White-nose syndrome (WNS) has emerged as the most serious threat to North American cave-dwelling bat species, with an estimated mortality of over 6 million since it was first documented in the USA in 2006. Tri-colored bat Perimyotis subflavus is one of the species most affected, with hibernaculum counts at caves in WNS-positive regions reduced by >90% from previous counts. While declines have been documented in hibernaculum surveys, long-term monitoring programs during active seasons provide a unique opportunity to examine population trends and impact of population declines post-WNS. We developed generalized linear mixed models using data from a state-wide, long-term (2011-2020) mobile bat acoustic monitoring program in Georgia, USA, to better understand P. subflavus population trends before and after disease detection and between WNS-negative and WNS-positive regions. We recorded 5046 P. subflavus passes across all acoustic routes during the 10 yr time period. We detected a significant decrease in activity 2 yr after disease detection in the WNS-positive region, whereas activity in the WNS-negative region remained stable over time. Understanding changes in bat populations as WNS spreads and measuring the magnitude of population declines to assess disease impacts is crucial for providing appropriate guidance for management. Our results provide evidence of the critical status of P. subflavus in the southernmost WNS-positive region, but also emphasize the importance of monitoring WNS spread to new regions, as those that remain WNS-free could provide refugia for the species and a potential source of recolonization to WNS-affected areas.

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There has been an increase in commercial bat detectors and noise filtering software for monitoring bat activity. In this study, we compare the recording efficiency of three bat detectors from the popular brand Wildlife Acoustics (Echo Meter 3, Echo Meter Touch Pro 1 and Song Meter 2 BAT) and the effectiveness of two noise filtering software (Kaleidoscope and SonoBat Batch Scrubber). To do so, we recorded 7513 files from 13 urban parks in Madrid in 2017, that were manually identified to species level. The results show that the Echo Meter 3 records significantly less activity than the Echo Meter Touch Pro 1 and Song Meter 2 BAT. Our results also identify SonoBat Batch Scrubber as more reliable than Kaleidoscope for preventing false negatives. Therefore, our study demonstrates that different bat detectors, and different noise filtering software, can provide different results.

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