Echolocating Daubenton's bats call louder, but show no spectral jamming avoidance in response to bands of masking noise during a landing task

Echolocating bats listen for weak echoes to navigate and hunt, which makes them prone to masking from background noise and jamming from other bats and prey. Like for electrical fish that display clear spectral jamming avoidance responses (JAR), some studies have reported that bats mitigate the effects of jamming by shifting the spectral contents of their calls, thereby reducing acoustic interference to improve echo-to-noise ratios (ENR). Here we test the hypothesis that FM bats employ a spectral JAR in response to six masking noise-bands ranging from 15-90kHz, by measuring the -3dB endpoints and peak frequency of echolocation calls from five male Daubenton's bats (Myotis daubentonii) during a landing task. The bats were trained to land on a noise generating spherical transducer surrounded by a star-shaped microphone array, allowing for acoustic localization and source parameter quantification of on-axis calls. We show that the bats did not employ spectral JAR as the peak frequency during jamming remained unaltered compared to silent controls (all P>0.05, 60.73±0.96 kHz) (mean±s.e.m.), and -3dB endpoints decreased in noise irrespective of treatment-type. Instead, Daubenton's bats responded to acoustic jamming by increasing call amplitude via a Lombard response that was bandwidth dependent ranging from 0.05 [0.04-0.06 mean±95% CI] dB/dB noise for the most narrowband (15-30 kHz) to 0.17 [0.16-0.18] dB/dB noise for the most broadband noise (30-90 kHz). We conclude that Daubenton's bats, despite the vocal flexibility to do so, do not employ a spectral JAR, but defend ENRs via a bandwidth dependent Lombard response.

Echo reception in group flight by Japanese horseshoe bats, Rhinolophus ferrumequinum nippon

The ability to detect behaviourally relevant sensory information is crucial for survival. Especially when active-sensing animals behave in proximity, mutual interferences may occur. The aim of this study was to examine how active-sensing animals deal with mutual interferences. Echolocation pulses and returning echoes were compared in spaces of various sizes (wide and narrow) in Rhinolophus ferrumequinum nippon flying alone or in a group of three bats. We found that in the narrow space, the group-flying bats increased the duration and bandwidth of the terminal frequency-modulated component of their vocalizations. By contrast, the frequency of the returning echoes did not differ in the presence of conspecifics. We found that their own echo frequencies were compensated within the narrow frequency ranges by Doppler shift compensation. By contrast, the estimated frequencies of the received pulses emitted by the other bats were much more broadly distributed than their echoes. Our results suggest that the bat auditory systems are sharply tuned to a narrow frequency to filter spectral interference from other bats.

Communication with self, friends and foes in active-sensing animals

Animals that rely on electrolocation and echolocation for navigation and prey detection benefit from sensory systems that can operate in the dark, allowing them to exploit sensory niches with few competitors. Active sensing has been characterized as a highly specialized form of communication, whereby an echolocating or electrolocating animal serves as both the sender and receiver of sensory information. This characterization inspires a framework to explore the functions of sensory channels that communicate information with the self and with others. Overlapping communication functions create challenges for signal privacy and fidelity by leaving active-sensing animals vulnerable to eavesdropping, jamming and masking. Here, we present an overview of active-sensing systems used by weakly electric fish, bats and odontocetes, and consider their susceptibility to heterospecific and conspecific jamming signals and eavesdropping. Susceptibility to interference from signals produced by both conspecifics and prey animals reduces the fidelity of electrolocation and echolocation for prey capture and foraging. Likewise, active-sensing signals may be eavesdropped, increasing the risk of alerting prey to the threat of predation or the risk of predation to the sender, or drawing competition to productive foraging sites. The evolutionary success of electrolocating and echolocating animals suggests that they effectively counter the costs of active sensing through rich and diverse adaptive behaviors that allow them to mitigate the effects of competition for signal space and the exploitation of their signals.

Absence of Jamming Avoidance and Flight Path Similarity in Paired Bent-Winged Bats,

Echolocating bats perceive their surroundings by listening to the echoes of self-generated ultrasound pulses. When multiple conspecifics fly in close proximity to each other, sounds emitted from nearby individuals could mutually interfere with echo reception. Many studies suggest that bats employ frequency shifts to avoid spectral overlap of pulses with other bats. Technical constraints in recording technology have made it challenging to capture subtle changes in the pulse characteristics of bat calls. Therefore, how bats change their behavior to extract their own echoes in the context of acoustic interference remains unclear. Also, to our best knowledge, no studies have investigated whether individual flight paths change when other bats are present, although movements likely reduce acoustic masking. Here, we recorded the echolocation pulses of bats flying alone or in pairs using telemetry microphones. Flight trajectories were also reconstructed using stereo camera recordings. We found no clear tendency to broaden individual differences in the acoustic characteristics of pulses emitted by pairs of bats compared to bats flying alone. However, some bats showed changes in pulse characteristics when in pairs, which suggests that bats can recognize their own calls based on the initial differences in call characteristics between individuals. In addition, we found that the paired bats spend more time flying in the same directions than in the opposite directions. Besides, we found that the flight paths of bats were more similar in “paired flight trials” than in virtual pairs of paired flight trials. Our results suggest that the bats tend to follow the other bat in paired flight. For the following bat, acoustic interference may be reduced, while the opportunity to eavesdrop on other bats’ calls may be increased.

