Classification of insects by echolocating greater horseshoe bats

Summary Echolocating greater horseshoe bats (Rhinolophus ferrumequinum) detect insects by concentrating on the characteristic amplitude- and frequency modulation pattern fluttering insects impose on the returning echoes. This study shows that horseshoe bats can also further analyse insect echoes and thus recognize and categorize the kind of insect they are echolocating.Four greater horseshoe bats were trained in a twoalternative forced-choice procedure to choose the echo of one particular insect species turning its side towards the bat (Fig. 1). The bats were able to discriminate with over 90% correct choices between the reward-positive echo and the echoes of other insect species all fluttering with exactly the same wingbeat rate (Fig. 4).When the angular orientation of the reward-positive insect was changed (Fig. 2), the bats still preferred these unknown echoes over echoes from other insect species (Fig. 5) without any further training. Because the untrained bats did not show any prey preference, this indicates that the bats were able to perform an aspect-anglein-dependent classification of insects.Finally we tested what parameters in the echo were responsible for species recognition. It turned out that the bats especially used the small echo-modulations in between glints as a source of information (Fig. 7). Neither the amplitudenor the frequencymodulation of the echoes alone was sufficient for recognition of the insect species (Fig. 8). Bats performed a pattern recognition task based on complex computations of several acoustic parameters, an ability which might be termed cognitive.Abbreviations AM amplitude modulation - CF constant frequency - FM frequency modulation - S+ positive stimulus - S- negative stimulus     

Prey pursuit strategy of Japanese horseshoe bats during an in-flight target-selection task

The prey pursuit behavior of Japanese horseshoe bats (Rhinolophus ferrumequinum nippon) was investigated by tasking bats during flight with choosing between two tethered fluttering moths. Echolocation pulses were recorded using a telemetry microphone mounted on the bat combined with a 17-channel horizontal microphone array to measure pulse directions. Flight paths of the bat and moths were monitored using two high-speed video cameras. Acoustical measurements of returning echoes from fluttering moths were first collected using an ultrasonic loudspeaker, turning the head direction of the moth relative to the loudspeaker from 0° (front) to 180° (back) in the horizontal plane. The amount of acoustical glints caused by moth fluttering varied with the sound direction, reaching a maximum at 70°–100° in the horizontal plane. In the flight experiment, moths chosen by the bat fluttered within or moved across these angles relative to the bat’s pulse direction, which would cause maximum dynamic changes in the frequency and amplitude of acoustical glints during flight. These results suggest that echoes with acoustical glints containing the strongest frequency and amplitude modulations appear to attract bats for prey selection.     

Convergence of temporal and spectral information into acoustic images of complex sonar targets perceived by the echolocating bat,Eptesicus fuscus

1. FM echolocating bats (Eptesicus fuscus) were trained to discriminate between a two-component complex target and a one-component simple target simulated by electronically-returned echoes in a series of experiments that explore the composition of the image of the two-component target. In Experiment I, echoes for each target were presented sequentially, and the bats had to compare a stored image of one target with that of the other. The bats made errors when the range of the simple target corresponded to the range of either glint in the complex target, indicating that some trace of the parts of one image interfered with perception of the other image. In Experiment II, echoes were presented simultaneously as well as sequentially, permitting direct masking of echoes from one target to the other. Changes in echo amplitude produced shifts in apparent range whose pattern depended upon the mode of echo presentation. 2. Eptesicus perceives images of complex sonar targets that explicitly represent the location and spacing of discrete glints located at different ranges. The bat perceives the target's structure in terms of its range profile along a psychological range axis using a combination of echo delay and echo spectral representations that together resemble a spectrogram of the FM echoes. The image itself is expressed entirely along a range scale that is defined with reference to echo delay. Spectral information contributes to the image by providing estimates of the range separation of glints, but it is transformed into these estimates. 3. Perceived absolute range is encoded by the timing of neural discharges and is vulnerable to shifts caused by neural amplitude-latency trading, which was estimated at 13 to 18 microseconds per dB from N1 and N4 auditory evoked potentials in Eptesicus. Spectral cues representing the separation of glints within the target are transformed into estimates of delay separations before being incorporated into the image. However, because they are encoded by neural frequency tuning rather than the time-of-occurrence of neural discharges, the perceived range separation of glints in images is not vulnerable to amplitude-latency shifts. 4. The bat perceives an image that is displayed in the domain of time or range. The image receives no evident spectral contribution beyond what is transformed into delay estimates. Although the initial auditory representation of FM echoes is spectrogram-like, the time, frequency, and amplitude dimensions of the spectrogram appear to be compressed into an image that has only time and amplitude dimensions.(ABSTRACT TRUNCATED AT 400 WORDS)     

