Using Fuzzy Cognitive Maps to Understand the Complexity of the Linkages betwee Urbanization, Phosphorus Flows and Eutrophication
Published: 31 October 2013 by MDPI AG in Proceedings of The 3rd World Sustainability Forum in The 3rd World Sustainability Forum session Sustainable Urban Development
MDPI AG, 10.3390/wsf3-e002
Abstract: Phosphorus has been identified as the limiting nutrient and a primary cause of both nuisance and hazardous algal blooms in the North American Great Lakes and other water bodies. Urban areas contributed phosphorus from wastewater treatment plants and through stormwater runoff. Phosphours reduction was the key element of the first Great Lakes Water Quality Agreement, between Canada and the United States in 1972. Although the measures that were enacted to reduce phosphorus were successful at reducing algal blooms, the problem reemerged in the last ten years. The largest hazardous algal bloom on Lake Erie occurred in 2011 and the first hazardous algal bloom on Lake Superior occurred in 2012. Nuisance algae have become a problem for infrastructure and recreation in the nearshore habitats of Lakes Erie and Ontario and to a lesser extent in tthe nearshore habitat of Lake Huron. Fuzzy cognitive mapping (FCM) has been used to describe and analyze theflow of phosphorus through Lake Erie (2009), through agricultural production into Lake Erie (2010) and most recently, through urban areas into Lake Erie. FCM represents the flow and linkages with algal blooms and eutrophication as a network of nodes and linkages. Each node is a driver, a final receptor, or a stressor (a mid-point that both receives and contributes phosphorus to the system). FCM is a modelling strategy that has proven to be very effective for complex systems where data are not available to describe the many processes and flows, yet where an urgent need for action has been established to cope with a problem. FCM is a process where diverse groups of experts work in teams to map out the system. These maps also include weights for each linkage that describe the strength of the linkage, the confidence in the linkage, the scientific certainty, the spatial and temporal extent of the relationship and other relevant factors. The various team maps can then be aggregated into one map through different methods such as averaging the weights or genetic algorithms. A stakeholder workshop was convened in March, 2013 to create several different maps that illustrate the linkages between urbanization, phosphorus, algal blooms and eutrophication. The aggregate maps highlight the multiple drivers and the complexity of the flows through the stressors. Maps might typically contain 90 nodes and 140 linkages. The analysis of the maps provides insight as to the most important nodes in these networks, sggesting where measures to control the flow of phosphorus might have the largest impact. The aggregation and analysis of the maps was done with the Fuzzy Aggregated Linakges Within Environmental Bounds (FALWEB) software, which was developed for fuzzy cognitive maps.
Keywords: urban areas, Algal Blooms, Linkages, LAKE, Extent, Erie, Flow of Phosphorus, contributed phosphorus