What a plant sounds like: the statistics of vegetation echoes as received by echolocating bats

Small-scale location identification in natural environments with deep learning based on biomimetic sonar echoes

Many bat species navigate in complex, heavily vegetated habitats. To achieve this, the animal relies on a sensory basis that is very different from what is typically done in engineered systems that are designed for outdoor navigation. Whereas the engineered systems rely on data-heavy senses such as lidar, bats make do with echoes triggered by short, ultrasonic pulses. Prior work has shown that 'clutter echoes' originating from vegetation can convey information on the environment they were recorded in-despite their unpredictable nature. The current work has investigated the spatial granularity that these clutter echoes can convey by applying deep-learning location identification to an echo data set that resulted from the dense spatial sampling of a forest environment. The Global Positioning System (GPS) location corresponding to the echo collection events was clustered to break the survey area into the number of spatial patches ranging from two to 100. A convolutional neural network (Resnet 152) was used to identify the patch associated with echo sets ranging from one to ten echoes. The results demonstrate a spatial resolution that is comparable to the accuracy of recreation-grade GPS operating under foliage cover. This demonstrates that fine-grained location identification can be accomplished at very low data rates.

A validation study for a bat-inspired sonar sensing simulator

Many species of bats rely on echoes to forage and navigate in densely vegetated environments. Foliage echoes in some cases can help bats gather information about the environment, whereas in others may generate clutter that can mask prey echoes during foraging. It is therefore important to study foliage echoes and their role in bat's sensory ecology. In our prior work, a foliage echo simulator has been developed; simulated echoes has been compared with field recordings using a biomimetic sonar head. In this work, we improve the existing simulator by allowing more flexible experimental setups and enabling a closer match with the experiments. Specifically, we add additional features into the simulator including separate directivity patterns for emitter and receiver, the ability to place emitter and receiver at distinct locations, and multiple options to orient the foliage to mimic natural conditions like strong wind. To study how accurately the simulator can replicate the real echo-generating process, we compare simulated echoes with experimental echoes measured by ensonifying a single leaf across four different species of trees. We further extend the prior work on estimating foliage parameters to estimating a map of the environment.

Acoustic traits of bat-pollinated flowers compared to flowers of other pollination syndromes and their echo-based classification using convolutional neural networks

Bat-pollinated flowers have to attract their pollinators in absence of light and therefore some species developed specialized echoic floral parts. These parts are usually concave shaped and act like acoustic retroreflectors making the flowers acoustically conspicuous to the bats. Acoustic plant specializations only have been described for two bat-pollinated species in the Neotropics and one other bat-dependent plant in South East Asia. However, it remains unclear whether other bat-pollinated plant species also show acoustic adaptations. Moreover, acoustic traits have never been compared between bat-pollinated flowers and flowers belonging to other pollination syndromes. To investigate acoustic traits of bat-pollinated flowers we recorded a dataset of 32320 flower echoes, collected from 168 individual flowers belonging to 12 different species. 6 of these species were pollinated by bats and 6 species were pollinated by insects or hummingbirds. We analyzed the spectral target strength of the flowers and trained a convolutional neural network (CNN) on the spectrograms of the flower echoes. We found that bat-pollinated flowers have a significantly higher echo target strength, independent of their size, and differ in their morphology, specifically in the lower variance of their morphological features. We found that a good classification accuracy by our CNN (up to 84%) can be achieved with only one echo/spectrogram to classify the 12 different plant species, both bat-pollinated and otherwise, with bat-pollinated flowers being easier to classify. The higher classification performance of bat-pollinated flowers can be explained by the lower variance of their morphology.