Foraging ecology and audition in echolocating bats

The types of echolocation signal and the auditory capacities of echolocating bats are adapted to specific acoustical constraints of the foraging areas. Bats hunting insects above the canopy use low frequencies for echolocation; this is an adaptation to prey detection over long distances. Bats foraging close to and within foliage avoid masking of insect echoes by specializing on 'fluttering target' detection. 'Gleaning' bats are adapted to the auditory detection of very faint noises generated by ground-dwelling prey, and are capable of analysing fine changes in the echo spectrum, which may indicate a stationary prey changing its posture on a substrate. This review of recent research demonstrates that, in bats, foraging ecology and audition are intricately interrelated and interdependent.     

Adaptive mechanisms underlying the bat biosonar behavior

For survival, bats of the suborder Microchiropetra emit intense ultrasonic pulses and analyze the weak returning echoes to extract the direction, distance, velocity, size, and shape of the prey. Although these bats and other mammals share the common layout of the auditory pathway and sound coding mechanism, they have highly developed auditory systems to process biologically relevant pulses at the expense of a reduced visual system. During this active biosonar behavior, they progressively shorten the pulse duration, decrease the amplitude and pulse-echo gap as they search, approach and finally intercept the prey. Presumably, these changes in multiple pulse parameters throughout the entire course of hunting enable them to extract maximal information about localized prey from the returning echoes. To hunt successfully, the auditory system of these bats must be less sensitive to intense emitted pulses but highly sensitive to weak returning echoes. They also need to recognize and differentiate the echoes of their emitted pulses from echoes of pulses emitted by other conspecifics. Past studies have shown the following mechanical and neural adaptive mechanisms underlying the successful bat biosonar behavior: (1) Forward orienting and highly mobile pinnae for effective scanning, signal reception, sound pressure transformation and mobile auditory sensitivity; (2) Avoiding and detecting moving targets more successfully than stationary ones; (3) Coordinated activity of highly developed laryngeal and middle ear muscles during pulse emission and reception; (4) Mechanical and neural attenuation of intense emitted pulses to prepare for better reception of weak returning echoes; (5) Increasing pulse repetition rate to improve multiple-parametric selectivity to echoes; (6) Dynamic variation of duration selectivity and recovery cycle of auditory neurons with hunting phase for better echo analysis; (7) Maximal multiple-parametric selectivity to expected echoes returning within a time window after pulse emission; (8) Pulse-echo delaysensitive neurons in higher auditory centers for echo ranging; (9) Corticofugal modulation to improve on-going multiple-parametric signal processing and reorganize signal representation, and (10) A large area of the superior colliculus, pontine nuclei and cerebellum that is sensitive to sound for sensori-motor integration. All these adaptive mechanisms facilitate the bat to effectively extract prey features for successful hunting.     

A comprehensive computational model of animal biosonar signal processing

Computational models of animal biosonar seek to identify critical aspects of echo processing responsible for the superior, real-time performance of echolocating bats and dolphins in target tracking and clutter rejection. The Spectrogram Correlation and Transformation (SCAT) model replicates aspects of biosonar imaging in both species by processing wideband biosonar sounds and echoes with auditory mechanisms identified from experiments with bats. The model acquires broadband biosonar broadcasts and echoes, represents them as time-frequency spectrograms using parallel bandpass filters, translates the filtered signals into ten parallel amplitude threshold levels, and then operates on the resulting time-of-occurrence values at each frequency to estimate overall echo range delay. It uses the structure of the echo spectrum by depicting it as a series of local frequency nulls arranged regularly along the frequency axis of the spectrograms after dechirping them relative to the broadcast. Computations take place entirely on the timing of threshold-crossing events for each echo relative to threshold-events for the broadcast. Threshold-crossing times take into account amplitude-latency trading, a physiological feature absent from conventional digital signal processing. Amplitude-latency trading transposes the profile of amplitudes across frequencies into a profile of time-registrations across frequencies. Target shape is extracted from the spacing of the object’s individual acoustic reflecting points, or glints, using the mutual interference pattern of peaks and nulls in the echo spectrum. These are merged with the overall range-delay estimate to produce a delay-based reconstruction of the object’s distance as well as its glints. Clutter echoes indiscriminately activate multiple parts in the null-detecting system, which then produces the equivalent glint-delay spacings in images, thus blurring the overall echo-delay estimates by adding spurious glint delays to the image. Blurring acts as an anticorrelation process that rejects clutter intrusion into perceptions.     

