Integrating evolutionary biology with digital arts to quantify ecological constraints on vision‐based behaviour. Issue 3 (6th November 2017)

• Record Type: Journal Article
• Authors: Bian, Xue; Chandler, Tom; Laird, Warwick; Pinilla, Angela; Peters, Richard
• Editors: Börger, Luca
• Is Part Of: Methods in ecology and evolution. Volume 9:Issue 3(2018)
• Page Start: 544
• Page End: 559
• Publication Date: 2017-11-06
• Subjects: 3D animation -- motion signal -- signal efficacy -- signal evolution -- visual saliency; Ecology -- Periodicals; Evolution -- Periodicals; 577
• DOI: 10.1111/2041-210X.12912
• Languages: English
• ISSNs: 2041-210X

Abstract

Abstract: Motion vision is crucial in the life of animals, in controlling locomotion, in foraging, for predator evasion and in communication. However, information on the conditions for motion vision in natural environments is limited. Advancing knowledge of the ecological limitations that affect functional behaviour requires novel methodologies. To explore motion ecology in more detail we describe an innovative method that integrates evolutionary biology with digital arts. A visualization tool that simulates three spatial dimensions plus movement through time, 3D animation is an innovative approach to understand dynamic environments. Animal signalling systems have provided useful insights into ecological limitations on behaviour, and we demonstrate the utility of our approach by examining motion displays of lizards surrounded by plant motion noise. The effectiveness of signals in noise was considered under different circumstances, and in each case, we had complete control over the simulations. We used these scenarios to both validate our approach and to demonstrate its potential. The relevance to motion signalling of prevailing wind and resultant plant motion is now well established and we begin by replicating this effect and illustrate how we can explore this in quantitative detail. We further demonstrate its utility by providing novel insights into the benefits of signalling in the right place and at the right time, by manipulating immediate signalling backgrounds, variation in signaller–plant distances and light environments. Each of these simulations provide opportunities for investigation that would be impossible in nature. Systematic measurements of motion ecology in detail are now achievable. In addition to insights into the evolution of motion signals, 3D environmental reconstruction will provide a test bed for other topics in the field of motion ecology, and a resource to enhance public engagement with science.