Using Hidden Markov Models to characterise intermittent social behaviour in fish shoals.

The movement of animals in groups is widespread in nature. Understanding this phenomenon presents an important problem in ecology with many applications that range from conservation to robotics. Underlying all group movements are interactions between individual animals and it is therefore crucial to understand the mechanisms of this social behaviour. To date, despite promising methodological developments, there are few applications to data of practical statistical techniques that inferentially investigate the extent and nature of social interactions in group movement. We address this gap by demonstrating the usefulness of a Hidden Markov Model approach to characterise individual-level social movement in published trajectory data on three-spined stickleback shoals (Gasterosteus aculeatus) and novel data on guppy shoals (Poecilia reticulata). With these models, we formally test for speed-mediated social interactions and verify that they are present. We further characterise this inferred social behaviour and find that despite the substantial shoal-level differences in movement dynamics between species, it is qualitatively similar in guppies and sticklebacks. It is intermittent, occurring in varying numbers of individuals at different time points. The speeds of interacting fish follow a bimodal distribution, indicating that they are either stationary or move at a preferred mean speed, and social fish with more social neighbours move at higher speeds, on average. Our findings and methodology present steps towards characterising social behaviour in animal groups.

Balancing direct and indirect sources of navigational information in a leaderless model of collective animal movement.

Navigation is an important movement process that enables individuals and groups of animals to find targets in space at different spatio-temporal scales. Earlier studies have shown how being in a group can confer navigational advantages to individuals, either through following more experienced leaders or through the pooling of many inaccurate compasses, a process known as the 'many wrongs principle'. However, the exact mechanisms for how information is transferred and used within the group in order to improve both individual- and group-level navigational performance are not fully understood. Here we explore the relative weighting that should be given to different sources of navigational information by an individual within a navigating group at each step of the movement process. Specifically, we consider a direct goal-oriented source of navigational information such as the individual׳s own imperfect knowledge of the target (a 'noisy compass') alongside two indirect sources of navigational information: the previous movement directions of neighbours in the group (social information) and, for the first time in this context, the previous movement direction of the individual (persistence). We assume that all individuals are equal in their abilities and that direct navigational information is prone to higher errors than indirect information. Using computer simulations, we show that in such situations giving a high weighting to either type of indirect navigational information can serve to significantly improve the navigation success of groups. Crucially, we also show that if the quality of social information is reduced, e.g. by an individual׳s limited cognitive abilities, the best navigational strategy for groups assigns a considerable weighting to persistence, a behaviour that is neither social, nor directly aimed at navigating.

Effect of grazing-mediated dimethyl sulfide (DMS) production on the swimming behavior of the copepod Calanus helgolandicus.

Chemical interactions play a fundamental role in the ecology of marine foodwebs. Dimethyl sulfide (DMS) is a ubiquitous marine trace gas that acts as a bioactive compound by eliciting foraging behavior in a range of marine taxa including the copepod Temora longicornis. Production of DMS can rapidly increase following microzooplankton grazing on phytoplankton. Here, we investigated whether grazing-induced DMS elicits an increase in foraging behavior in the copepod Calanus helgolandicus. We developed a semi-automated method to quantify the effect of grazing-mediated DMS on the proportion of the time budget tethered females allocate towards slow swimming, typically associated with feeding. The pooled data showed no differences in the proportion of the 25 min time budget allocated towards slow swimming between high (23.6 ± 9.74%) and low (29.1 ± 18.33%) DMS treatments. However, there was a high degree of variability between behavioral responses of individual copepods. We discuss the need for more detailed species-specific studies of individual level responses of copepods to chemical signals at different spatial scales to improve our understanding of chemical interactions between copepods and their prey.

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.

The principles of pedestrian route choice.

Pedestrian route choice, the process by which individuals decide on their walking path between two locations, is a fundamental problem across disciplines. Because this behaviour is investigated from different conceptual and methodological angles, and because it strongly depends on the environmental context, it is challenging to establish a systematic framework for research. Here, by reviewing previous work, we identify four principles for pedestrian route choice that are relevant across disciplines. First, 'information perception' deals with how pedestrians can perceive information selectively and purposely, given the limited available information. Second, 'information integration' considers how pedestrians subjectively integrate environmental spatial information into mental representations. Third, 'responding to information' is concerned with how pedestrians tend to be attracted and repelled by specific attributes individually and how this can lead to positive or negative feedback loops across many individuals. Fourth 'decision-making mechanisms' describe how pedestrians trade off the evidence provided by different attributes. How pedestrians perceive, integrate, respond to, and act upon information is not fixed but varies with the context. We give examples for each principle and explain how these principles shape pedestrian choice behaviours. We hope this contribution provides a systematic overview of the field and helps to spark inspiration among specialists.

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.

Making noise: emergent stochasticity in collective motion.

Individual-based models of self-propelled particles (SPPs) are a popular and promising approach to explain features of the collective motion of animal aggregations. Many models that capture some features of group motion have been suggested but a common framework has yet to emerge. Key to all of these models is the inclusion of "noise" or stochastic errors in the individual behaviour of the SPPs. Here, we present a fully stochastic SPP model in one dimension that demonstrates a new way of introducing noise into SPP models whilst preserving emergent behaviours of previous models such as coherent groups and spontaneous direction switching. This purely individual-to-individual, local model is related to previous models in the literature and can easily be extended to higher dimensions. Its coarse-grained behaviour qualitatively reproduces recently reported locust movement data. We suggest that our approach offers an alternative to current reasoning about model construction and has the potential to offer mechanistic explanations for emergent properties of animal groups in nature.

