Visual cues enhance obstacle avoidance in echolocating bats

Ventral wing hairs provide tactile feedback for aerial prey capture in the big brown bat, Eptesicus fuscus

Bats rely on their hand-wings to execute agile flight maneuvers, to grasp objects, and cradle young. Embedded in the dorsal and ventral membranes of bat wings are microscopic hairs. Past research findings implicate dorsal wing hairs in airflow sensing for flight control, but the function of ventral wing hairs has not been previously investigated. Here, we test the hypothesis that ventral wing hairs carry mechanosensory signals for flight control, prey capture, and handling. To test this hypothesis, we used synchronized high-speed stereo video and audio recordings to quantify flight and echolocation behaviors of big brown bats (Eptesicus fuscus) engaged in an aerial insect capture task. We analyzed prey-capture strategy and performance, along with flight kinematics, before and after depilation of microscopic hairs from the bat's ventral wing and tail membranes. We found that ventral wing hair depilation significantly impaired the bat's prey-capture performance. Interestingly, ventral wing hair depilation also produced increases in the bat's flight speed, an effect previously attributed exclusively to airflow sensing along the dorsal wing surface. These findings demonstrate that microscopic hairs embedded in the ventral wing and tail membranes of insectivorous bats provide mechanosensory feedback for prey handling and flight control.

Daubenton's bats maintain stereotypical echolocation behaviour and a lombard response during target interception in light

Most bats hunt insects on the wing at night using echolocation as their primary sensory modality, but nevertheless maintain complex eye anatomy and functional vision. This raises the question of how and when insectivorous bats use vision during their largely nocturnal lifestyle. Here, we test the hypothesis that the small insectivorous bat, Myotis daubentonii, relies less on echolocation, or dispenses with it entirely, as visual cues become available during challenging acoustic noise conditions. We trained five wild-caught bats to land on a spherical target in both silence and when exposed to broad-band noise to decrease echo detectability, while light conditions were manipulated in both spectrum and intensity. We show that during noise exposure, the bats were almost three times more likely to use multiple attempts to solve the task compared to in silent controls. Furthermore, the bats exhibited a Lombard response of 0.18 dB/dBnoise and decreased call intervals earlier in their flight during masking noise exposures compared to in silent controls. Importantly, however, these adjustments in movement and echolocation behaviour did not differ between light and dark control treatments showing that small insectivorous bats maintain the same echolocation behaviour when provided with visual cues under challenging conditions for echolocation. We therefore conclude that bat echolocation is a hard-wired sensory system with stereotyped compensation strategies to both target range and masking noise (i.e. Lombard response) irrespective of light conditions. In contrast, the adjustments of call intervals and movement strategies during noise exposure varied substantially between individuals indicating a degree of flexibility that likely requires higher order processing and perhaps vocal learning.

Adaptive echolocation behavior of bats and toothed whales in dynamic soundscapes

Journal of Experimental Biology has a long history of reporting research discoveries on animal echolocation, the subject of this Centenary Review. Echolocating animals emit intense sound pulses and process echoes to localize objects in dynamic soundscapes. More than 1100 species of bats and 70 species of toothed whales rely on echolocation to operate in aerial and aquatic environments, respectively. The need to mitigate acoustic clutter and ambient noise is common to both aerial and aquatic echolocating animals, resulting in convergence of many echolocation features, such as directional sound emission and hearing, and decreased pulse intervals and sound intensity during target approach. The physics of sound transmission in air and underwater constrains the production, detection and localization of sonar signals, resulting in differences in response times to initiate prey interception by aerial and aquatic echolocating animals. Anti-predator behavioral responses of prey pursued by echolocating animals affect behavioral foraging strategies in air and underwater. For example, many insect prey can detect and react to bat echolocation sounds, whereas most fish and squid are unresponsive to toothed whale signals, but can instead sense water movements generated by an approaching predator. These differences have implications for how bats and toothed whales hunt using echolocation. Here, we consider the behaviors used by echolocating mammals to (1) track and intercept moving prey equipped with predator detectors, (2) interrogate dynamic sonar scenes and (3) exploit visual and passive acoustic stimuli. Similarities and differences in animal sonar behaviors underwater and in air point to open research questions that are ripe for exploration.

Combining acoustic tracking and LiDAR to study bat flight behaviour in three-dimensional space

BACKGROUND

Habitat structure strongly influences niche differentiation, facilitates predator avoidance, and drives species-specific foraging strategies of bats. Vegetation structure is also a strong driver of echolocation call characteristics. The fine-scale assessment of how bats utilise such structures in their natural habitat is instrumental in understanding how habitat composition shapes flight- and acoustic behaviour. However, it is notoriously difficult to study their species-habitat relationship in situ.

