Factors impacting bat activity and species richness in protected parks in the oak openings region of Northwest Ohio.

Protected areas are important for wildlife, especially in heavily developed areas. Bats are one group utilizing protected areas, but it is unclear what makes an ideal place for bats to live in parks, especially since preferences vary between open and forest foraging species and at different scales. The main objective of this study was to determine the landscape and vegetation factors at multiple scales most associated with higher bat activity and species richness in protected parks. Total bat activity, species richness, and activity for open and forested foraging species were compared to small-scale data vegetation structure collected in the field and larger-scale landscape data calculated in ArcGIS and FRAGSTATS. Bat activity and species richness increased with higher percentages of dry and open land cover types such as sand barrens, savanna, cropland, and upland prairie and decreased with higher percentages of forest and wet prairies. Patch richness, understory height, and clutter at the 3-6.5 m level were negatively associated with total bat activity. The most important variables for bats differed depending on spatial scale measured and if species were open or forest adapted. When managing for bats in parks, it would be advantageous to restore open land cover types such as savanna and mid-level clutter, and excessive fragmentation. Whether species are open or forest adapted and scale-specific differences should also be considered.

Examining Land Use Changes to Evaluate the Effects of Land Management in a Complex, Dynamic Landscape.

Anthropogenic alterations to landscapes have increased as the human population continues to rise, leading to detrimental changes in natural habitats. Ecological restoration assists in recovery by altering habitats to improve conditions and foster biodiversity. We examined land cover changes over time within a complex, dynamic region in the Midwest to assess the long-term effects of conservation. We used Landsat 8 bands for a 15-class land cover map of Oak Openings Region using supervised classification. We validated our map and achieved an overall accuracy of 71.2% from correctly classified points out of total visited points. Change over 10 years, from 2006 to 2016, was explored by comparing class statistics from FRAGSTATS between our map and original land cover map. We found that natural land, i.e., forest and early successional, covered 33%, with 10% permanently protected, while human-modified land, i.e., agricultural and developed, covered 67% of the region. Over 10 years, natural classes increased, and cultural classes decreased by 5.8%. There were decreases for the three forest communities and increases for the two early successional communities. These changes are likely the result of natural recovery and disturbance, and conservation efforts by the Green Ribbon Initiative. Changes in habitat also came with distribution changes, e.g., increased fragmentation for some classes, which was readily visible. Our useful method measured functionality by emphasizing changes in composition and configuration. Our approach provides a tool for assessing cumulative regional-scale effects from site-level management and conservation. This large-scale view for conservation is needed to effectively mitigate future changes.

A multi-scale spatial analysis of native and exotic plant species richness within a mixed-disturbance oak savanna landscape.

Impacts of human land use pose an increasing threat to global biodiversity. Resource managers must respond rapidly to this threat by assessing existing natural areas and prioritizing conservation actions across multiple spatial scales. Plant species richness is a useful measure of biodiversity but typically can only be evaluated on small portions of a given landscape. Modeling relationships between spatial heterogeneity and species richness may allow conservation planners to make predictions of species richness patterns within unsampled areas. We utilized a combination of field data, remotely sensed data, and landscape pattern metrics to develop models of native and exotic plant species richness at two spatial extents (60- and 120-m windows) and at four ecological levels for northwestern Ohio's Oak Openings region. Multiple regression models explained 37-77 % of the variation in plant species richness. These models consistently explained more variation in exotic richness than in native richness. Exotic richness was better explained at the 120-m extent while native richness was better explained at the 60-m extent. Land cover composition of the surrounding landscape was an important component of all models. We found that percentage of human-modified land cover (negatively correlated with native richness and positively correlated with exotic richness) was a particularly useful predictor of plant species richness and that human-caused disturbances exert a strong influence on species richness patterns within a mixed-disturbance oak savanna landscape. Our results emphasize the importance of using a multi-scale approach to examine the complex relationships between spatial heterogeneity and plant species richness.