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1. Transfer Entropy Analysis of Interactions between Bats Using Position and Echolocation Data

   https://doi.org/10.3390/e22101176  

   Shaffer, Irena; Abaid, Nicole (October 2020, Entropy)

   null (Ed.)

   Many animal species, including many species of bats, exhibit collective behavior where groups of individuals coordinate their motion. Bats are unique among these animals in that they use the active sensing mechanism of echolocation as their primary means of navigation. Due to their use of echolocation in large groups, bats run the risk of signal interference from sonar jamming. However, several species of bats have developed strategies to prevent interference, which may lead to different behavior when flying with conspecifics than when flying alone. This study seeks to explore the role of this acoustic sensing on the behavior of bat pairs flying together. Field data from a maternity colony of gray bats (Myotis grisescens) were collected using an array of cameras and microphones. These data were analyzed using the information theoretic measure of transfer entropy in order to quantify the interaction between pairs of bats and to determine the effect echolocation calls have on this interaction. This study expands on previous work that only computed information theoretic measures on the 3D position of bats without echolocation calls or that looked at the echolocation calls without using information theoretic analyses. Results show that there is evidence of information transfer between bats flying in pairs when time series for the speed of the bats and their turning behavior are used in the analysis. Unidirectional information transfer was found in some subsets of the data which could be evidence of a leader–follower interaction. 

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2. Echolocating bats adjust sonar call features and head/ear position as they track moving targets in the presence of clutter

   https://doi.org/10.1121/10.0036252  

   Wilkinson, Michael_G T; Wang, XingYao York; Cowan, Noah J; Moss, Cynthia F (March 2025, The Journal of the Acoustical Society of America)

   Echolocating bats often encounter clutter as they pursue insect prey. To probe the adaptive behaviors bats employ to mitigate the effects of clutter, this study quantified echolocation call features and head movements of big brown bats (Eptesicus fuscus) as they tracked a moving prey target in the dark. Bats were trained to rest on a perch and track an approaching target for a food reward. Clutter was positioned at different distances and angular offsets from the bat and the path of a moving target. This study hypothesized that bats dynamically adjust call features and head direction to facilitate target localization in the presence of clutter. The results show that bats shortened call duration and interval and increased head movements when the target was close to clutter. The study also revealed that bats increase the production of sonar strobe groups in cluttered environments, which may sharpen sonar spatial resolution. Spectral analysis showed that maximum call power shifted to lower frequencies when clutter was close to the target. These data demonstrate the big brown bat's range of adaptive behaviors that support target tracking in cluttered environments. 

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3. SVIn2: A multi-sensor fusion-based underwater SLAM system

   https://doi.org/10.1177/02783649221110259  

   Rahman, Sharmin; Quattrini_Li, Alberto; Rekleitis, Ioannis (July 2022, The International Journal of Robotics Research)

   This paper presents SVIn2, a novel tightly-coupled keyframe-based Simultaneous Localization and Mapping (SLAM) system, which fuses Scanning Profiling Sonar, Visual, Inertial, and water-pressure information in a non-linear optimization framework for small and large scale challenging underwater environments. The developed real-time system features robust initialization, loop-closing, and relocalization capabilities, which make the system reliable in the presence of haze, blurriness, low light, and lighting variations, typically observed in underwater scenarios. Over the last decade, Visual-Inertial Odometry and SLAM systems have shown excellent performance for mobile robots in indoor and outdoor environments, but often fail underwater due to the inherent difficulties in such environments. Our approach combats the weaknesses of previous approaches by utilizing additional sensors and exploiting their complementary characteristics. In particular, we use (1) acoustic range information for improved reconstruction and localization, thanks to the reliable distance measurement; (2) depth information from water-pressure sensor for robust initialization, refining the scale, and assisting to limit the drift in the tightly-coupled integration. The developed software—made open source—has been successfully used to test and validate the proposed system in both benchmark datasets and numerous real world underwater scenarios, including datasets collected with a custom-made underwater sensor suite and an autonomous underwater vehicle Aqua2. SVIn2 demonstrated outstanding performance in terms of accuracy and robustness on those datasets and enabled other robotic tasks, for example, planning for underwater robots in presence of obstacles. 

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4. Extracting Interactions between Flying Bat Pairs Using Model-Free Methods

   https://doi.org/10.3390/e21010042  

   Roy, Subhradeep; Howes, Kayla; Müller, Rolf; Butail, Sachit; Abaid, Nicole (January 2019, Entropy)

   Social animals exhibit collective behavior whereby they negotiate to reach an agreement, such as the coordination of group motion. Bats are unique among most social animals, since they use active sensory echolocation by emitting ultrasonic waves and sensing echoes to navigate. Bats’ use of active sensing may result in acoustic interference from peers, driving different behavior when they fly together rather than alone. The present study explores quantitative methods that can be used to understand whether bats flying in pairs move independently of each other or interact. The study used field data from bats in flight and is based on the assumption that interactions between two bats are evidenced in their flight patterns. To quantify pairwise interaction, we defined the strength of coupling using model-free methods from dynamical systems and information theory. We used a control condition to eliminate similarities in flight path due to environmental geometry. Our research question is whether these data-driven methods identify directed coupling between bats from their flight paths and, if so, whether the results are consistent between methods. Results demonstrate evidence of information exchange between flying bat pairs, and, in particular, we find significant evidence of rear-to-front coupling in bats’ turning behavior when they fly in the absence of obstacles. 

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5. High duty cycle moth sounds jam bat echolocation: bats counter with compensatory changes in buzz duration

   https://doi.org/10.1242/jeb.244187  

   Fernández, Yohami; Dowdy, Nicolas J.; Conner, William E. (September 2022, Journal of Experimental Biology)

   ABSTRACT Tiger moth species vary greatly in the number of clicks they produce and the resultant duty cycle. Signals with higher duty cycles are expected to more effectively interfere with bat sonar. However, little is known about the minimum duty cycle of tiger moth signals for sonar jamming. Is there a threshold that allows us to classify moths as acoustically aposematic versus sonar jammers based on their duty cycles? We performed playback experiments with three wild-caught adult male bats, Eptesicus fuscus. Bat attacks on tethered moths were challenged using acoustic signals of Bertholdia trigona with modified duty cycles ranging from 0 to 46%. We did not find evidence for a duty cycle threshold; rather, the ability to jam the bat's sonar was a continuous function of duty cycle consistent with a steady increase in the number of clicks arriving during a critical signal processing time window just prior to the arrival of an echo. The proportion of successful captures significantly decreased as the moth duty cycle increased. Our findings suggest that moths cannot be unambiguously classified as acoustically aposematic or sonar jammers based solely on duty cycle. Bats appear to compensate for sonar jamming by lengthening the duration of their terminal buzz and they are more successful in capturing moths when they do so. In contrast to previous findings for bats performing difficult spatial tasks, the number of sonar sound groups decreased in response to high duty cycles and did not affect capture success. 

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