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Ohio is an eastern USA state that historically was >70% covered in upland and mixed coniferous forest; about 60% of it glaciated by the Wisconsinan glacial episode. Its stonefly fauna has been studied in piecemeal fashion until now. The assemblage of Ohio stoneflies was assessed from over 4,000 records accumulated from 18 institutions, new collections, and trusted literature sources. Species richness totaled 102 with estimators Chao2 and ICE Mean predicting 105.6 and 106.4, respectively. Singletons and doubletons totaled 18 species. All North American families were represented with Perlidae accounted for the highest number of species at 34. The family Peltoperlidae contributed a single species. Most species had univoltine–fast life cycles with the vast majority emerging in summer, although there was a significant component of winter stoneflies. Nine United States Geological Survey hierarchical drainage units level 6 (HUC6) were used to stratify specimen data. Species richness was significantly related to the number of unique HUC6 locations, but there was no relationship with HUC6 drainage area. A nonparametric multidimensional scaling analysis found that larger HUC6s in the western part of the state had similar assemblages with lower species richness that were found to align with more savanna and wetland habitat. Other drainages having richer assemblages were aligned with upland deciduous and mixed coniferous forests of the east and south where slopes were higher. The Ohio assemblage was most similar to the well–studied fauna of Indiana (88 spp.) and Kentucky (108 spp.), two neighboring states. Many rare species and several high quality stream reaches should be considered for greater protection.

To effectively conserve and restore stream ecosystems, we need to better understand the distribution and abundance of individual fish species in relation to natural environments and anthropological stressors. In this study, we modeled the abundance of 97 fish species in small wadeable streams of Illinois, USA, based on random forests regression and landscape-level environmental variables. Model R2 values for intermediately common species were higher than for common species, but highly variable among rare ones. Models for 50 species reached R2 of 0.2–0.70 and were tested with a separate set of samples and applied to unsampled wadeable reaches to show the population hotspots of each species across the state. Furthermore, we evaluated the importance of individual environmental variables to a given fish species as well as the directional responses of each species to top 10 key predictors. Climate and land use were the best predictors for most species, followed by topography, geology, and soil permeability. Spatial connection of a stream also was associated with a large number of species. These findings improved our understanding of the relationships between fish species and landscape environments. The distribution maps could guide resource management, restoration, and monitoring of stream fish assemblages.

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This research is a product of the graduate program in Biological Sciences at Eastern Illinois University. Find out more about the program.