Bat occupancy of forests and managed savanna and woodland in the Missouri Ozark Region

Starbuck, Clarissa A.

doi:10.32469/10355/43155

Cited by 3 publications

(4 citation statements)

References 37 publications

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“…Indiana/little brown and northern long-eared bats showed a negative relationship between detection and relative humidity levels, which can increase attenuation of echolocation calls (Griffin 1971, Livengood 2003. These results are in contrast to findings of Starbuck (2013).…”

Section: Detectioncontrasting

confidence: 99%

“…Eastern red bats showed a conflicting influence of temperature and dew point on detection across years. Detection was negatively related to forest clutter for most species, which is similar to findings of others (Starbuck 2013, O'Keefe et al 2014). We did not find similar results to Kaiser and O'Keefe (2015) who noted greater detection of Indiana bats in areas of higher clutter, perhaps because this species was not abundant on our study site (Sheets et al 2013).…”

Section: Detectionsupporting

confidence: 89%

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A Comparison of Bat Activity in a Managed Central Hardwood Forest

Caldwell

Carter

Doll

2019

The American Midland Naturalist

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Bats exploit forest resources based on species-specific adaptations, resulting in differences in activity across forested landscapes. Forest management practices alter forests, impacting species differently and presumably affecting bat activity. Application of forest management that promotes bat conservation requires further understanding of bat response to silvicultural practices. We surveyed timber harvest treatments on two Indiana State Forests to compare bat activity across forest management treatments, in forests adjacent to harvests, and at locations across the harvest-forest gradient from May to July 2013 and 2014. We used Wildlife Acoustics Song Meter SM2BAT+ detectors to survey bats in relation to four treatment types: clear cut, patch cut, shelterwood cut, and intact forest. Detectors were deployed at two points within each treatment and three points on the forested periphery of treatments and recorded for three consecutive nights. We examined bat activity using N-mixture models that estimate abundance and probability of detection for an open population and used Akaike's Information Criterion to select the best models. Eastern red bats and hoary bats were more active in harvest treatments than control treatments. Big brown, eastern red, and tri-colored bats were most active at harvest edges. Northern long-eared and Indiana/little brown bats were most active at harvest edges and in adjacent forest and hoary bats were most active at harvest centers. All species were active in forests adjacent to harvests. Variables affecting detection probability differed among species and included air temperature, relative humidity, barometric pressure, dew point, cloud cover, wind speed, and forest clutter. Differences in bat activity across these managed forests suggest bat assemblages benefit from management that employs an array of silvicultural methods, provides edge habitat, and maintains adjacent forest stands. Our results can be used to predict effects of forest management practices on bat activity to maximize bat usage of forests. have a long list of people to thank for getting me through it. Firstly, I thank my advisor, Dr. Tim Carter for his endless support, patience, and mentorship at every stage of this process. Not many major professors willingly lead the charge into a briar-filled clear cut on their birthday to help a student collect data, but I was lucky enough to have one that did. I also thank my committee members, Dr. Joy O'Keefe and Dr. Mark Pyron for their willingness to edit my thesis and attend my defense with less than two weeks notice and for their input and advice throughout the project. My parents, Paul and Alyson Caldwell, and sister Sara Beth Caldwell are the backbone of any success I have ever achieved and graduate school was no different. I thank them for tolerating my lack of participation in family events due to writing and for doing everything possible to unburden me of stress. I thank my boyfriend, Luke Etchison, for supporting me through every thesis-related meltdown, helping me trade ...

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Section: Detectioncontrasting

confidence: 99%

Section: Detectionsupporting

confidence: 89%

A Comparison of Bat Activity in a Managed Central Hardwood Forest

Caldwell

Carter

Doll

2019

The American Midland Naturalist

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“…LAIN, EPFULANO, and TABR are considered openadapted species (Menzel et al 2005;Loeb and O'Keefe 2006) and we accordingly found negative effects of increasing vegetation clutter for these species. Myotis species are considered clutter-adapted species Starbuck 2013), and accordingly, we found the probability of detecting MYLELUSE was very high at high-clutter stationary points and low at low-and medium-clutter stationary points and along mobile transects. However, it must be noted that for modeling purposes it was necessary to combine all Myotis detections other than those of MYAU.…”

Section: Discussionmentioning

confidence: 58%

“…Bat activity tends to increase with increasing temperature (O'Donnell 2000;Broders et al 2006;Kitzes and Merenlender 2014;Wolbert et al 2014); therefore, we hypothesized that the probability of detection for all species would increase as temperature increased. Relative humidity affects the attenuation of sound waves (Bass et al 1990) and may both positively and negatively affect the detection of bats (Starbuck 2013). Thus, we tested whether it had an effect for any species in our surveys.…”

Section: Species Amentioning

confidence: 99%

Implementing and Assessing the Efficacy of the North American Bat Monitoring Program

Neece

Loeb

Jachowski

2019

Journal of Fish and Wildlife Management

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Bats are under threat from habitat loss, energy development, and the disease white-nose syndrome; therefore, an efficient and effective means to monitor bat populations is needed. The North American Bat Monitoring Program (NABat) was initiated in 2015 to provide standardized, large-scale monitoring to benefit bat biologists, managers, and policy makers. Given the recency of this program, our first objective was to determine the efficacy of implementing NABat. Further, because the probability of detecting a bat varies among species and survey conditions, our second objective was to determine factors affecting detection probabilities of bats using NABat acoustic surveys. We conducted surveys across South Carolina from mid-May through July 2015 and 2016. To determine efficacy of NABat, we compared species detections with historical known distributions and predicted distributions based on environmental occupancy models. To determine factors that affected detection probability, we evaluated support for predictive detection models for each species or species grouping. In general, we found that predicted distributions closely matched known distributions. However, we detected some species in ≤50% of cells within their ranges and others outside their ranges, suggesting NABat may also reveal new information about species distributions. Most species had higher detection probabilities at stationary points than mobile transects, but the influence of interrupted surveys, environmental conditions (e.g., temperature, rainfall, and wind) and habitat conditions often varied among species. Overall, our results suggest NABat is an effective and efficient method for monitoring many bat species, but we suggest that future efforts account for species-specific biological and behavioral characteristics influencing detection probability.

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