Biomimetic detection of dynamic signatures in foliage echoes

Certain bat species (familyRhinolophidae) dynamically deform their emission baffles (noseleaves) and reception baffles (pinnae) during echolocation. Prior research using numerical models, laboratory characterizations, and experiments with simple targets have suggested that this dynamics may manifest itself in time-variant echo signatures. Since the pronounced random nature of echoes from natural targets such as foliage has not been reflected in these experiments, we have collected a large number (>55 000) of foliage echoes outdoors with a sonar head that mimics the dynamic periphery in bats. The echo data was processed with a custom auditory processing model to create spike-based echo representations. Deep-learning classifiers were able to estimate the dynamic state of the periphery, i.e., static or dynamic, based on single echoes with accuracies of up to 80%. This suggests that the effects of the peripheral dynamics are present in the bat brains and could hence be used by the animals. The best classification performances were obtained for data obtained within a spatially confined area. Hence, if the bat brains suffer from the same generalization issues, they would have to have a way to adapt their neural echo processing to such local fluctuations to exploit the dynamic effects successfully.

Echolocating bats detect but misperceive a multidimensional incongruent acoustic stimulus

Coherent perception relies on integrating multiple dimensions of a sensory modality, for example, color and shape in vision. We reveal how different acoustic dimensions, specifically echo intensity and sonar aperture (or width), are important for correct perception by echolocating bats. We flew bats down a corridor blocked by objects with different intensity-aperture combinations. To our surprise, bats crashed straight into large (aperture) walls with weak echo intensity as if they did not exist. The echolocation behavior of the bats indicated that they did detect the wall, suggesting that crashing was not a result of limited sensory sensitivity, but of a perceptual deficit. We systematically manipulated intensity and aperture by changing the materials and width of different reflectors, and we conclude that a coherent echo-based percept is created only when these two acoustic dimensions have certain relations which are typical for objects in nature (e.g., large and intense or small and weak reflectors). Nevertheless, we show that these preferred relations are not innate. We show that young pups are not constrained to these relations and that new intensity-aperture associations can also be learned by adult bats.

Socially foraging bats discriminate between group members based on search-phase echolocation calls

Animals have evolved diverse strategies to use social information for increasing foraging success and efficiency. Echolocating bats, for example, can eavesdrop on bats foraging nearby because they shift from search-phase calls to feeding buzzes when they detect prey. Feeding buzzes can directly convey information about prey presence, but it is unknown whether search-phase calls also convey social information. Here, we investigated whether search-phase echolocation calls, distinct calls produced by some bat species to scan large open areas for prey, can additionally convey individual identity. We tested this in Molossus molossus, a neotropical insectivorous bat that forages with group members, presumably to find ephemeral insect swarms more efficiently. We caught M. molossus from six different social groups and recorded their search-phase calls during a standardized release procedure, then recaptured and tested 19 marked bats with habituation–dishabituation playback experiments. We showed that they can discriminate between group members based on search-phase calls, and our statistical analysis of call parameters supported the presence of individual signatures in search-phase calls. Individual discrimination is a prerequisite of individual recognition, which may allow M. molossus to maintain contact with group members while foraging without using specialized signals for communication.

Bioinspired sonar reflectors as guiding beacons for autonomous navigation

Sonar sensors are universally applied in autonomous vehicles such as robots and driverless cars as they are inexpensive, energy-efficient, and provide accurate range measurements; however, they have some limitations. Their measurements can lead to ambiguous estimates and echo clutter can hamper target detection. In nature, echolocating bats experience similar problems when searching for food, especially if their food source is close to vegetation, as is the case for gleaning bats and nectar-feeding bats. However, nature has come up with solutions to overcome clutter problems and acoustically guide bats. Several bat-pollinated plants have evolved specially shaped floral parts that act as sonar reflectors, making the plants acoustically conspicuous. Here we show that artificial sonar beacons inspired by floral shapes streamline the navigation efficacy of sonar-guided robot systems. We developed floral-inspired reflector forms and demonstrate their functionality in 2 proof-of-principle experiments. First we show that the reflectors are easily recognized among dense clutter, and second we show that it is possible to discern different reflector shapes and use this identification to guide a robot through an unfamiliar environment. Bioinspired sonar reflectors could have a wide range of applications that could significantly advance sonar-guided systems.

