In recent decades, harmful algal blooms (HABs) have increased significantly in Lake Erie. The blooms can affect human health, aquatic ecosystems, and the local economy. The effects can vary across communities in the Lake Erie Basin due to local socioeconomic status and dependence on lake resources. Therefore, it is crucial to identify HAB-vulnerable populations and regions to adjust regional governance strategies and allocate resources for government support. This study introduces a 5-theme spatial HAB vulnerability index (HAB-VI) comprised of socioeconomic, resource dependence, and spatial factors affecting vulnerability to HAB events. Using a multi-factor hierarchical model, it also applies the index to evaluate the HAB-related vulnerabilities of 50 counties in the Lake Erie Basin. Uncertainty analysis is an essential step to assess the robustness of the model and the stability of the calculated indices. The research utilizes a Monte Carlo-based uncertainty analysis and visualizes the statistical results of the simulation runs to indicate the variability and reliability of the HAB-VI rankings. Comparing thematic maps of the generated HAB-VI rankings, indicators of local governance strength, and nonpoint nutrient loads provides further insights into prioritizing the regions for government support and building community resilience.
Design and Use of a Spatial Harmful Algal Bloom Vulnerability Index for Informing Environmental Policy and Advancing Environmental Justice
Abstract
Publication Type
Journal Article
Date
Journal
Applied Spatial Analysis and Policy
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D.G. Webster
Semra Aytur
Article published in Sustainability
Article published in Journal of Public Administration Research and Theory