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.

Testing the hypothesis of hierarchical predictability in ecological restoration and succession

To advance predictive ecology, the hypothesis of hierarchical predictability proposes that community measures for which species are interchangeable (e.g., structure and species richness) are more predictable than measures for which species identity matters (e.g., community composition). Predictability is hypothesized to decrease for response measures in order of the following categories: structure, species richness, function, and species composition. We tested this hypothesis using a 14-year, oak savanna-prairie restoration experiment that removed non-native pine plantations at 24 sites in northwestern Ohio, USA. Based on 24 response measures, the data showed minimal support for the hypothesis, because response measures varied in predictability within categories. Half of response measures had over half their variability modeled using fixed (restoration treatment and year) and random plot effects, and these "predictable" measures occurred in all four categories. Pine basal area, environment (e.g., soil texture), and antecedent vegetation accounted for over half the variation in change within the first three post-restoration years for 77% of response measures. Change between the 3rd and 14th years was less predictable, but most restoration measures increased favorably via sites achieving them in unique ways. We propose that variation will not conform with the hypothesis of hierarchical predictability in ecosystems with vegetation dynamics driven by stochastic processes such as seed dispersal, or where vegetation structure and species richness are influenced by species composition. The ability to predict a community measure may be more driven by the number of combinations of casual factors affecting a measure than by the number of values it can have.