Echolocation behavior of the Japanese horseshoe bat in pursuit of fluttering prey

Echolocation sounds of Rhinolophus ferrumequinum nippon as they approached a fluttering moth (Goniocraspidum pryeri) were investigated using an on-board telemetry microphone (Telemike). In 40?% of the successful moth-capture flights, the moth exhibited distinctive evasive flight behavior, but the bat pursued the moth by following its flight path. When the distance to the moth was approximately 3-4?m, the bats increased the duration of the pulses to 65-95?ms, which is 2-3 times longer than those during landing flight (30-40?ms). The mean of 5.8 long pulses were emitted before the final buzz phase of moth capture, without strengthening the sound pressure level. The mean duration of long pulses (79.9?±?7.9?ms) corresponded to three times the fluttering period of G. pryeri (26.5?×?3?=?79.5?ms). These findings indicate that the bats adjust the pulse duration to increase the number of temporal repetitions of fluttering information rather than to produce more intense sonar sounds to receive fine insect echoes. The bats exhibited Doppler-shift compensation for echoes returning from large static objects ahead, but not for echoes from target moths, even though the bats were focused on capturing the moths. Furthermore, the echoes of the Telemike recordings from target moths showed spectral glints of approximately 1-1.5?kHz caused by the fluttering of the moths but not amplitude glints because of the highly acoustical attenuation of ultrasound in the air, suggesting that spectral information may be more robust than amplitude information in echoes during moth capturing flight.     

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.     

Preference of a revolving target to a stationary one by the big brown bat, Eptesicus fuscus

Utilizing a three-ramp platform, we studied the detection of a revolving and a stationary target in the presence of background clutter by trained Eptesicus fuscus. During the test, the mean amplitude of echo from either target was always larger than that of the background echoes at the bat-to-target distance of 30, 70 and 100 cm. The amplitude of the echo reflected back from a revolving target was modulated between a maximum and a minimum value. An electric motor was used to revolve a target. The frequency contents of the motor noise were mostly below 1 kHz. While the total percent response of approaching either target is always more than 90% at every bat-to-target distance tested, the bats approach a revolving target more frequently than a stationary one. Echolocation pulses emitted by the bats during the test were recorded and analyzed. The bats shortened their pulse durations and interpulse intervals and lowered the frequency contents as they entered into the crawling phase from the searching phase. Potential interference of background echoes and ambient noise with the performance of the bats is discussed. The preference of a revolving target to a stationary one by the bats is perhaps due to the fact that a revolving target has a higher releasing value than a stationary one does.     

Horseshoe bats make adaptive prey-selection decisions, informed by echo cues

Foragers base their prey-selection decisions on the information acquired by the sensory systems. In bats that use echolocation to find prey in darkness, it is not clear whether the specialized diet, as sometimes found by faecal analysis, is a result of active decision-making or rather of biased sensory information. Here, we tested whether greater horseshoe bats decide economically when to attack a particular prey item and when not. This species is known to recognize different insects based on their wing-beat pattern imprinted in the echoes. We built a simulation of the natural foraging process in the laboratory, where the bats scanned for prey from a perch and, upon reaching the decision to attack, intercepted the prey in flight. To fully control echo information available to the bats and assure its unambiguity, we implemented computer-controlled propellers that produced echoes resembling those from natural insects of differing profitability. The bats monitored prey arrivals to sample the supply of prey categories in the environment and to inform foraging decisions. The bats adjusted selectivity for the more profitable prey to its inter-arrival intervals as predicted by foraging theory (an economic strategy known to benefit fitness). Moreover, unlike in previously studied vertebrates, foraging performance of horseshoe bats was not limited by costly rejections of the profitable prey. This calls for further research into the evolutionary selection pressures that sharpened the species's decision-making capacity.     

