Computerized stimuli for studying oddity effects

Dobbinson, Khia E.; Morrell, Lesley J.; Skarratt, Paul A.

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.

Citation

Dobbinson, K. E., Morrell, L. J., & Skarratt, P. A. (2020). Computerized stimuli for studying oddity effects. Behavioral ecology, 31(1), 176-183. https://doi.org/10.1093/beheco/arz174

• Journal Article Type: Article
• Acceptance Date: Aug 19, 2019
• Online Publication Date: Oct 16, 2019
• Publication Date: Jan 31, 2020
• Deposit Date: Sep 9, 2019
• Publicly Available Date: Oct 17, 2020
• Journal: Behavioral Ecology
• Print ISSN: 1045-2249
• Electronic ISSN: 1465-7279
• Publisher: Oxford University Press
• Peer Reviewed: Peer Reviewed
• Volume: 31
• Issue: 1
• Pages: 176-183
• DOI: https://doi.org/10.1093/beheco/arz174
• Public URL: https://hull-repository.worktribe.com/output/2633143