A sensorimotor model shows why a spectral jamming avoidance response does not help bats deal with jamming

For decades, researchers have speculated how echolocating bats deal with masking by conspecific calls when flying in aggregations. To date, only a few attempts have been made to mathematically quantify the probability of jamming, or its effects. We developed a comprehensive sensorimotor predator-prey simulation, modeling numerous bats foraging in proximity. We used this model to examine the effectiveness of a spectral Jamming Avoidance Response (JAR) as a solution for the masking problem. We found that foraging performance deteriorates when bats forage near conspecifics, however, applying a JAR does not improve insect sensing or capture. Because bats constantly adjust their echolocation to the performed task (even when flying alone), further shifting the signals' frequencies does not mitigate jamming. Our simulations explain how bats can hunt successfully in a group despite competition and despite potential masking. This research demonstrates the advantages of a modeling approach when examining a complex biological system.

Modeling active sensing reveals echo detection even in large groups of bats

Active sensing animals perceive their surroundings by emitting probes of energy and analyzing how the environment modulates these probes. However, the probes of conspecifics can jam active sensing, which should cause problems for groups of active sensing animals. This problem was termed the cocktail party nightmare for echolocating bats: as bats listen for the faint returning echoes of their loud calls, these echoes will be masked by the loud calls of other close-by bats. Despite this problem, many bats echolocate in groups and roost socially. Here, we present a biologically parametrized framework to quantify echo detection in groups. Incorporating properties of echolocation, psychoacoustics, acoustics, and group flight, we quantify how well bats flying in groups can detect each other despite jamming. A focal bat in the center of a group can detect neighbors in group sizes of up to 100 bats. With increasing group size, fewer and only the closest and frontal neighbors are detected. Neighbor detection is improved by longer call intervals, shorter call durations, denser groups, and more variable flight and sonar beam directions. Our results provide a quantification of the sensory input of echolocating bats in collective group flight, such as mating swarms or emergences. Our results further generate predictions on the sensory strategies bats may use to reduce jamming in the cocktail party nightmare. Lastly, we suggest that the spatially limited sensory field of echolocators leads to limited interactions within a group, so that collective behavior is achieved by following only nearest neighbors.

The jamming avoidance response in echolocating bats

Bats face many sources of acoustic interference in their natural environments, including other bats and potential prey items that affect their ability to interpret the returning echoes of their biosonar signals. To be able to navigate and forage successfully, bats must be able to counteract this interference and one of the ways they achieve this is by altering the various parameters of their echolocation. We describe these changes in signal design within the context of a modified definition of the jamming avoidance response originally applied to the signal changes of weakly electric fish. Both of these groups use active sensory systems that exhibit similarities in function but we take this opportunity to highlight major differences each groups' response to signal interference. These discrepancies form the basis of our need for an expanded description of the jamming avoidance response in echolocating bats.

Adaptive frequency shifts of echolocation sounds in Miniopterus fuliginosus according to the frequency-modulated pattern of jamming sounds

When flying in a group, echolocating bats have to separate their own echoes from pulses and echoes belonging to other individuals to extract only the information necessary for their own navigation. Previous studies have demonstrated that frequency-modulated (FM) bats change the terminal frequencies (TFs) of downward FM pulses under acoustic interference. However, it is not yet clear which acoustic characteristics of the jamming signals induce the TF shift according to the degree of acoustic interference. In this study, we examined changes in the acoustic characteristics of pulses emitted by Miniopterus fuliginosus while presenting jamming stimuli with different FM patterns to the bat flying alone. Bats significantly altered their TFs when responding to downward (dExp) and upward (uExp) exponential FM sounds as well as to a constant-frequency (CF) stimulus, by approximately 1-2 kHz (dExp: 2.1±0.9 kHz; uExp: 1.7±0.3 kHz; CF: 1.3±0.4 kHz) but not for linear FM sounds. The feature common to the spectra of these three jamming stimuli is a spectrum peak near the TF frequency, demonstrating that the bats shift the TF to avoid masking of jamming sounds on the TF frequency range. These results suggest that direct frequency masking near the TF frequency range induces the TF shift, which simultaneously decreases the similarity between their own echolocation sounds and jamming signals.

Timing and technique impact the effectiveness of road-based, mobile acoustic surveys of bats

Mobile acoustic surveys are a common method of surveying bat communities. However, there is a paucity of empirical studies exploring different methods for conducting mobile road surveys of bats. During 2013, we conducted acoustic mobile surveys on three routes in north‐central Indiana, U.S.A., using (1) a standard road survey, (2) a road survey where the vehicle stopped for 1 min at every half mile of the survey route (called a “start‐stop method”), and (3) a road survey with an individual using a bicycle. Linear mixed models with multiple comparison procedures revealed that when all bat passes were analyzed, using a bike to conduct mobile surveys detected significantly more bat passes per unit time compared to other methods. However, incorporating genus‐level comparisons revealed no advantage to using a bike over vehicle‐based methods. We also found that survey method had a significant effect when analyses were limited to those bat passes that could be identified to genus, with the start–stop method generally detecting more identifiable passes than the standard protocol or bike survey. Additionally, we found that significantly more identifiable bat passes (particularly those of the Eptesicus and Lasiurus genera) were detected in surveys conducted immediately following sunset. As governing agencies, particularly in North America, implement vehicle‐based bat monitoring programs, it is important for researchers to understand how variations on protocols influence the inference that can be gained from different monitoring schemes.