The external ear morphology and presence of tragi in Australian marsupials

Multiple studies have described the anatomy and function of the external ear (pinna) of bats, and other placental mammals, however, studies of marsupial pinna are largely absent. In bats, the tragus appears to be especially important for locating and capturing insect prey. In this study, we aimed to investigate the pinnae of Australian marsupials, with a focus on the presence/absence of tragi and how they may relate to diet. We investigated 23 Australian marsupial species with varying diets. The pinnae measurements (scapha width, scapha length) and tragi (where present) were measured. The interaural distance and body length were also recorded for each individual. Results indicated that all nectarivorous, carnivorous, and insectivorous species had tragi with the exception of the insectivorous striped possum (Dactylopsila trivirgata), numbat (Myrmecobius fasciatus), and nectarivorous sugar glider (Petaurus breviceps). No herbivorous or omnivorous species had tragi. Based on the findings in this study, and those conducted on placental mammals, we suggest marsupials use tragi in a similar way to placentals to locate and target insectivorous prey. The Tasmanian devil (Sarcophilus harrisii) displayed the largest interaural distance that likely aids in better localization and origin of noise associated with prey detection. In contrast, the smallest interaural distance was exhibited by a macropod. Previous studies have suggested the hearing of macropods is especially adapted to detect warnings of predators made by conspecifics. While the data in this study demonstrate a diversity in pinnae among marsupials, including presence and absence of tragi, it suggests that there is a correlation between pinna structure and diet choice among marsupials. A future study should investigate a larger number of individuals and species and include marsupials from Papua New Guinea, and Central and South America as a comparison.     

How anthropogenic noise affects foraging

The influence of human activity on the biosphere is increasing. While direct damage (e.g. habitat destruction) is relatively well understood, many activities affect wildlife in less apparent ways. Here, we investigate how anthropogenic noise impairs foraging, which has direct consequences for animal survival and reproductive success. Noise can disturb foraging via several mechanisms that may operate simultaneously, and thus, their effects could not be disentangled hitherto. We developed a diagnostic framework that can be applied to identify the potential mechanisms of disturbance in any species capable of detecting the noise. We tested this framework using Daubenton's bats, which find prey by echolocation. We found that traffic noise reduced foraging efficiency in most bats. Unexpectedly, this effect was present even if the playback noise did not overlap in frequency with the prey echoes. Neither overlapping noise nor nonoverlapping noise influenced the search effort required for a successful prey capture. Hence, noise did not mask prey echoes or reduce the attention of bats. Instead, noise acted as an aversive stimulus that caused avoidance response, thereby reducing foraging efficiency. We conclude that conservation policies may seriously underestimate numbers of species affected and the multilevel effects on animal fitness, if the mechanisms of disturbance are not considered.     

On-board telemetry of emitted sounds from free-flying bats: compensation for velocity and distance stabilizes echo frequency and amplitude

To understand complex sensory-motor behavior related to object perception by echolocating bats, precise measurements are needed for echoes that bats actually listen to during flight. Recordings of echolocation broadcasts were made from flying bats with a miniature light-weight microphone and radio transmitter (Telemike) set at the position of the bat's ears and carried during flights to a landing point on a wall. Telemike recordings confirm that flying horseshoe bats (Rhinolophus ferrumequinum nippon) adjust the frequency of their sonar broadcasts to compensate for echo Doppler shifts. Returning constant frequency echoes were maintained at the bat's reference frequency +/-83 Hz during flight, indicating that the bats compensated for frequency changes with an accuracy equivalent to that at rest. The flying bats simultaneously compensate for increases in echo amplitude as target range becomes shorter. Flying bats thus receive echoes with both stabilized frequencies and stabilized amplitudes. Although it is widely understood that Doppler-shift frequency compensation facilitates detection of fluttering insects, approaches to a landing do not involve fluttering objects. Combined frequency and amplitude compensation may instead be for optimization of successive frequency modulated echoes for target range estimation to control approach and landing.     