METHODS

Here, we describe a methodology combining Light Detection and Ranging (LiDAR) to characterise three-dimensional vegetation structure and acoustic tracking to map bat behaviour. This makes it possible to study fine-scale use of habitat by bats, which is essential to understand spatial niche segregation in bats. Bats were acoustically tracked with microphone arrays and bat calls were classified to bat guild using automated identification. We did this in multiple LiDAR scanned vegetation plots in forest edge habitat. The datasets were spatially aligned to calculate the distance between bats' positions and vegetation structures.

RESULTS

Our results are a proof of concept of combining LiDAR with acoustic tracking. Although it entails challenges with combining mass-volumes of fine-scale bat movements and vegetation information, we show the feasibility and potential of combining those two methods through two case studies. The first one shows stereotyped flight patterns of pipistrelles around tree trunks, while the second one presents the distance that bats keep to the vegetation in the presence of artificial light.

CONCLUSION

By combining bat guild specific spatial behaviour with precise information on vegetation structure, the bat guild specific response to habitat characteristics can be studied in great detail. This opens up the possibility to address yet unanswered questions on bat behaviour, such as niche segregation or response to abiotic factors in interaction with natural vegetation. This combination of techniques can also pave the way for other applications linking movement patterns of other vocalizing animals and 3D space reconstruction.

Night skies through animals' eyes-Quantifying night-time visual scenes and light pollution as viewed by animals

A large proportion of animal species enjoy the benefits of being active at night, and have evolved the corresponding optical and neural adaptations to cope with the challenges of low light intensities. However, over the past century electric lighting has introduced direct and indirect light pollution into the full range of terrestrial habitats, changing nocturnal animals' visual worlds dramatically. To understand how these changes affect nocturnal behavior, we here propose an animal-centered analysis method based on environmental imaging. This approach incorporates the sensitivity and acuity limits of individual species, arriving at predictions of photon catch relative to noise thresholds, contrast distributions, and the orientation cues nocturnal species can extract from visual scenes. This analysis relies on just a limited number of visual system parameters known for each species. By accounting for light-adaptation in our analysis, we are able to make more realistic predictions of the information animals can extract from nocturnal visual scenes under different levels of light pollution. With this analysis method, we aim to provide context for the interpretation of behavioral findings, and to allow researchers to generate specific hypotheses for the behavior of nocturnal animals in observed light-polluted scenes.

Sensory error drives fine motor adjustment

Fine audiovocal control is a hallmark of human speech production and depends on precisely coordinated muscle activity guided by sensory feedback. Little is known about shared audiovocal mechanisms between humans and other mammals. We hypothesized that real-time audiovocal control in bat echolocation uses the same computational principles as human speech. To test the prediction of this hypothesis, we applied state feedback control (SFC) theory to the analysis of call frequency adjustments in the echolocating bat, Hipposideros armiger. This model organism exhibits well-developed audiovocal control to sense its surroundings via echolocation. Our experimental paradigm was analogous to one implemented in human subjects. We measured the bats' vocal responses to spectrally altered echolocation calls. Individual bats exhibited highly distinct patterns of vocal compensation to these altered calls. Our findings mirror typical observations of speech control in humans listening to spectrally altered speech. Using mathematical modeling, we determined that the same computational principles of SFC apply to bat echolocation and human speech, confirming the prediction of our hypothesis.

Social Communication in Big Brown Bats

Bats are social mammals that display a wide array of social communication calls. Among them, it is common for most bats species to emit distress, agonistic, appeasement and infant isolation calls. Big brown bats (Eptesicus fuscus) are no different: They are gregarious animals living in colonies that can comprise hundreds of individuals. These bats live in North America and, typically found roosting in man-made structures like barns and attics, are considered common. They are insectivorous laryngeal echolocators, and while their calls and associated brain mechanisms in echolocation are well-documented, much less is known about their neural systems for analyzing social vocalizations. In this work we review what we know about the social lives of big brown bats and propose how to consolidate the nomenclature used to describe their social vocalizations. Furthermore, we discuss the next steps in the characterization of the social structure of this species and how these studies will advance both research in neuroethology and ecology of big brown bats.

Bats: Vision or echolocation, why not both?

Echolocation allows bats to navigate in complete darkness. Yet, some bats also have keen eyesight. A new study shows that bats integrate these sensory modalities, even when light abundance would make it possible for them to rely solely on vision.