Avoidance of non-localizable obstacles in echolocating bats: A robotic model

Most objects and vegetation making up the habitats of echolocating bats return a multitude of overlapping echoes. Recent evidence suggests that the limited temporal and spatial resolution of bio-sonar prevents bats from separately perceiving the objects giving rise to these overlapping echoes. Therefore, bats often operate under conditions where their ability to localize obstacles is severely limited. Nevertheless, bats excel at avoiding complex obstacles. In this paper, we present a robotic model of bat obstacle avoidance using interaural level differences and distance to the nearest obstacle as the minimal set of cues. In contrast to previous robotic models of bats, the current robot does not attempt to localize obstacles. We evaluate two obstacle avoidance strategies. First, the Fixed Head Strategy keeps the acoustic gaze direction aligned with the direction of flight. Second, the Delayed Linear Adaptive Law (DLAL) Strategy uses acoustic gaze scanning, as observed in hunting bats. Acoustic gaze scanning has been suggested to aid the bat in hunting for prey. Here, we evaluate its adaptive value for obstacle avoidance when obstacles can not be localized. The robot's obstacle avoidance performance is assessed in two environments mimicking (highly cluttered) experimental setups commonly used in behavioral experiments: a rectangular arena containing multiple complex cylindrical reflecting surfaces and a corridor lined with complex reflecting surfaces. The results indicate that distance to the nearest object and interaural level differences allows steering the robot clear of obstacles in environments that return non-localizable echoes. Furthermore, we found that using acoustic gaze scanning reduced performance, suggesting that gaze scanning might not be beneficial under conditions where the animal has limited access to angular information, which is in line with behavioral evidence.

Biosonar interpulse intervals and pulse-echo ambiguity in four species of echolocating bats

In complex biosonar scenes, the delay of echoes represents the spatial distribution of objects in depth. To avoid overlap of echo streams from successive broadcasts, individual echolocation sounds should only be emitted after all echoes of previous sounds have returned. However, close proximity of obstacles demands rapid pulse updates for steering to avoid collisions, which often means emitting a new sound before all of the previous echoes have returned. When two echo streams overlap, there is ambiguity about assigning echoes to the corresponding broadcasts. In laboratory tests of flight in dense, cluttered scenes, four species of echolocating bats exhibited different patterns of pulse emissions to accommodate potential pulse-echo ambiguity. Miniopterus fuliginosus emitted individual FM pulses only after all echoes of previous pulses had returned, with no alternating between long and short intervals. Pipistrellus abramus and Eptesicus fuscus alternated between emitting long FM pulse intervals to receive all echoes before the next pulse, and short intervals to update the rapidly changing scene while accepting partial overlap of successive echo streams. Rhinolophus ferrumequinum nippon transmitted CF/FM pulses in alternating short and long intervals, usually two to four closely spaced sounds that produced overlapping echo streams, followed by a longer interval that separated echo streams. Rhinolophus f. nippon is a statistical outlier from the three FM species, which are more similar to each other. The repeated overlap of CF/FM echo streams suggests that CF components have a distinct role in rejection of clutter and mitigation of ambiguity.

Acoustic emissions of Sorex unguiculatus (Mammalia: Soricidae): Assessing the echo-based orientation hypothesis

Shrew species have been proposed to utilize an echo-based orientation system to obtain additional acoustic information while surveying their environments. This system has been supported by changes in vocal emission rates when shrews encounter different habitats of varying complexity, although detailed acoustic features in this system have not been reported. In this study, behavioral experiments were conducted using the long-clawed shrew (Sorex unguiculatus) to assess this orientation system. Three experimental conditions were set, two of which contained obstacles. Short-click, noisy, and different types of tonal calls in the audible-to-ultrasonic frequency range were recorded under all experimental conditions. The results indicated that shrews emit calls more frequently when they are facing obstacles or exploring the experimental environment. Shrews emitted clicks and several different types of tonal calls while exploring, and modified the use of different types of calls for varying behavior. Furthermore, shrews modified the dominant frequency and duration of squeak calls for different types of obstacles, that is, plants and acrylic barriers. The vocalizations emitted at short inter-pulse intervals could not be observed when shrews approached these obstacles. These results are consistent with the echo-based orientation hypothesis according to which shrews use a simple echo-orientation system to obtain information from their surrounding environments, although further studies are needed to confirm this hypothesis.

