Assessing Drivers of Human-induced Change in Lake Erie Using Fuzzy Cognitive Mapping

Session: Poster session

Jessica Ives, University of Windsor, [email protected]
Jan Ciborowski, Dept of Biological Sciences, Univ. of Windsor, [email protected]
Rebecca Rooney, University of Waterloo, [email protected]
John Gannon, formerly of IJC, [email protected]
Silviya Ivanova, University of Windsor, [email protected]

Abstract

Organic pollution as a source of eutrophication on Lake Erie has been a concern since the 1920s. Research to identify candidate causes has led to management activities that have repeatedly solved acute issues. However, the relative importance of main drivers changes, and the effects of their interactions remain unclear. As part of the Lake Futures project at the University of Waterloo, we are using fuzzy cognitive maps (FCMs) to identify putative relationships between drivers (e.g., phosphorus loading, human population, precipitation), intermediate variables, and ecosystem indicators (e.g., cyanobacteria biomass, botulism animal kills, phytoplankton biomass) of eutrophication. FCMs are semi-quantitative models that consist of concepts (nodes), joined by directional edges (arcs) representing purported causal relationships among concepts identified through best professional judgement. We combine results from three sets of expert workshops addressing proximal and ultimate causes of eutrophication to obtain a consensual FCM representing the current understanding of causes of Lake Erie eutrophication. We use the resulting consensual FCM to propose recommendations for continuing research to understand current concerns of human-induced changes in Lake Erie.

1. Keyword
bioindicators

2. Keyword
eutrophication

3. Keyword
management

4. Additional Keyword
expert assessment

5. Additional Keyword
semi-quantitative models