Interpulse interval modulation by echolocating big brown bats (<Emphasis Type="Italic">Eptesicus fuscus</Emphasis>) in different densities of obstacle clutter

Big brown bats (Eptesicus fuscus) use biosonar to find insect prey in open areas, but they also find prey near vegetation and even fly through vegetation when in transit from roosts to feeding sites. To evaluate their reactions to dense, distributed clutter, bats were tested in an obstacle array consisting of rows of vertically hanging chains. Chains were removed from the array to create a curved corridor of three clutter densities (high, medium, low). Bats flew along this path to receive a food reward after landing on the far wall. Interpulse intervals (IPIs) varied across clutter densities to reflect different compromises between using short IPIs for gathering echoes rapidly enough to maneuver past the nearest chains and using longer IPIs so that all echoes from one sound can be received before the next sound is emitted. In high-clutter density, IPIs were uniformly shorter (20–65 ms) than in medium and low densities (40–100 ms) and arranged in “strobe groups,” with some overlap of echo streams from different broadcasts, causing pulse-echo ambiguity. As previously proposed, alternating short and long IPIs in strobe groups may allow bats to focus on large-scale pathfinding tasks as well as close-in obstacle avoidance.     

Plant classification from bat-like echolocation signals

Classification of plants according to their echoes is an elementary component of bat behavior that plays an important role in spatial orientation and food acquisition. Vegetation echoes are, however, highly complex stochastic signals: from an acoustical point of view, a plant can be thought of as a three-dimensional array of leaves reflecting the emitted bat call. The received echo is therefore a superposition of many reflections. In this work we suggest that the classification of these echoes might not be such a troublesome routine for bats as formerly thought. We present a rather simple approach to classifying signals from a large database of plant echoes that were created by ensonifying plants with a frequency-modulated bat-like ultrasonic pulse. Our algorithm uses the spectrogram of a single echo from which it only uses features that are undoubtedly accessible to bats. We used a standard machine learning algorithm (SVM) to automatically extract suitable linear combinations of time and frequency cues from the spectrograms such that classification with high accuracy is enabled. This demonstrates that ultrasonic echoes are highly informative about the species membership of an ensonified plant, and that this information can be extracted with rather simple, biologically plausible analysis. Thus, our findings provide a new explanatory basis for the poorly understood observed abilities of bats in classifying vegetation and other complex objects.     

The role of prey-generated sounds,vision, and echolocation in prey localization by the African batCardioderma cor (Megadermatidae)

Summary Cardioderma cor responded with head movements and flight toward speakers broadcasting calls of frogs and crickets which contained only sonic frequencies. Unlike the frog-eating bat,Trachops cirrhosus, they did not make contact with the speakers. Prey movements that generated sonic and ultrasonic sounds were both sufficient and necessary for the bats to localize and capture prey. Prey dragged across a glass sheet with a thin layer of water did not generate sounds and bats did not attempt to capture these prey, even with the availability of visual and echolocation cues. There was no evidence for the use of visual cues while hunting; bats did not localize prey more readily in light than darkness. Prey were presented such that their movements initially generated sounds, but then the prey moved onto the water layer of the glass sheet and sounds were eliminated. The bats emitted echolocation signals while hunting in this situation; however, the information from these signals was not utilized. The bats landed at the site that prey last made sound. These results demonstrate the importance of passive hearing for prey localization in this bat, and further suggest that when preygenerated sounds and echolocation signals offer conflicting information the bat's behavior is guided by the former.     

Neural ensemble coding of target identity in echolocating bats

Most insectivorous bats use echolocation to determine the identity of flying insects. Among the many target features that are so extracted, the insect's wingbeat pattern and frequency appear to serve as useful cues for identification. Biosonar pulses impinging on the fluttering wings of an insect are returned as echoes whose amplitudes vary with time, thus providing a characteristic signature of the insect. It has been shown previously that neurons in the inferior colliculus, a midbrain auditory nucleus, of the little brown bat respond to sound stimuli that mimic echoes from fluttering targets. To examine the manner in which target identity is represented in the inferior colliculus, an ensemble coding analysis using a filter-based approach was undertaken. The analysis indicates that a discrete subset of neurons in the inferior colliculus, the onset units, are strongly tuned to wingbeat frequencies of targets that the bat hunts, and that ensemble response reaches a maximum at a distinct phase of the prey capture maneuver: the late approach stage. On the basis of the analysis it is hypothesized that inferior colliculus neurons may play an important role in target detection-identification processing. Although ensemble coding of temporally sequenced information has not been analyzed in the auditory system so far, this study indicates that this method of coding may provide the information necessary to detect and identify targets during prey capture. Received: 4 December 1995 / Accepted in revised form: 19 April 1996     