A fully autonomous terrestrial bat-like acoustic robot

Echolocating bats rely on active sound emission (echolocation) for mapping novel environments and navigating through them. Many theoretical frameworks have been suggested to explain how they do so, but few attempts have been made to build an actual robot that mimics their abilities. Here, we present the ‘Robat’—a fully autonomous bat-like terrestrial robot that relies on echolocation to move through a novel environment while mapping it solely based on sound. Using the echoes reflected from the environment, the Robat delineates the borders of objects it encounters, and classifies them using an artificial neural-network, thus creating a rich map of its environment. Unlike most previous attempts to apply sonar in robotics, we focus on a biological bat-like approach, which relies on a single emitter and two ears, and we apply a biological plausible signal processing approach to extract information about objects’ position and identity.

Many animals are able of mapping a new environment even while moving through it for the first time. Bats can do this by emitting sound and extracting information from the echoes reflected from objects in their surroundings. In this study, we mimicked this ability by developing a robot that emits sound like a bat and analyzes the returning echoes to generate a map of space. Our Robat had an ultrasonic speaker mimicking the bat’s mouth and two ultrasonic microphones mimicking its ears. It moved autonomously through novel out-doors environments and mapped them using sound only. It was able to negotiate obstacles and move around them, to avoid dead-ends and even to recognize if the object in front of it is a plant or not. We show the great potential of using sound for future robotic applications.

A Unified Analysis of Structured Sonar-terrain Data using Bayesian Functional Mixed Models

Sonar emits pulses of sound and uses the reflected echoes to gain information about target objects. It offers a low cost, complementary sensing modality for small robotic platforms. While existing analytical approaches often assume independence across echoes, real sonar data can have more complicated structures due to device setup or experimental design. In this paper, we consider sonar echo data collected from multiple terrain substrates with a dual-channel sonar head. Our goals are to identify the differential sonar responses to terrains and study the effectiveness of this dual-channel design in discriminating targets. We describe a unified analytical framework that achieves these goals rigorously, simultaneously, and automatically. The analysis was done by treating the echo envelope signals as functional responses and the terrain/channel information as covariates in a functional regression setting. We adopt functional mixed models that facilitate the estimation of terrain and channel effects while capturing the complex hierarchical structure in data. This unified analytical framework incorporates both Gaussian models and robust models. We fit the models using a full Bayesian approach, which enables us to perform multiple inferential tasks under the same modeling framework, including selecting models, estimating the effects of interest, identifying significant local regions, discriminating terrain types, and describing the discriminatory power of local regions. Our analysis of the sonar-terrain data identifies time regions that reflect differential sonar responses to terrains. The discriminant analysis suggests that a multi- or dual-channel design achieves target identification performance comparable with or better than a single-channel design.

Spike Train Similarity Space (SSIMS) Method Detects Effects of Obstacle Proximity and Experience on Temporal Patterning of Bat Biosonar

Bats emit biosonar pulses in complex temporal patterns that change to accommodate dynamic surroundings. Efforts to quantify these patterns have included analyses of inter-pulse intervals, sonar sound groups, and changes in individual signal parameters such as duration or frequency. Here, the similarity in temporal structure between trains of biosonar pulses is assessed. The spike train similarity space (SSIMS) algorithm, originally designed for neural activity pattern analysis, was applied to determine which features of the environment influence temporal patterning of pulses emitted by flying big brown bats, Eptesicus fuscus. In these laboratory experiments, bats flew down a flight corridor through an obstacle array. The corridor varied in width (100, 70, or 40 cm) and shape (straight or curved). Using a relational point-process framework, SSIMS was able to discriminate between echolocation call sequences recorded from flights in each of the corridor widths. SSIMS was also able to tell the difference between pulse trains recorded during flights where corridor shape through the obstacle array matched the previous trials (fixed, or expected) as opposed to those recorded from flights with randomized corridor shape (variable, or unexpected), but only for the flight path shape in which the bats had previous training. The results show that experience influences the temporal patterns with which bats emit their echolocation calls. It is demonstrated that obstacle proximity to the bat affects call patterns more dramatically than flight path shape.

