harmful algal blooms.
The student engaged in this project will link human activity to adverse environmental consequences (e.g., eutrophication, algal blooms) using fuzzy cognitive mapping (FCM) and graph theory models (Ozesmi & Ozesmi 2004; Malek 2017).
Building on models first posited in 2009 by the International Joint Commission and the Lake Erie LAMP to identify the causes of harmful algal blooms in the Western Basin of Erie (IJC 2009) this project will address a major knowledge gap, one manifestation of which is causes of blooms of Cladophora in the Eastern Basin of Lake Erie. We will update the FCM model with findings from recent research results, and expand the model by adding novel sub-models that incorporate the roles of agriculture and urban land use to probabilistically evaluate the risks to/improvement in water quality posed by changes in land use and climate. This process will identify relevant, sensitive ecological indicators that will assist GWF end users in monitoring and decision-making. This project integrates the inputs/outputs of coupled lake-watershed nutrient dynamic models to measures and manifestations of the vulnerability, resilience, degradation and recovery of Lake Erie and facilitates the assessment of management objectives that can counter water quality deterioration and abate nuisance algal blooms under changing climate and land-use scenarios.