Control of self-motion in dynamic fluids: fish do it differently from bees

Scholtyssek, Christine; Dacke, Marie; Kröger, Ronald H. H.; Baird, Emily

doi:10.1098/rsbl.2014.0279

Cited by 20 publications

(20 citation statements)

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“…Hence an organism's response to flow conditions, or lack thereof, will influence its travel duration, route, total energy expenditure, and whether a destination (goal) can actually be reached [ 5 , 6 ]. Not surprisingly, animals across taxa have evolved mechanisms to gauge and react to the surrounding flow [ 2 , 7 – 10 ].…”

Section: Introductionmentioning

confidence: 99%

Optimal orientation in flows: providing a benchmark for animal movement strategies

McLaren

Shamoun‐Baranes

Dokter

et al. 2014

J. R. Soc. Interface.

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Animal movements in air and water can be strongly affected by experienced flow. While various flow-orientation strategies have been proposed and observed, their performance in variable flow conditions remains unclear. We apply control theory to establish a benchmark for time-minimizing (optimal) orientation. We then define optimal orientation for movement in steady flow patterns and, using dynamic wind data, for short-distance mass movements of thrushes (Turdus sp.) and 6000 km non-stop migratory flights by great snipes, Gallinago media. Relative to the optimal benchmark, we assess the efficiency (travel speed) and reliability (success rate) of three generic orientation strategies: full compensation for lateral drift, vector orientation (single-heading movement) and goal orientation (continually heading towards the goal). Optimal orientation is characterized by detours to regions of high flow support, especially when flow speeds approach and exceed the animal's self-propelled speed. In strong predictable flow (short distance thrush flights), vector orientation adjusted to flow on departure is nearly optimal, whereas for unpredictable flow (inter-continental snipe flights), only goal orientation was near-optimally reliable and efficient. Optimal orientation provides a benchmark for assessing efficiency of responses to complex flow conditions, thereby offering insight into adaptive flow-orientation across taxa in the light of flow strength, predictability and navigation capacity.

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Section: Introductionmentioning

confidence: 99%

Optimal orientation in flows: providing a benchmark for animal movement strategies

McLaren

Shamoun‐Baranes

Dokter

et al. 2014

J. R. Soc. Interface.

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“…This finding has implications for studies across other taxa: a tendency to steer away from vertical gratings does not necessarily imply a response to nasal-to-temporal pattern velocity (e.g., refs. 4,34,35).…”

Section: Discussionmentioning

confidence: 99%

Visual guidance of forward flight in hummingbirds reveals control based on image features instead of pattern velocity

Dakin

Fellows

Altshuler

2016

Proc. Natl. Acad. Sci. U.S.A.

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Information about self-motion and obstacles in the environment is encoded by optic flow, the movement of images on the eye. Decades of research have revealed that flying insects control speed, altitude, and trajectory by a simple strategy of maintaining or balancing the translational velocity of images on the eyes, known as pattern velocity. It has been proposed that birds may use a similar algorithm but this hypothesis has not been tested directly. We examined the influence of pattern velocity on avian flight by manipulating the motion of patterns on the walls of a tunnel traversed by Anna's hummingbirds. Contrary to prediction, we found that lateral course control is not based on regulating nasal-to-temporal pattern velocity. Instead, birds closely monitored feature height in the vertical axis, and steered away from taller features even in the absence of nasalto-temporal pattern velocity cues. For vertical course control, we observed that birds adjusted their flight altitude in response to upward motion of the horizontal plane, which simulates vertical descent. Collectively, our results suggest that birds avoid collisions using visual cues in the vertical axis. Specifically, we propose that birds monitor the vertical extent of features in the lateral visual field to assess distances to the side, and vertical pattern velocity to avoid collisions with the ground. These distinct strategies may derive from greater need to avoid collisions in birds, compared with small insects. The translational motion of images on the eye (hereafter referred to as "pattern velocity") provides a rich source of information about selfmotion and the surrounding environment and has been shown to play a prominent role in the visual guidance strategies of all flying animals studied to date (2-5). Honey bees use pattern velocity for a diverse set of flight controls: they balance pattern velocity on their left and right sides to navigate narrow passageways (6); they regulate pattern velocity to control their flight speed (7) and altitude (8); and they integrate pattern velocity to estimate distances to foraging sites, communicating this information to hivemates (9, 10). Pattern velocity thus represents an elegant solution to insect flight control that is robust to a range of spatial frequencies and contrasts (2, 3, 6, 7).In the first study to ask whether birds also use a similar strategy, Bhagavatula et al. (11) trained five budgerigars to fly repeatedly down a tunnel. The authors found that like bees (6), the budgerigars steered away from vertically oriented gratings that provided strong nasal-to-temporal (fore-aft) pattern velocity, and toward horizontally oriented gratings and blank walls that provided little to no nasal-to-temporal pattern velocity. However, because Bhagavatula et al. (11) used only stationary gratings and did not manipulate pattern velocity directly, the exact mechanism used by birds remains to be confirmed. More recent experiments demonstrate that pattern velocity does not affect the flight speed of budgerigars (12) ...