A simplified model of biosonar echoes from foliage and the properties of natural foliages

Foliage echoes could play an important role in the sensory ecology of echolocating bats, but many aspects of their sensory information content remain to be explored. A realistic numerical model for these echoes could support the development of hypotheses for the relationship between foliage properties and echo parameters. In prior work by the authors, a simple foliage model based on circular disks distributed uniformly in space has been developed. In the current work, three key simplifications used in this model have been examined: (i) representing leaves as circular disks, (ii) neglecting shading effects between leaves, and (iii) the uniform spatial distribution of the leaves. The target strengths of individual leaves and shading between them have been examined in physical experiments, whereas the impact of the spatial leaf distribution has been studied by modifying the numerical model to include leaf distributions according to a biomimetic model for natural branching patterns (L-systems). Leaf samples from a single species (leatherleaf arrowwood) were found to match the relationship between size and target strength of the disk model fairly well, albeit with a large variability part of which could be due to unaccounted geometrical features of the leaves. Shading between leaf-sized disks did occur for distances below 50 cm and could hence impact the echoes. Echoes generated with L-system models in two distinct tree species (ginkgo and pine) showed consistently more temporal inhomogeneity in the envelope amplitudes than a reference with uniform distribution. However, these differences were small compared to effects found in response to changes in the relative orientation of simulated sonar beam and foliage. These findings support the utility of the uniform leaf distribution model and suggest that bats could use temporal inhomogeneities in the echoes to make inferences regarding the relative positioning of their sonar and a foliage.

A computational model for biosonar echoes from foliage

Since many bat species thrive in densely vegetated habitats, echoes from foliage are likely to be of prime importance to the animals’ sensory ecology, be it as clutter that masks prey echoes or as sources of information about the environment. To better understand the characteristics of foliage echoes, a new model for the process that generates these signals has been developed. This model takes leaf size and orientation into account by representing the leaves as circular disks of varying diameter. The two added leaf parameters are of potential importance to the sensory ecology of bats, e.g., with respect to landmark recognition and flight guidance along vegetation contours. The full model is specified by a total of three parameters: leaf density, average leaf size, and average leaf orientation. It assumes that all leaf parameters are independently and identically distributed. Leaf positions were drawn from a uniform probability density function, sizes and orientations each from a Gaussian probability function. The model was found to reproduce the first-order amplitude statistics of measured example echoes and showed time-variant echo properties that depended on foliage parameters. Parameter estimation experiments using lasso regression have demonstrated that a single foliage parameter can be estimated with high accuracy if the other two parameters are known a priori. If only one parameter is known a priori, the other two can still be estimated, but with a reduced accuracy. Lasso regression did not support simultaneous estimation of all three parameters. Nevertheless, these results demonstrate that foliage echoes contain accessible information on foliage type and orientation that could play a role in supporting sensory tasks such as landmark identification and contour following in echolocating bats.

Acoustic communication in plant-animal interactions

Acoustic communication is widespread and well-studied in animals but has been neglected in other organisms such as plants. However, there is growing evidence for acoustic communication in plant-animal interactions. While knowledge about active acoustic signalling in plants (i.e. active sound production) is still in its infancy, research on passive acoustic signalling (i.e. reflection of animal sounds) revealed that bat-dependent plants have adapted to the bats' echolocation systems by providing acoustic reflectors to attract their animal partners. Understanding the proximate mechanisms and ultimate causes of acoustic communication will shed light on an underestimated dimension of information transfer between plants and animals.

