Information transfer in moving animal groups

Moving animal groups provide some of the most intriguing and difficult to characterise examples of collective behaviour. We review some recent (and not so recent) empirical research on the motion of animal groups, including fish, locusts and homing pigeons. An important concept which unifies our understanding of these groups is that of transfer of directional information. Individuals which change their direction of travel in response to the direction taken by their near neighbours can quickly transfer information about the presence of a predatory threat or food source. We show that such information transfer is optimised when the density of individuals in a group is close to that at which a phase transition occurs between random and ordered motion. Similarly, we show that even relatively small differences in information possessed by group members can lead to strong collective-level decisions for one of two options. By combining the use of self-propelled particle and social force models of collective motion with thinking about the evolution of flocking we aim to better understand how complexity arises within these groups.

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Tendency-distance models of social cohesion in animal groups

Although it has been assumed that attraction and repulsion between social individuals constitute a basis for group cohesion, there has been no systematic study of the possible ways in which these tendencies might vary with inter-individual distance (IID), or of associated implications for group structure. In this paper, a family of attraction/repulsion--distance functions is described. Computer simulation was used to examine the effects of each function on group cohesion, as reflected by mean values and variability in IID and group shape. Our results showed that: (a) all models led to stability in group structure, but differed significantly in terms of stable IID and group shape characteristics; (b) cohesion was best served by an upwardly convex behaviour--distance function in which maximum attraction equaled maximum repulsion (and the biological plausibility of this function is discussed); (c) group elongation and variability in mean IID were significantly positively correlated; (d) although dyads maintained an equilibrial separation distance, at which attraction balanced repulsion, in larger groups stable nearest neighbour distances were often less than the equilibrium distance; and (e) individuals needed to monitor and respond to only relatively few of their companions in order to avoid group fragmentation.     

How perceived threat increases synchronization in collectively moving animal groups

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.     

Bayesian inference for identifying interaction rules in moving animal groups

The emergence of similar collective patterns from different self-propelled particle models of animal groups points to a restricted set of "universal" classes for these patterns. While universality is interesting, it is often the fine details of animal interactions that are of biological importance. Universality thus presents a challenge to inferring such interactions from macroscopic group dynamics since these can be consistent with many underlying interaction models. We present a Bayesian framework for learning animal interaction rules from fine scale recordings of animal movements in swarms. We apply these techniques to the inverse problem of inferring interaction rules from simulation models, showing that parameters can often be inferred from a small number of observations. Our methodology allows us to quantify our confidence in parameter fitting. For example, we show that attraction and alignment terms can be reliably estimated when animals are milling in a torus shape, while interaction radius cannot be reliably measured in such a situation. We assess the importance of rate of data collection and show how to test different models, such as topological and metric neighbourhood models. Taken together our results both inform the design of experiments on animal interactions and suggest how these data should be best analysed.     

Context dependence of personalities: risk-taking behavior in a social and a nonsocial situation

Individuals of many species differ consistently in their behavioralreaction to mild novel challenges. Suites of these behaviorsare referred to as behavioral syndromes or personalities. Personalitytraits are often phenotypically and genetically correlated.Therefore, animal personalities are generally considered asbroad characteristics, with one underlying genetical and physiologicalmechanism that is expressed across situations and contexts.Because there are carryover effects between situations, animalsare not entirely flexible in their behavior in each situation.This may cause behaviors to seem nonadaptive in isolated situations.To test whether individuals with different personalities couldreact differently to changes in their environment, we studiedcontext dependence of personalities in the great tit (Parusmajor). We tested birds categorized as either fast or slow explorersfor their latency to come back to a feeding table after a mildstartle (risk-taking behavior) in a nonsocial followed by asocial context. We found that the relation between exploratorybehavior and risk-taking behavior depended on the social context.Females in general returned later in the social test, whilemale reaction to the presence of a conspecific was dependenton their behavioral type. Slow males thereby reacted to thebehavior of the companion and fast males did not. These resultsshow that although personalities have a rigid structure therelation between personality traits is context dependent. Theseresults are discussed in the perspective of the adaptive significanceand maintenance of personalities.     

