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      Echolocating Bats Use a Nearly Time-Optimal Strategy to Intercept Prey


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          Acquisition of food in many animal species depends on the pursuit and capture of moving prey. Among modern humans, the pursuit and interception of moving targets plays a central role in a variety of sports, such as tennis, football, Frisbee, and baseball. Studies of target pursuit in animals, ranging from dragonflies to fish and dogs to humans, have suggested that they all use a constant bearing (CB) strategy to pursue prey or other moving targets. CB is best known as the interception strategy employed by baseball outfielders to catch ballistic fly balls. CB is a time-optimal solution to catch targets moving along a straight line, or in a predictable fashion—such as a ballistic baseball, or a piece of food sinking in water. Many animals, however, have to capture prey that may make evasive and unpredictable maneuvers. Is CB an optimum solution to pursuing erratically moving targets? Do animals faced with such erratic prey also use CB? In this paper, we address these questions by studying prey capture in an insectivorous echolocating bat. Echolocating bats rely on sonar to pursue and capture flying insects. The bat's prey may emerge from foliage for a brief time, fly in erratic three-dimensional paths before returning to cover. Bats typically take less than one second to detect, localize and capture such insects. We used high speed stereo infra-red videography to study the three dimensional flight paths of the big brown bat, Eptesicus fuscus, as it chased erratically moving insects in a dark laboratory flight room. We quantified the bat's complex pursuit trajectories using a simple delay differential equation. Our analysis of the pursuit trajectories suggests that bats use a constant absolute target direction strategy during pursuit. We show mathematically that, unlike CB, this approach minimizes the time it takes for a pursuer to intercept an unpredictably moving target. Interestingly, the bat's behavior is similar to the interception strategy implemented in some guided missiles. We suggest that the time-optimal strategy adopted by the bat is in response to the evolutionary pressures of having to capture erratic and fast moving insects.


          Analysis of the three dimensional flight paths of the big brown bat reveals a similar strategy to intercept targets as used by some guided missiles.

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          Most cited references43

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          The echolocation of flying insects by bats

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            Echolocation and pursuit of prey by bats.

            Echolocating bats use different information-gathering strategies for hunting prey in open, uncluttered environments, in relatively open environments with some obstacles, and in densely cluttered environments. These situations differ in the extent to which individual targets such as flying insects can be detected as isolated objects or must be separated perceptually from backgrounds. Echolocating bats also differ in whether they use high-resolution, multidimensional images of targets or concentrate specifically on one particular target dimension, such as movement, to detect prey.
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              Echolocation behavior of big brown bats, Eptesicus fuscus, in the field and the laboratory.

              Echolocation signals were recorded from big brown bats, Eptesicus fuscus, flying in the field and the laboratory. In open field areas the interpulse intervals (IPI) of search signals were either around 134 ms or twice that value, 270 ms. At long IPI's the signals were of long duration (14 to 18-20 ms), narrow bandwidth, and low frequency, sweeping down to a minimum frequency (Fmin) of 22-25 kHz. At short IPI's the signals were shorter (6-13 ms), of higher frequency, and broader bandwidth. In wooded areas only short (6-11 ms) relatively broadband search signals were emitted at a higher rate (avg. IPI= 122 ms) with higher Fmin (27-30 kHz). In the laboratory the IPI was even shorter (88 ms), the duration was 3-5 ms, and the Fmin 30- 35 kHz, resembling approach phase signals of field recordings. Excluding terminal phase signals, all signals from all areas showed a negative correlation between signal duration and Fmin, i.e., the shorter the signal, the higher was Fmin. This correlation was reversed in the terminal phase of insect capture sequences, where Fmin decreased with decreasing signal duration. Overall, the signals recorded in the field were longer, with longer IPI's and greater variability in bandwidth than signals recorded in the laboratory.

                Author and article information

                Role: Academic Editor
                PLoS Biol
                PLoS Biology
                Public Library of Science (San Francisco, USA )
                May 2006
                18 April 2006
                : 4
                : 5
                : e108
                [1] 1Neuroscience and Cognitive Science Program, University of Maryland, College Park, Maryland, United States of America
                [2] 2Department of Psychology, University of Maryland, College Park, Maryland, United States of America
                [3] 3Department of Electrical and Computer Engineering, University of Maryland, College Park, Maryland, United States of America
                [4] 4Institute for Systems Research, University of Maryland, College Park, Maryland, United States of America
                California Institute of Technology United States of America
                Copyright: © 2006 Ghose et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                : 8 November 2005
                : 8 February 2006
                Research Article
                Animal Behavior
                Bioinformatics/Computational Biology
                Systems Biology

                Life sciences
                Life sciences


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