How perceived threat increases synchronization in collectively moving animal groups

Abstract

Nature is rich with many different examples of the cohesive motion of animals. Previous attempts to model collective motion have primarily focused on group behaviours of identical individuals. In contrast, we put our emphasis on modelling the contributions of different individual-level characteristics within such groups by using stochastic asynchronous updating of individual positions and orientations. Our model predicts that higher updating frequency, which we relate to perceived threat, leads to more synchronized group movement, with speed and nearest-neighbour distributions becoming more uniform. Experiments with three-spined sticklebacks (Gasterosteus aculeatus) that were exposed to different threat levels provide strong empirical support for our predictions. Our results suggest that the behaviour of fish (at different states of agitation) can be explained by a single parameter in our model: the updating frequency. We postulate a mechanism for collective behavioural changes in different environment-induced contexts, and explain our findings with reference to confusion and oddity effects.

Adversity magnifies the importance of social information in decision-making

“…This is consistent with the general presence of super-aggregation in adversity [1][2][3][4][5]7], but of course does not rule out additional mechanisms in particular situations, such as collective protection or confusion effects in the case of predation risk. Interestingly, our approach also makes predictions that are probably different from other explanations.…”

“…This phenomenon is well documented in groups of moving animals, which often form tighter groups in response to the detection of a predator [1][2][3][4][5][6]; but it also takes place in other adverse conditions, such as in the absence of food [7] or when animals are introduced into an unknown environment [8,9]. In humans, the occurrence of sudden bank runs [10][11][12] and human stampedes [13 -19] suggests increased aggregation in adversity, although data are insufficient to draw definitive conclusions.…”

From behavioural analyses to models of collective motion in fish schools

“…However, there is a different way to implement stochasticity, which has been recently investigated by Bode et al [80]. Instead of updating in synchronous way the position and velocity of all agents and add to the set of rules a random component, the agent updates are made through a deterministic set of rules in a random order.…”

“…Even though this behaviour is reminiscent of the schools of Paracheirodon innesi (C. Becco & N. Vandewalle 2009, Experimental study of collective behaviours in fish swarms, unpublished data), where the continuous motion of the school is composed of the sum of individual bouts and pauses with no apparent synchronicity (figure 2a), Bode et al emphasize that there is no direct link between the updating frequency and the actual locomotors events. Yet, this new approach has an interesting ability to match experimental data [80]: a simple variation of update frequency can reproduce the speed distributions observed in groups of three spine sticklebacks under various level of agitation as they are frightened, hungry or steady.…”

Distinguishing Social from Nonsocial Navigation in Moving Animal Groups

“…State-of-the-art models for collectively moving groups of socially interacting individuals are based on the finding that individual actions are the combination of simple behavioral rules that can loosely be expressed as "avoid collisions," "align with conspecifics," and "maintain group cohesion." Interactions based on these rules result in complex and realistic movement dynamics (e.g., Couzin et al 2002;Buhl et al 2006;Bode et al 2010). Navigation toward a target or in a target direction can be added to these individual behaviors (Grünbaum 1998;Couzin et al 2005;Codling et al 2007).…”