Animal navigation: the difficulty of moving in a straight line

In principle, there are two strategies for navigating a straight course. One is to use an external directional reference and continually reorienting with reference to it, while the other is to infer body rotations from internal sensory information only. We show here that, while the first strategy will enable an animal or mobile agent to move arbitrarily far away from its starting point, the second strategy will not do so, even after an infinite number of steps. Thus, an external directional reference—some form of compass—is indispensable for ensuring progress away from home. This limitation must place significant constraints on the evolution of biological navigation systems. Some specific examples are discussed. An important corollary arising from the analysis of compassless navigation is that the maximum expected displacement represents a robust measure of the straightness of a path.     

Hypothesis testing in animal social networks

Behavioural ecologists are increasingly using social network analysis to describe the social organisation of animal populations and to test hypotheses. However, the statistical analysis of network data presents a number of challenges. In particular the non-independent nature of the data violates the assumptions of many common statistical approaches. In our opinion there is currently confusion and uncertainty amongst behavioural ecologists concerning the potential pitfalls when hypotheses testing using social network data. Here we review what we consider to be key considerations associated with the analysis of animal social networks and provide a practical guide to the use of null models based on randomisation to control for structure and non-independence in the data.     

Controlling airborne cues to study small animal navigation

Small animals such as nematodes and insects analyze airborne chemical cues to infer the direction of favorable and noxious locations. In these animals, the study of navigational behavior evoked by airborne cues has been limited by the difficulty of precisely controlling stimuli. We present a system that can be used to deliver gaseous stimuli in defined spatial and temporal patterns to freely moving small animals. We used this apparatus, in combination with machine-vision algorithms, to assess and quantify navigational decision making of Drosophila melanogaster larvae in response to ethyl acetate (a volatile attractant) and carbon dioxide (a gaseous repellant).     

The neural mechanisms of long distance animal navigation

Animal navigation is a complex process involving the integration of many sources of specialized sensory information for navigation in near and far space. Our understanding of the neurobiological underpinnings of near-space navigation is well-developed, whereas the neural mechanisms of long-distance navigation are just beginning to be unraveled. One crucial question for future research is whether the near space concepts of place cells, head direction cells, and maps in the entorhinal cortex scale up to animals navigating over very long distances and whether they are related to the map and compass concepts of long-distance navigation.     

Distinguishing Family from Friends

Kinship and friendship are key human relationships. Increasingly, data suggest that people are not less altruistic toward friends than close kin. Some accounts suggest that psychologically we do not distinguish between them; countering this is evidence that kinship provides a unique explanatory factor. Using the Implicit Association Test, we examined how people implicitly think about close friends versus close kin in three contexts. In Experiment 1, we examined generic attitudinal dispositions toward friends and family. In Experiment 2, attitude similarity as a marker of family and friends was examined, and in Experiments 3 and 4, strength of in-group membership for family and friends was examined. Findings show that differences exist in implicit cognitive associations toward family and friends. There is some evidence that people hold more positive general dispositions toward friends, associate attitude similarity more with friends, consider family as more representative of the in-group than friends, but see friends as more in-group than distant kin.     

Motion-guided attention promotes adaptive communications during social navigation

Animals are capable of enhanced decision making through cooperation, whereby accurate decisions can occur quickly through decentralized consensus. These interactions often depend upon reliable social cues, which can result in highly coordinated activities in uncertain environments. Yet information within a crowd may be lost in translation, generating confusion and enhancing individual risk. As quantitative data detailing animal social interactions accumulate, the mechanisms enabling individuals to rapidly and accurately process competing social cues remain unresolved. Here, we model how motion-guided attention influences the exchange of visual information during social navigation. We also compare the performance of this mechanism to the hypothesis that robust social coordination requires individuals to numerically limit their attention to a set of n-nearest neighbours. While we find that such numerically limited attention does not generate robust social navigation across ecological contexts, several notable qualities arise from selective attention to motion cues. First, individuals can instantly become a local information hub when startled into action, without requiring changes in neighbour attention level. Second, individuals can circumvent speed–accuracy trade-offs by tuning their motion thresholds. In turn, these properties enable groups to collectively dampen or amplify social information. Lastly, the minority required to sway a group''s short-term directional decisions can change substantially with social context. Our findings suggest that motion-guided attention is a fundamental and efficient mechanism underlying collaborative decision making during social navigation.