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“…For example, optic flow, the angular velocity of image motion across the retina (Gibson, 1979), provides continuous feedback to an animal about its relative velocity and distance to objects in its environment (Srinivasan et al, 1991(Srinivasan et al, , 1996. In several behavioral studies, visually guided animals, such as honeybees (Baird et al, 2005;Srinivasan et al, 1991Srinivasan et al, , 1996, Drosophila (David, 1982) and budgerigars (Bhagavatula et al, 2011), have been shown to adapt their flight trajectory and speed in response to experimental manipulation of optic flow patterns (Baird et al, 2005(Baird et al, , 2010Bhagavatula et al, 2011;Dyhr and Higgins, 2010;Linander et al, 2015;Scholtyssek et al, 2014;Srinivasan et al, 1991Srinivasan et al, , 1996.…”

Section: Introductionmentioning

confidence: 99%

Echo interval and not echo intensity drives bat flight behavior in structured corridors

Warnecke

Macías

Falk

et al. 2018

Journal of Experimental Biology

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To navigate in the natural environment, animals must adapt their locomotion in response to environmental stimuli. The echolocating bat relies on auditory processing of echo returns to represent its surroundings. Recent studies have shown that echo flow patterns influence bat navigation, but the acoustic basis for flight path selection remains unknown. To investigate this problem, we released bats in a flight corridor with walls constructed of adjacent individual wooden poles, which returned cascades of echoes to the flying bat. We manipulated the spacing and echo strength of the poles comprising each corridor side, and predicted that bats would adapt their flight paths to deviate toward the corridor side returning weaker echo cascades. Our results show that the bat's trajectory through the corridor was not affected by the intensity of echo cascades. Instead, bats deviated toward the corridor wall with more sparsely spaced, highly reflective poles, suggesting that pole spacing, rather than echo intensity, influenced bat flight path selection. This result motivated investigation of the neural processing of echo cascades. We measured local evoked auditory responses in the bat inferior colliculus to echo playback recordings from corridor walls constructed of sparsely and densely spaced poles. We predicted that evoked neural responses would be discretely modulated by temporally distinct echoes recorded from the sparsely spaced pole corridor wall, but not by echoes from the more densely spaced corridor wall. The data confirm this prediction and suggest that the bat's temporal resolution of echo cascades may drive its flight behavior in the corridor.

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Control of self-motion in dynamic fluids: fish do it differently from bees

Cited by 20 publications

References 15 publications

Optimal orientation in flows: providing a benchmark for animal movement strategies

Optimal orientation in flows: providing a benchmark for animal movement strategies

Visual guidance of forward flight in hummingbirds reveals control based on image features instead of pattern velocity

Echo interval and not echo intensity drives bat flight behavior in structured corridors

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