Camera traps with white flash are a minimally invasive method for long‐term bat monitoring

Abstract

AbstractCamera traps are an increasingly popular survey tool for ecological research and biodiversity conservation, but studies investigating their impact on focal individuals have been limited to only a few mammal species. In this context, echolocating bats are particularly interesting as they rely less on vision for navigation, yet show a strong negative reaction to constant illumination. At hibernacula, camera traps with white flash could offer an efficient alternative method for monitoring threatened bat species, but the potential negative impact of white flash on bat behavior is unknown. Here, we investigate the effect of camera traps emitting white flash at four hibernation sites fitted with infrared light barriers, infrared video cameras, and acoustic recorders over 16 weeks. At each site, the flash was turned off every second week. We quantified whether flash affected (1) nightly bat passes using generalized linear mixed models, (2) flight direction of entering bats using permutational multivariate analyses, and (3) latency of the first echolocation call after the camera trap trigger using randomization tests. Additionally, we quantified and corrected for the potential impact of confounding factors, such as weather and social interactions. Overall, white flash did not influence short‐ or long‐term bat activity, flight direction or echolocation behavior. A decrease in nightly bat activity was observed with an increasing proportion of hours with rain. Moreover, flight direction was affected by the presence of other bats, likely due to chasing and avoidance behavior. Our findings highlight the potential of camera traps with white flash triggered by infrared light barriers as a minimally invasive method for long‐term bat population monitoring and observation of species‐specific phenology. Such automated monitoring technologies can improve our understanding of long‐term population dynamics across a wide range of spatial‐temporal scales and taxa and consequently, contribute to data‐driven wildlife conservation and management.