Sensorimotor Model of Obstacle Avoidance in Echolocating Bats

Bat echolocation is an ability consisting of many subtasks such as navigation, prey detection and object recognition. Understanding the echolocation capabilities of bats comes down to isolating the minimal set of acoustic cues needed to complete each task. For some tasks, the minimal cues have already been identified. However, while a number of possible cues have been suggested, little is known about the minimal cues supporting obstacle avoidance in echolocating bats. In this paper, we propose that the Interaural Intensity Difference (IID) and travel time of the first millisecond of the echo train are sufficient cues for obstacle avoidance. We describe a simple control algorithm based on the use of these cues in combination with alternating ear positions modeled after the constant frequency bat Rhinolophus rouxii. Using spatial simulations (2D and 3D), we show that simple phonotaxis can steer a bat clear from obstacles without performing a reconstruction of the 3D layout of the scene. As such, this paper presents the first computationally explicit explanation for obstacle avoidance validated in complex simulated environments. Based on additional simulations modelling the FM bat Phyllostomus discolor, we conjecture that the proposed cues can be exploited by constant frequency (CF) bats and frequency modulated (FM) bats alike. We hypothesize that using a low level yet robust cue for obstacle avoidance allows bats to comply with the hard real-time constraints of this basic behaviour.

Echolocating bats can fly through complex environments in complete darkness. Swift and apparently effortless obstacle avoidance is the most fundamental function supported by biosonar. Despite this, we still do not know which acoustic cues, from among the many possible cues, bats actually exploit while avoiding obstacles. In this paper, we show using spatial simulations (2D and 3D) that the Interaural Intensity Difference (IID) and travel time of the first millisecond of the echo train in combination with alternating ear positions provide robust and reliable cues for obstacle avoidance. Simulating the echoes received by a flying bat, we show that simple phonotaxis can steer a bat clear from obstacles without performing 3D reconstruction of the layout of the scene. As such, this paper presents the first computationally explicit explanation for obstacle avoidance in realistic and complex 3D environments. We hypothesize that using low level yet robust cues for obstacle avoidance allows bats to comply with the hard real-time constraints of this basic behaviour.

Temporal binding of neural responses for focused attention in biosonar

Big brown bats emit biosonar sounds and perceive their surroundings from the delays of echoes received by the ears. Broadcasts are frequency modulated (FM) and contain two prominent harmonics sweeping from 50 to 25 kHz (FM1) and from 100 to 50 kHz (FM2). Individual frequencies in each broadcast and each echo evoke single-spike auditory responses. Echo delay is encoded by the time elapsed between volleys of responses to broadcasts and volleys of responses to echoes. If echoes have the same spectrum as broadcasts, the volley of neural responses to FM1 and FM2 is internally synchronized for each sound, which leads to sharply focused delay images. Because of amplitude-latency trading, disruption of response synchrony within the volleys occurs if the echoes are lowpass filtered, leading to blurred, defocused delay images. This effect is consistent with the temporal binding hypothesis for perceptual image formation. Bats perform inexplicably well in cluttered surroundings where echoes from off-side objects ought to cause masking. Off-side echoes are lowpass filtered because of the shape of the broadcast beam, and they evoke desynchronized auditory responses. The resulting defocused images of clutter do not mask perception of focused images for targets. Neural response synchronization may select a target to be the focus of attention, while desynchronization may impose inattention on the surroundings by defocusing perception of clutter. The formation of focused biosonar images from synchronized neural responses, and the defocusing that occurs with disruption of synchrony, quantitatively demonstrates how temporal binding may control attention and bring a perceptual object into existence.

