Computerized stimuli for studying oddity effects

Abstract

Visually hunting predators must overcome the challenges that prey groups present. One such challenge is the confusion effect where an overburdened visual system means predators are unable to successfully target prey. A strategy to overcome confusion is the targeting of distinct, or odd, individuals (the oddity effect). In live prey experiments, manipulation of group member phenotypes can be challenging and prey may differ on more than the single feature one intends to define as odd. The use of highly controllable computerized stimuli to study predator–prey interactions is increasingly popular in the field of behavioral ecology. However, to our knowledge, the validity of computerized stimuli to study the oddity effect has not been established. Predator choice experiments were conducted using naive stickleback predators to ascertain whether the oddity effect could be demonstrated in the absence of live prey. We found evidence for both the oddity effect and preferential targeting of group edges and low-density regions, as would be predicted if predators targeted prey individuals to minimize confusion. The oddity effect was evident at a low threshold, above which dots were no longer perceived as odd and no longer attacked more often than expected by chance. We conclude that computerized stimuli are an improved, practical method for studying oddity effects while further validating the use of similar methods for studying other aspects of visual predation. In addition to higher control of “prey” appearance, the replacement of live prey animals with digital stimuli is ethically beneficial and reusing code improves experimental efficiency.

The measure of spatial position within groups that best predicts predation risk depends on group movement

“…We predicted that centre-edge measures of spatial position would better predict predation risk in moving groups due to the greater encounter rate with moving groups, especially at the front of the prey group [10]. By presenting real predators with virtual prey, the limitations of studies using predators attacking live prey, and simulated predators targeting simulated prey, can be overcome [3,9,25].…”

Virtual prey with Lévy motion are preferentially attacked by predatory fish

“…It is generally considered that unpredictable movement by prey may hinder capture by predators ( Humphries and Driver 1970 ; Jones et al 2011 ; Richardson et al 2018 ; although see Szopa-Comley and Ioannou 2022 ); the lack of turns during longer step lengths, which are more common in Lévy trajectories, 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 ( Duffield and Ioannou 2017 ; Dobbinson et al 2020 ; Lambert et al 2021 ) 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 ( Viswanathan et al 1999 ; Bartumeus et al 2002 ; Humphries et al 2012 ; Guinard and Korman 2021 ). Brownian motion was used as the control treatment in comparison to Lévy motion as the contrast between these two movement patterns has been studied extensively in previous studies of animal movement ( Bartumeus et al 2002 ; Humphries et al 2010 ; Sims et al 2012 ; de Jager et al 2013 ; Abe and Shimada 2015 ).…”

The measure of spatial position within groups that best predicts predation risk depends on group movement

“…The spatial positions of targeted and non-targeted prey were defined according to different measures previously used in the literature, and the success of each measure in predicting the likelihood of predation (i.e., attack) was assessed with an information criterion model comparison approach. By presenting real predators with virtual prey, the limitations of studies using predators attacking live prey, and simulated predators targeting simulated prey, can be overcome [3,9,24].…”