Keeping returns optimal: gain control exerted through sensitivity adjustments in the harbour porpoise auditory system

Animals that use echolocation (biosonar) listen to acoustic signals with a large range of intensities, because echo levels vary with the fourth power of the animal's distance to the target. In man-made sonar, engineers apply automatic gain control to stabilize the echo energy levels, thereby rendering them independent of distance to the target. Both toothed whales and bats vary the level of their echolocation clicks to compensate for the distance-related energy loss. By monitoring the auditory brainstem response (ABR) during a psychophysical task, we found that a harbour porpoise (Phocoena phocoena), in addition to adjusting the sound level of the outgoing signals up to 5.4 dB, also reduces its ABR threshold by 6 dB when the target distance doubles. This self-induced threshold shift increases the dynamic range of the biosonar system and compensates for half of the variation of energy that is caused by changes in the distance to the target. In combination with an increased source level as a function of target range, this helps the porpoise to maintain a stable echo-evoked ABR amplitude irrespective of target range, and is therefore probably an important tool enabling porpoises to efficiently analyse and classify received echoes.     

Neural coding of echo-envelope disparities in echolocating bats

The effective use of echolocation requires not only measuring the delay between the emitted call and returning echo to estimate the distance of an ensonified object. To locate an object in azimuth and elevation, the bat’s auditory system must analyze the returning echoes in terms of their binaural properties, i.e., the echoes’ interaural intensity and time differences (IIDs and ITDs). The effectiveness of IIDs for echolocation is undisputed, but when bats ensonify complex objects, the temporal structure of echoes may facilitate the analysis of the echo envelope in terms of envelope ITDs. Using extracellular recordings from the auditory midbrain of the bat, Phyllostomus discolor, we found a population of neurons that are sensitive to envelope ITDs of echoes of their sonar calls. Moreover, the envelope-ITD sensitivity improved with increasing temporal fluctuations in the echo envelopes, a sonar parameter related to the spatial statistics of complex natural reflectors like vegetation. The data show that in bats envelope ITDs may be used not only to locate external, prey-generated rustling sounds but also in the context of echolocation. Specifically, the temporal fluctuations in the echo envelope, which are created when the sonar emission is reflected from a complex natural target, support ITD-mediated echolocation.     

Multimodal cues improve prey localization under complex environmental conditions

Predators often eavesdrop on sexual displays of their prey. These displays can provide multimodal cues that aid predators, but the benefits in attending to them should depend on the environmental sensory conditions under which they forage. We assessed whether bats hunting for frogs use multimodal cues to locate their prey and whether their use varies with ambient conditions. We used a robotic set-up mimicking the sexual display of a male túngara frog (Physalaemus pustulosus) to test prey assessment by fringe-lipped bats (Trachops cirrhosus). These predatory bats primarily use sound of the frog''s call to find their prey, but the bats also use echolocation cues returning from the frog''s dynamically moving vocal sac. In the first experiment, we show that multimodal cues affect attack behaviour: bats made narrower flank attack angles on multimodal trials compared with unimodal trials during which they could only rely on the sound of the frog. In the second experiment, we explored the bat''s use of prey cues in an acoustically more complex environment. Túngara frogs often form mixed-species choruses with other frogs, including the hourglass frog (Dendropsophus ebraccatus). Using a multi-speaker set-up, we tested bat approaches and attacks on the robofrog under three different levels of acoustic complexity: no calling D. ebraccatus males, two calling D. ebraccatus males and five D. ebraccatus males. We found that bats are more directional in their approach to the robofrog when more D. ebraccatus males were calling. Thus, bats seemed to benefit more from multimodal cues when confronted with increased levels of acoustic complexity in their foraging environments. Our data have important consequences for our understanding of the evolution of multimodal sexual displays as they reveal how environmental conditions can alter the natural selection pressures acting on them.