Spatial release from simultaneous echo masking in bat sonar

Big brown bats (Eptesicus fuscus) use biosonar to navigate and locate objects in their surroundings. During natural foraging, they often encounter echoes returned by a target of interest located to the front while other, often stronger, clutter echoes are returned from objects, such as vegetation, located to the sides or above. Nevertheless, bats behave as if they do not suffer interference from this clutter. Using a two-choice delay discrimination procedure, bats were tested for the masking effectiveness of clutter echoes on target echoes when the target echoes were delivered from the bat's front while clutter echoes were delivered from 90° overhead, a direction of lowpass filtering by the external ears. When clutter echoes are presented from the front at the same delay as target echoes, detection performance declines and clutter masking occurs. When the clutter echoes are presented at the same delay but from overhead, discrimination performance is unaffected and no masking occurs. Thus there is masking release for simultaneous off-axis lowpass clutter compared to masking by simultaneous clutter from the front. The bat's performance for simultaneous target and clutter echoes indicates a new role for the mechanism that separates overlapping echoes by decomposing the bat's auditory time-frequency representation.

Bat guilds, a concept to classify the highly diverse foraging and echolocation behaviors of microchiropteran bats

Throughout evolution the foraging and echolocation behaviors as well as the motor systems of bats have been adapted to the tasks they have to perform while searching and acquiring food. When bats exploit the same class of environmental resources in a similar way, they perform comparable tasks and thus share similar adaptations independent of their phylogeny. Species with similar adaptations are assigned to guilds or functional groups. Habitat type and foraging mode mainly determine the foraging tasks and thus the adaptations of bats. Therefore, we use habitat type and foraging mode to define seven guilds. The habitat types open, edge and narrow space are defined according to the bats' echolocation behavior in relation to the distance between bat and background or food item and background. Bats foraging in the aerial, trawling, flutter detecting, or active gleaning mode use only echolocation to acquire their food. When foraging in the passive gleaning mode bats do not use echolocation but rely on sensory cues from the food item to find it. Bat communities often comprise large numbers of species with a high diversity in foraging areas, foraging modes, and diets. The assignment of species living under similar constraints into guilds identifies patterns of community structure and helps to understand the factors that underlie the organization of highly diverse bat communities. Bat species from different guilds do not compete for food as they differ in their foraging behavior and in the environmental resources they use. However, sympatric living species belonging to the same guild often exploit the same class of resources. To avoid competition they should differ in their niche dimensions. The fine grain structure of bat communities below the rather coarse classification into guilds is determined by mechanisms that result in niche partitioning.

Modelling sensory limitation: the role of tree selection, memory and information transfer in bats' roost searching strategies

Sensory limitation plays an important role in the evolution of animal behaviour. Animals have to find objects of interest (e.g. food, shelters, predators). When sensory abilities are strongly limited, animals adjust their behaviour to maximize chances for success. Bats are nocturnal, live in complex environments, are capable of flight and must confront numerous perceptual challenges (e.g. limited sensory range, interfering clutter echoes). This makes them an excellent model for studying the role of compensating behaviours to decrease costs of finding resources. Cavity roosting bats are especially interesting because the availability of tree cavities is often limited, and their quality is vital for bats during the breeding season. From a bat’s sensory point of view, cavities are difficult to detect and finding them requires time and energy. However, tree cavities are also long lasting, allowing information transfer among conspecifics. Here, we use a simple simulation model to explore the benefits of tree selection, memory and eavesdropping (compensation behaviours) to searches for tree cavities by bats with short and long perception range. Our model suggests that memory and correct discrimination of tree suitability are the basic strategies decreasing the cost of roost finding, whereas perceptual range plays a minor role in this process. Additionally, eavesdropping constitutes a buffer that reduces the costs of finding new resources (such as roosts), especially when they occur in low density. We conclude that natural selection may promote different strategies of roost finding in relation to habitat conditions and cognitive skills of animals.

