Bats (Plecotus auritus) use contact calls for communication among roost mates

Communication between group members is mediated by a diverse range of signals. Contact calls are produced by many species of birds and mammals to maintain group cohesion and associations among individuals. Contact calls in bats are typically relatively low-frequency social calls, produced only for communication. However, echolocation calls (higher in frequency and used primarily for orientation and prey detection) can also facilitate interaction among individuals and location of conspecifics in the roost. We studied calling behaviour of brown long-eared bats (Plecotus auritus) during return to maternity roosts in response to playbacks of social and echolocation calls. We hypothesised that calling by conspecifics would elicit responses in colony members. Bat responses (inspection flights and social calls production) were significantly highest during social call and echolocation call playbacks than during noise (control) playbacks. We suggest that social calling in maternity roosts of brown long-eared bat evolved to maintain associations among roostmates, rather than to find roosts or roostmates, because this species is strongly faithful to roosts and the social groups and roosts are stable over time and space. Living in a stable social group requires recognition of group members and affiliation of social bonds with group members, features that may be mediated by vocal signals.

Acoustic deterrents influence foraging activity, flight and echolocation behaviour of free-flying bats

Acoustic deterrents have shown potential as a viable mitigation measure to reduce human impacts on bats, however, the mechanisms underpinning acoustic deterrence of bats have yet to be explored. Bats avoid ambient ultrasound in their environment and alter their echolocation calls in response to masking noise. Using stereo thermal videogrammetry and acoustic methods, we tested predictions that i) bats would avoid acoustic deterrents and forage and social call less in a ‘treated airspace’; ii) deterrents would cause bats to fly with more direct flight paths akin to commuting behaviour and in line with a reduction in foraging activity, resulting in increased flight speed and decreased flight tortuosity; iii) bats would alter their echolocation call structure in response to the masking deterrent sound. As predicted, overall bat activity was reduced by 30% and we recorded a significant reduction in counts of Pipistrellus pygmaeus (27%), Myotis spp. (probably M. daubentonii) (26%) and Nyctalus and Eptesicus spp. (68%) passes. P. pygmaeus feeding buzzes were also reduced by the deterrent in relation to general activity (by 38%), however social calls were not (only 23% reduction). Bats also increased their flight speed and reduced the tortuosity of their flight paths and P. pygmaeus reduced echolocation call bandwidth and start frequency of calls in response to deterrent playback, probably due to the masking effect of the sound. Deterrence could therefore be used to remove bats from areas where they forage, for example wind turbines and roads, where they may be under threat from direct mortality.

Automated classification of bat echolocation call recordings with artificial intelligence

Acoustic recorders are commonly used to remotely monitor and collect data on bats (Order Chiroptera). These efforts result in many acoustic recordings that must be classified by a bat biologist with expertise in call classification in order to obtain useful information. The rarity of this expertise and time constraints have prompted efforts to automatically classify bat species in acoustic recordings using a variety of learning methods. There are several software programs available for this purpose, but they are imperfect and the United States Fish and Wildlife Service often recommends that a qualified acoustic analyst review bat call identifications even if using these software programs. We sought to build a model to classify bat species using modern computer vision techniques. We used images of bat echolocation calls (i.e., plots of the pulses) to train deep learning computer vision models that automatically classify bat calls to species. Our model classifies 10 species, five of which are protected under the Endangered Species Act. We evaluated our models using standard model validation procedures, but we also performed two out-of-distribution tests. For the out-of-distribution tests, an entire dataset was withheld from the procedure before splitting the data into training and validation sets. We found that our validation accuracy (93%) and out-of-distribution accuracy (90%) were higher than when we used Kaleidoscope Pro and BCID software (65% and 61% accuracy, respectively) to evaluate the same calls. Our results suggest that our approach is effective at classifying bat species from acoustic recordings, and our trained model will be incorporated into new bat call identification software: WEST-EchoVision.

