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Abstract Bat population estimates are typically made during winter, although this is only feasible for bats that aggregate in hibernacula. While it is essential to measure summer bat population sizes for management, we lack a reliable method. Acoustic surveys should be less expensive and more efficient than capture surveys, and acoustic activity data are already used as indices of population size. Although we currently cannot differentiate individual bats by their calls, we can enter call counts, information on signal and detection angles, and weather data into generalized random encounter models to estimate bat density. We assessed the utility of generalized random encounter models for estimating Indiana bat (Myotis sodalis) population density with acoustic data collected at 51 total sites in six conservation areas in northeast Missouri, 2019–2021. We tested the effects of year, volancy period, conservation area, and their interactions on estimated density. Volancy period was the best predictor, with average predicted density increasing 60% from pre‐volancy (46 bats/km2) to post‐volancy (74 bats/km2); however, the magnitude of the effect differed by conservation area. We showed that passive acoustic surveys yield informative density estimates that are responsive to temporal changes in bat population size, which suggests this method may be useful for long‐term monitoring. However, we need more information to choose the most appropriate values for the density estimation formula. Future work to refine this approach should include assessments of bat behavior and detection parameters and testing the method's efficacy in areas where population sizes are known.

Wind energy is a growing source of renewable energy with a 3-fold increase in use globally over the last decade. However, wind turbines cause bat mortality, especially for migratory species. The southwest United States has high bat species diversity and is an important area for migratory species, although little is known about their seasonal distribution. To examine potential risk to bats in areas proposed for wind energy development, we characterized bat occupancy spatially and temporally across northern Arizona, identifying use during summer when bats are reproductively active and fall during the migratory season. Our objectives were to determine occupancy of migratory species and species of greatest conservation need and develop a probability of occupancy map for species to identify areas of potential conflict with wind energy development. We selected 92 sites in 10 clusters with potential for development and used acoustic detectors to sample bats in the summer and fall of 2016 and 2017 for 6 nights per site per year. We predicted response of migratory bat species and species of special concern to 9 landscape variables using Program MARK. During summer, higher densities of forest on the landscape resulted in a higher probability of occupancy of migratory species such as hoary bats (Lasiurus cinereus), silver-haired bats (Lasionycteris noctivagans), big free-tailed bats (Nyctinomops macrotis), and species of conservation need such as spotted bats (Euderma maculatum). During the fall, higher concentration of valleys on the landscape predicted occupancy of hoary bats, big free-tailed bats, and spotted bats. High bat occupancy in the fall was also associated with higher elevation and close proximity to forests. We recommend that wind turbines be placed in open, flat grasslands away from forested landscapes and concentrations of valleys or other topographic variation.

ABSTRACT Many land‐management agencies are restoring savannas and woodlands using prescribed fire and forest thinning, and information is needed on how wildlife species respond to these management activities. Our objectives were to evaluate support for relationships of bat site occupancy with vegetation structure and management and landscape composition and structure across a gradient of savanna to forest in the Missouri Ozark Highlands, USA. We selected study sites that were actively managed for savanna and woodland conditions and control areas on similar landforms that had succeeded to closed‐canopy forest. We used Anabat detectors to survey bats during the summers of 2010, 2011, and 2012. We fit single‐species site‐occupancy models to estimate detection probability and site occupancy. We evaluated a priori hypotheses in an information theoretic approach by evaluating support for candidate models that included habitat, landscape, and management effects. Site occupancy of evening bats (Nycticeius humeralis) was negatively related to poletimber and sawtimber density and positively related to fire frequency, while northern long‐eared bat (Myotis septentrionalis) site occupancy was positively related to poletimber density and negatively related to understory stem densities. Site occupancy of big brown bats (Eptesicus fuscus), eastern red bats (Lasiurus borealis), and tri‐colored bats (Perimyotis subflavus) were mostly not related to local vegetation structure and site occupancy was high across the savanna, woodland, forest gradient. We found more consistent and larger effect sizes for landscape‐scale than for habitat‐scale relationships; therefore, land managers should be cognizant of large‐scale patterns in land cover when making local management decisions for these species. Published 2014. This article is a U.S. Government work and is in the public domain in the USA.

Bats are among the most widespread mammals on Earth, and are subject to habitat change, loss, and other disturbances such as fire. Wildfire causes rapid changes in vegetation that affect habitat use. However, the spatial scale at which these changes affect bats depends on their use of habitat elements. Three years post wildfire, we assessed how burn severity, water, landform type, elevation, vegetation type, and roads affected use by bats of a forest landscape at multiple spatial scales. We deployed acoustic detectors at randomly selected locations within a 217,712 ha wildfire boundary in Arizona. We classified echolocation calls to species or group and calculated an activity index by adjusting the calls per hour. We conducted a multi-scale analysis of landscape structure and composition around each location from a 90 to 5760 m radius. No scale was selected preferentially by any species or group. Stream density and elevation range were more important predictors for species groups than burn severity. When burn severity was a predictor, agile species had higher activity in areas that were unburned or had low severity burn. A heterogeneous landscape composed of high, medium, and low burn severity patches within a forest altered by large wildfires provided habitat for different bat species, but water density and range in elevation were more important for predicting bat habitat use than fire severity in this arid landscape. More than one spatial scale, representing local to landscape levels, should be considered in managing habitat for bats. In arid areas, such as the western United States, maintaining reliable water sources is important for bats. Managing these factors at multiple spatial scales will benefit bat species with different wing morphologies, echolocation call types, and habitat selections.