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The mis(alignment) of harmful algal bloom social-ecological networks and key water quality parameters in Lake Erie

Authors: Meghan Klasic*, Center for Environmental Policy & Behavior, University of California - Davis, Rachel Lamb, Geographical Sciences, University of Maryland, College Park, Kelsey Leonard, Comparative Public Policy, McMaster University, Canada, Vanessa Vargas-Nguyen, Marine, Estuarine, Environmental Science, University of Maryland Center for Environmental Science
Topics: Coupled Human and Natural Systems, Hazards, Risks, and Disasters, Water Resources and Hydrology
Keywords: social ecological systems, social ecological network analysis, water governance, resilience, water quality
Session Type: Paper
Day: 4/10/2020
Start / End Time: 8:00 AM / 9:15 AM
Room: Virtual Track 2
Presentation File: No File Uploaded


Since the signing of the Great Lakes Water Quality Agreement, Lake Erie decision-making remains fractured across multiple levels of governance. Effective management strategies, that build towards long-term resilience, need to better account for social-ecological system interactions at the watershed level. This research combines social-ecological network (SEN) analysis of cross-level relationships between governance and ecological actors, with spatial analysis of observed water quality monitoring data. Using this combined approach, we analyze how the Lake Erie harmful algal bloom (HABs) governance network (mis)aligns with relevant water quality (Phosphorus and Nitrogen) levels and trends during the 2012-2017 timeframe. By analyzing the socio-spatial relationships between human and physical data, we are able to inform HABs management processes in Lake Erie by identifying areas of weakness and strength from both a governance and water quality perspective in a geospatial context. Our initial findings show: 1) the HABs governance system in the Western and Central Basins of Lake Erie is complex and polycentric; 2) concentrations of key water quality parameters (Phosphorus and Nitrogen) generally increased between 2012 and 2017; 3) there is a correlation between watershed governance network density and water quality levels; and 4) neighboring watersheds that share common actors correlate with higher overall water quality from 2012-2017 than neighboring watersheds that do not share common actors. This combined analytical approach can improve risk reduction and management by identifying areas of HABs management social-ecological (mis)alignment, which can inform where future investment or improvement could be targeted.

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