In situ novel environment assay reveals acoustic exploration as a repeatable behavioral response in migratory bats

Integrating information on species-specific sensory perception with spatial activity provides a high-resolution understanding of how animals explore environments, yet frequently used exploration assays commonly ignore sensory acquisition as a measure for exploration. Echolocation is an active sensing system used by hundreds of mammal species, primarily bats. As echolocation call activity can be reliably quantified, bats present an excellent model system to investigate intraspecific variation in environmental cue sampling. Here, we developed an in situ roost-like novel environment assay for tree-roosting bats. We repeatedly tested 52 individuals of the migratory bat species, Pipistrellus nathusii, across 24 h, to examine the role of echolocation when crawling through a maze-type arena and test for consistent intraspecific variation in sensory-based exploration. We reveal a strong correlation between echolocation call activity and spatial activity. Moreover, we show that during the exploration of the maze, individuals consistently differed in spatial activity as well as echolocation call activity, given their spatial activity, a behavioral response we term ’acoustic exploration’. Acoustic exploration was correlated with other exploratory behaviors, but not with emergence latency. We here present a relevant new measure for exploration behavior and provide evidence for consistent (short-term) intra-specific variation in the level at which wild bats collect information from a novel environment.

Description of Echolocation Call Parameters for Urban Bats in Vietnam as a Step Towards a More Integrated Acoustic Monitoring of Urban Wildlife in Southeast Asia

This study is the first step towards more systematic monitoring of urban bat fauna in Vietnam and other Southeast Asian countries by collecting bat echolocation call parameters in Ho Chi Minh and Tra Vinh cities. We captured urban bats and then recorded echolocation calls after releasing in a tent. Additional bat’s echolocation calls from the free-flying bats were recorded at the site where we captured bat. We used the obtained echolocation call parameters for a discriminant function analysis to test the accuracy of classifying these species based on their echolocation call parameters. Data from this pilot work revealed a low level of diversity for the studied bat assemblages. Additionally, the discriminant function analysis successfully classified bats to four bat species with an accuracy of >87.4%. On average, species assignments were correct for all calls from Taphozous melanopogon (100% success rate), for 70% of calls from Pipistrellus javanicus, for 80.8% of calls from Myotis hasseltii and 67.3% of calls from Scotophilus kuhlii. Our study comprises the first quantitative description of echolocation call parameters for urban bats of Vietnam. The success in classifying urban bats based on their echolocation call parameters provides a promising baseline for monitoring the effect of urbanization on bat assemblages in Vietnam and potentially also other Southeast Asian countries.

In situnovel environment assay reveals acoustic exploration as a repeatable behavioral response in migratory bats

Integrating information on species-specific sensory perception together with spatial activity provides a high-resolution understanding of how animals explore environments, yet frequently used exploration assays commonly ignore sensory acquisition as a measure for exploration. Echolocation is an active sensing system used by hundreds of mammal species, primarily bats. As echolocation call activity can be reliably quantified, bats present an excellent animal model to investigate intra-specific variation in environmental cue sampling. Here, we developed anin situroost-like novel environment assay for tree-cave roosting bats. We repeatedly tested 52 individuals of the migratory bat species,Pipistrellus nathusii, across 24 hours, to examine the role of echolocation when crawling through a maze-type arena and test for consistent intra-specific variation in sensory-based exploration. We reveal a strong correlation between echolocation call activity and spatial activity. Moreover, we show that during the exploration of the maze, individuals consistently differed in spatial activity as well as echolocation call activity given their spatial activity, a behavioral response we term ‘acoustic exploration’. Acoustic exploration was correlated with other exploratory behaviors, but not with emergence latency. We here present a relevant new measure for exploration behavior and provide evidence for consistent (short-term) intra-specific variation in the level at which wild bats collect information from a novel environment.

Echolocation call frequency variation in horseshoe bats: molecular basis revealed by comparative transcriptomics

Recently diverged taxa with contrasting phenotypes offer opportunities for unravelling the genetic basis of phenotypic variation in nature. Horseshoe bats are a speciose group that exhibit a derived form of high-duty cycle echolocation in which the inner ear is finely tuned to echoes of the narrowband call frequency. Here, by focusing on three recently diverged subspecies of the intermediate horseshoe bat ( Rhinolophus affinis ) that display divergent echolocation call frequencies, we aim to identify candidate loci putatively involved in hearing frequency variation. We used de novo transcriptome sequencing of two mainland taxa ( himalayanus and macrurus ) and one island taxon ( hainanus ) to compare expression profiles of thousands of genes. By comparing taxa with divergent call frequencies (around 15 kHz difference), we identified 252 differentially expressed genes, of which six have been shown to be involved in hearing or deafness in human/mouse. To obtain further validation of these results, we applied quantitative reverse transcription–PCR to the candidate gene FBXL15 and found a broad association between the level of expression and call frequency across taxa. The genes identified here represent strong candidate loci associated with hearing frequency variation in bats.