In recent decades, aquatic ecosystem conditions have been monitored using a tool known as an index of biotic integrity (IBI). An IBI combines taxon-specific metrics into one score for easy interpretation of ecosystem health. The Great Lakes are an example of a highly monitored ecosystem where the Great Lakes Coastal Wetland Monitoring Program (CWMP) uses multiple taxonomic IBIs for assessing conditions in over 1,000 coastal wetlands. The program monitors fishes, macroinvertebrates, birds, and vegetation to get one IBI per taxa group. This method provides us with a more detailed look at wetland conditions, though having multiple IBI scores can cause complications when variation occurs across taxa IBIs. The goal of this study was to develop an approach for understanding cross-taxa IBI variation to better understand wetland conditions. We modeled the four CWMP IBIs against a set of environmental variables to determine influences on IBI scores and variation among IBIs. Our results indicate that each taxonomic group was influenced by a different set of environmental variables. Water level fluctuations, land cover, and local wetland characteristics all influenced each of the taxonomic IBIs in varying ways, which helps explain IBI variation. Understanding the environmental influences on each taxonomic IBI will allow restoration managers to build site-specific restoration targets that better align with ecological objectives.
