Long-term video surveillance and automated analyses reveal arousal patterns in groups of hibernating bats
Methods in Ecology and Evolution
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- Data Release: Long-term video surveillance and automated analyses of hibernating bats in Virginia and Indiana, winters 2011-2014
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Abstract
- Understanding natural behaviours is essential to determining how animals deal with new threats (e.g. emerging diseases). However, natural behaviours of animals with cryptic lifestyles, like hibernating bats, are often poorly characterized. White-nose syndrome (WNS) is an unprecedented disease threatening multiple species of hibernating bats, and pathogen-induced changes to host behaviour may contribute to mortality. To better understand the behaviours of hibernating bats and how they might relate to WNS, we developed new ways of studying hibernation across entire seasons.
- We used thermal-imaging video surveillance cameras to observe little brown bats (Myotis lucifugus) and Indiana bats (M. sodalis) in two caves over multiple winters. We developed new, sharable software to test for autocorrelation and periodicity of arousal signals in recorded video.
- We processed 740 days (17,760 hr) of video at a rate of >1,000 hr of video imagery in less than 1 hr using a desktop computer with sufficient resolution to detect increases in arousals during midwinter in both species and clear signals of daily arousal periodicity in infected M. sodalis.
- Our unexpected finding of periodic synchronous group arousals in hibernating bats demonstrate the potential for video methods and suggest some bats may have innate behavioural strategies for coping with WNS. Surveillance video and accessible analysis software make it now practical to investigate long-term behaviours of hibernating bats and other hard-to-study animals.
| Publication type | Article |
|---|---|
| Publication Subtype | Journal Article |
| Title | Long-term video surveillance and automated analyses reveal arousal patterns in groups of hibernating bats |
| Series title | Methods in Ecology and Evolution |
| DOI | 10.1111/2041-210X.12823 |
| Volume | 8 |
| Issue | 12 |
| Year Published | 2017 |
| Language | English |
| Publisher | British Ecological Society |
| Contributing office(s) | Fort Collins Science Center |
| Description | 9 p. |
| First page | 1813 |
| Last page | 1821 |
| Google Analytic Metrics | Metrics page |