Large-scale wildlife research studies, such as the Snapshot USA project coordinated by the Smithsonian Institute, offer valuable information on how wildlife communities change across the United States. Such large-scale studies allow for researchers to investigate how mammal communities are affected by landscape variables, such as habitat edge and human development. In our study area of Urbana, Illinois, these two variables convergence at a fine scale, where data collection took place in small forest patches surrounded by an agricultural and exurban landscape in an area that was previously dominated by tall grass prairie. We placed 14 motion-triggered camera traps in forested areas during September and October 2019 and compared our results to deployments in ecologically similar areas. For our comparisons to ecologically similar sites, we grouped Snapshot USA 2019 deployments into a “prairie” or “forest” category based on Bailey’s Prairie and Hot Continental ecoregions. We found a species richness of 15 mammals (Mean = 9.0 ± 0.46; range = 6 - 12) across all Urbana camera sites, while other Snapshot USA sites recorded species richness ranging from 1 to 19. We found that species richness was significantly higher at Urbana sites when compared to prairie sites and that synanthropic species (eastern gray squirrel [Sciurus carolinensis]; northern raccoon [Procyon lotor]; and white-tailed deer [Odocoileus virginianus]) had higher relative abundances in Urbana than forest and prairie sites. These results indicate that the combination of two over-lapping ecoregions and the high percentage of agricultural landcover in Urbana, Illinois may be the reason for the differences seen in mammal communities between the Urbana site and other areas that should have similar communities. If the Snapshot USA project continues with large-scale sampling over many years, this dataset will be an important tool for monitoring changes in wildlife communities across the United States.
|Title of host publication
|81st Midwest Fish and Wildlife Conference
|Published - 2021