Distinguishing Social from Nonsocial Navigation in Moving Animal Groups

Many animals, such as migrating shoals of fish, navigate in groups. Knowing the mechanisms involved in animal navigation is important when it comes to explaining navigation accuracy, dispersal patterns, population and evolutionary dynamics, and consequently, the design of conservation strategies. When navigating toward a common target, animals could interact socially by sharing available information directly or indirectly, or each individual could navigate by itself and aggregations may not disperse because all animals are moving toward the same target. Here we present an analysis technique that uses individual movement trajectories to determine the extent to which individuals in navigating groups interact socially, given knowledge of their target. The basic idea of our approach is that the movement directions of individuals arise from a combination of responses to the environment and to other individuals. We estimate the relative importance of these responses, distinguishing between social and nonsocial interactions. We develop and test our method, using simulated groups, and we demonstrate its applicability to empirical data in a case study on groups of guppies moving toward shelter in a tank. Our approach is generic and can be extended to different scenarios of animal group movement. © 2012 by The University of Chicago

Individual – to – resource landscape interaction strength can explain different collective feeding behaviours

Taking in sufficient quantities of nutrients is vital for all living beings and in doing so, individuals interact with the local resource environment. Here, we focus explicitly on the interactions between feeding individuals and the resource landscape. In particular, we are interested in the emergent movement dynamics resulting from these interactions. We present an individual-based simulation model for the movement of populations in a resource landscape that allows us to vary the strength of the interactions mentioned above. The key assumption and novelty of our model is that individuals can cause the release of additional nutrients, as well as consuming them. Our model produces clear predictions. For example, we expect more tortuous individual movement paths and higher levels of aggregation in populations occupying homogeneous environments where individual movement makes more nutrients available. We also show how observed movement dynamics could change when local nutrient sources are depleted or when the population density increases. Our predictions are testable and qualitatively reproduce the different feeding behaviours observed in filter-feeding ducks, for example. We suggest that considering two-way interactions between feeding individuals and resource landscapes could help to explain fine-scale movement dynamics

Human exit route choice in virtual crowd evacuations

The collective behaviour of human crowds emerges from the local interactions of individuals. To understand human crowds we therefore need to identify the behavioural rules individual pedestrians follow. This is crucial for the control of emergency evacuations from confined spaces, for example. At a microscopic level we seek to predict the next step of pedestrians based on their local environment. However, we also have to consider 'tactical-level' individual behaviour that is not an immediate response to the local environment, such as the choice between different routes to exit a building. We used an interactive virtual environment to study human exit route decisions in simulated evacuations. Participants had to escape from a building and had to choose between different exit routes in the presence of evacuating simulated agents. We found no inherent preference for familiar routes, but under a stress-inducing treatment, subjects were more likely to display behaviour in their route choice that was detrimental to their evacuation time. Most strikingly, subjects were less likely to avoid a congested exit by changing their original decision to move towards it under this treatment. Age and gender had clear effects on reaction times in the virtual environment. © 2013 The Association for the Study of Animal Behaviour