Responsive robotic prey reveal how predators adapt to predictability in escape tactics

Abstract

Significance A widespread strategy used by prey animals, seen in insects, mammals, amphibians, crustaceans, fish, and reptiles, is to vary the direction in which they escape when attacked by a predator. This unpredictability is thought to benefit prey by inhibiting predators from predicting the prey’s escape trajectory, but experimental evidence is lacking. Using fish predators repeatedly tested with interactive, robot-controlled prey escaping in the same (predictable) or in random (unpredictable) directions, we find no clear benefit to prey of escaping unpredictably, driven by behavioral counteradaptation by the predators. The benefit of unpredictable escape behavior may depend on whether predators are able to counteract prey escape tactics by flexibly modifying their behavior, or unpredictability may instead be explained biomechanical or sensory constraints.

Predatory fish preferentially target virtual prey with Lévy motion rather than Brownian motion

“…The advantage of a virtual prey system allowing for precise control over prey traits and hence minimising confounding effects is, however, countered by the limited range of predators that are suitable for testing in such an artificial, laboratory-based set up. Another valuable extension of the results here would be to explore the consequence of allowing predators repeated exposure to prey that vary in their movement pattern, as recently we have shown that predators can adapt to unpredictability of fleeing prey [16]. Any such future work would ideally not only consider the choice of which prey is targeted amongst those displaying different types of motion, but also allow the prey to be captured and consumed so that attack success can be measured.…”

“…However, except for apex predators, how animals move in space also determines encounter rates with, and conspicuousness to, their own predators [10–12]. It is also generally considered that unpredictable movement by prey may hinder capture by predators [13–15, although see 16]; the lack of turns during longer step lengths may increase the short-term predictability of movement and so increase predation risk. Here we use a system of fish predators (three-spined sticklebacks, Gasterosteus aculeatus ) targeting computer-generated prey whose motion can be entirely controlled [17,18] to test the hypothesis that prey with Lévy motion are targeted preferentially relative to prey with Brownian motion, potentially revealing a cost of Lévy motion that counteracts the benefits for finding resources [4–7].…”

Antipredator defences in motion: animals reduce predation risks by concealing or misleading motion signals

“…The effectiveness of protean motion may also differ depending on the predators' approach to the prey. For instance, an ambush predator may be less likely to adjust and modify their trajectory and tactics rapidly, compared to a pursuit predator (Szopa-Comley & Ioannou, 2022). Furthermore, unpredictable motion may be more effective during initial attempts to escape, as the predator may adapt to the prey's path after a certain period.…”

Mechanisms of group‐hunting in vertebrates

“…during searches and increase individual foraging efficiency for predators; indeed, this has been shown to be a vitalcomponent of the hunt when predators such as porpoises and seabirds search for fish schools (Norris et al, 1961;Hoffman, Heinemann & Wiens, 1981;Götmark, Winkler & Andersson, 1986;Barrett-Lennard, Ford & Heise, 1996;Benoit-Bird, Würsig & McFadden, 2004;Benoit-Bird & Au, 2009;Goodale et al, 2010;Assali, Bez & Tremblay, 2020). Flock leaders in colonies of black-billed gulls (Larus bulleri) call for flock mates to follow them during hunting outings (active information sharing; Evans, 1982) and during Cape gannet (Morus capensis) hunting trips aimed at fish schools, conspecifics act as directional cues and reduce the time to find a patch by half (passive information sharing; Thiebault et al, 2014a). Some toothed whales are estimated to be able to detect prey up to 300 m away using echolocation (Madsen et al, 2007), and it may be possible that conspecifics eavesdrop on the echoes of their groupmates (passive information sharing).…”

“…In these experiments, the precise movements of robotic prey (or predators) can be programmed to provide controls that are impossible with real animals (Bierbach et al ., 2021; Landgraf et al ., 2021). Recently, robotic fish have been used as prey to test how the predictability of the escape path affects predator pursuit behaviour (Szopa‐Comley & Ioannou, 2022), and robots have also been used to assess differences in social responsiveness between social partners (Bierbach et al ., 2018) and how movement variables such as speed drive patterns of collective movement (Jolles et al ., 2020).…”