Bats' avoidance of real and virtual objects: implications for the sonar coding of object size

Fast movement in complex environments requires the controlled evasion of obstacles. Sonar-based obstacle evasion involves analysing the acoustic features of object-echoes (e.g., echo amplitude) that correlate with this object's physical features (e.g., object size). Here, we investigated sonar-based obstacle evasion in bats emerging in groups from their day roost. Using video-recordings, we first show that the bats evaded a small real object (ultrasonic loudspeaker) despite the familiar flight situation. Secondly, we studied the sonar coding of object size by adding a larger virtual object. The virtual object echo was generated by real-time convolution of the bats' calls with the acoustic impulse response of a large spherical disc and played from the loudspeaker. Contrary to the real object, the virtual object did not elicit evasive flight, despite the spectro-temporal similarity of real and virtual object echoes. Yet, their spatial echo features differ: virtual object echoes lack the spread of angles of incidence from which the echoes of large objects arrive at a bat's ears (sonar aperture). We hypothesise that this mismatch of spectro-temporal and spatial echo features caused the lack of virtual object evasion and suggest that the sonar aperture of object echoscapes contributes to the sonar coding of object size.

Floral acoustics: conspicuous echoes of a dish-shaped leaf attract bat pollinators

The visual splendor of many diurnal flowers serves to attract visually guided pollinators such as bees and birds, but it remains to be seen whether bat-pollinated flowers have evolved analogous echo-acoustic signals to lure their echolocating pollinators. Here, we demonstrate how an unusual dish-shaped leaf displayed above the inflorescences of the vine Marcgravia evenia attracts bat pollinators. Specifically, this leaf's echoes fulfilled requirements for an effective beacon, that is, they were strong, multidirectional, and had a recognizable invariant echo signature. In behavioral experiments, presence of the leaves halved foraging time for flower-visiting bats.

Information generated by the moving pinnae of Rhinolophus rouxi: tuning of the morphology at different harmonics

Bats typically emit multi harmonic calls. Their head morphology shapes the emission and hearing sound fields as a function of frequency. Therefore, the sound fields are markedly different for the various harmonics. As the sound field provides bats with all necessary cues to locate objects in space, different harmonics might provide them with variable amounts of information about the location of objects. Also, the ability to locate objects in different parts of the frontal hemisphere might vary across harmonics. This paper evaluates this hypothesis in R. rouxi, using an information theoretic framework. We estimate the reflector position information transfer in the echolocation system of R. rouxi as a function of frequency. This analysis shows that localization performance reaches a global minimum and a global maximum at the two most energetic frequency components of R. rouxi call indicating tuning of morphology and harmonic structure. Using the fundamental the bat is able to locate objects in a large portion of the frontal hemisphere. In contrast, using the 1 overtone, it can only locate objects, albeit with a slightly higher accuracy, in a small portion of the frontal hemisphere by reducing sensitivity to echoes from outside this region of interest. Hence, different harmonic components provide the bat either with a wide view or a focused view of its environment. We propose these findings can be interpreted in the context of the foraging behaviour of R. rouxi, i.e., hunting in cluttered environments. Indeed, the focused view provided by the 1 overtone suggests that at this frequency its morphology is tuned for clutter rejection and accurate localization in a small region of interest while the finding that overall localization performance is best at the fundamental indicates that the morphology is simultaneously tuned to optimize overall localization performance at this frequency.

Complex echo classification by echo-locating bats: a review

Echo-locating bats constantly emit ultrasonic pulses and analyze the returning echoes to detect, localize, and classify objects in their surroundings. Echo classification is essential for bats' everyday life; for instance, it enables bats to use acoustical landmarks for navigation and to recognize food sources from other objects. Most of the research of echo based object classification in echo-locating bats was done in the context of simple artificial objects. These objects might represent prey, flower, or fruit and are characterized by simple echoes with a single up to several reflectors. Bats, however, must also be able to use echoes that return from complex structures such as plants or other types of background. Such echoes are characterized by superpositions of many reflections that can only be described using a stochastic statistical approach. Scientists have only lately started to address the issue of complex echo classification by echo-locating bats. Some behavioral evidence showing that bats can classify complex echoes has been accumulated and several hypotheses have been suggested as to how they do so. Here, we present a first review of this data. We raise some hypotheses regarding possible interpretations of the data and point out necessary future directions that should be pursued.