Emergent acoustic order in arrays of mosquitoes.

The yellow fever mosquito Aedes aegypti forms aerial swarms that serve as mating aggregations [1]. Despite lacking the remarkable collective order of other animal ensembles, such as fish and birds [2], the kinematic properties of these swarms bear the hallmarks of local interaction and global cohesion [3,4]. However, the mechanisms responsible for collective behaviour in mosquitoes are not well understood. Mosquitoes use their antennae as hearing organs to locate and interact with one another via the frequencies of sounds generated by their beating wings [5]. Acoustic detection and recognition are known to mediate copula formation in opposite-sex pairs [6], but have not been investigated in larger groups. By recording the flight tones of multiple, tethered, male Ae. aegypti, we test the hypothesis that acoustic signalling is a determinant of swarm morphology and present the first compelling evidence that flight tone interactions between males drive observed group coherence in the frequency domain. We find that group size critically affects collective and individual acoustic traits: cohesive acoustic behaviours emerge in groups of more than six male mosquitoes, occurring to a greater degree than predicted in the absence of interaction. Importantly, acoustic interactions between multiple males differ from those reported previously for same-sex pairs [7,8]. Our findings enable future research targeting key behavioural and reproductive aspects of the biology of mosquitoes of epidemiological importance.

Route choice in pedestrians: determinants for initial choices and revising decisions.

In moving pedestrian crowds, the distribution of individuals over different available routes emerges from the decisions of individuals that may be influenced by the actions of others. Understanding this phenomenon not only is important for research into collective behaviour, but also has practical applications for building safety and event management. Here, we study the mechanisms underlying pedestrian route choice, focusing on how time-independent information, such as path lengths, and time-dependent information, such as queue lengths, affect both initial decisions and subsequent changes in route choices. We address these questions using experiments with nearly 140 volunteers and an individual-based model for route choice. Crucially, we consider a wide range of route choice scenarios. We find that initial route choices of pedestrians achieve a balanced usage of available routes. Our model suggests that pedestrians performing trade-offs between exit widths and predicted exit crowdedness can explain this emergent distribution in many contexts. Few pedestrians adjust their route choice in our experiments. Simulations suggest that these decisions could be explained by pedestrians comparing estimates of the time it would take them to reach their target using different routes. Route choice is complex, but our findings suggest that conceptually simple behaviours may explain many movement decisions.

A method for detecting characteristic patterns in social interactions with an application to handover interactions.

Social interactions are a defining behavioural trait of social animals. Discovering characteristic patterns in the display of such behaviour is one of the fundamental endeavours in behavioural biology and psychology, as this promises to facilitate the general understanding, classification, prediction and even automation of social interactions. We present a novel approach to study characteristic patterns, including both sequential and synchronous actions in social interactions. The key concept in our analysis is to represent social interactions as sequences of behavioural states and to focus on changes in behavioural states shown by individuals rather than on the duration for which they are displayed. We extend techniques from data mining and bioinformatics to detect frequent patterns in these sequences and to assess how these patterns vary across individuals or changes in interaction tasks. To illustrate our approach and to demonstrate its potential, we apply it to novel data on a simple physical interaction, where one person hands a cup to another person. Our findings advance the understanding of handover interactions, a benchmark scenario for social interactions. More generally, we suggest that our approach permits a general perspective for studying social interactions.

How cognitive heuristics can explain social interactions in spatial movement.

The movement of pedestrian crowds is a paradigmatic example of collective motion. The precise nature of individual-level behaviours underlying crowd movements has been subject to a lively debate. Here, we propose that pedestrians follow simple heuristics rooted in cognitive psychology, such as 'stop if another step would lead to a collision' or 'follow the person in front'. In other words, our paradigm explicitly models individual-level behaviour as a series of discrete decisions. We show that our cognitive heuristics produce realistic emergent crowd phenomena, such as lane formation and queuing behaviour. Based on our results, we suggest that pedestrians follow different cognitive heuristics that are selected depending on the context. This differs from the widely used approach of capturing changes in behaviour via model parameters and leads to testable hypotheses on changes in crowd behaviour for different motivation levels. For example, we expect that rushed individuals more often evade to the side and thus display distinct emergent queue formations in front of a bottleneck. Our heuristics can be ranked according to the cognitive effort that is required to follow them. Therefore, our model establishes a direct link between behavioural responses and cognitive effort and thus facilitates a novel perspective on collective behaviour.

COLLECTIVE VORTEX BEHAVIORS: DIVERSITY, PROXIMATE, AND ULTIMATE CAUSES OF CIRCULAR ANIMAL GROUP MOVEMENTS.

Ant mill, caterpillar circle, bat doughnut, amphibian vortex, duck swirl, and fish torus are different names for rotating circular animal formations, where individuals turn around a common center. These "collective vortex behaviors" occur at different group sizes from pairs to several million individuals and have been reported in a large number of organisms, from bacteria to vertebrates, including humans. However, to date, no comprehensive review and synthesis of the literature on vortex behaviors has been conducted. Here, we review the state of the art of the proximate and ultimate causes of vortex behaviors. The ubiquity of this behavioral phenomenon could suggest common causes or fundamental underlying principles across contexts. However, we find that a variety of proximate mechanisms give rise to vortex behaviors. We highlight the potential benefits of collective vortex behaviors to individuals involved in them. For example, in some species, vortices increase feeding efficiency and could give protection against predators. It has also been argued that vortices could improve collective decision-making and information transfer. We highlight gaps in our understanding of these ubiquitous behavioral phenomena and discuss future directions for research in vortex studies.

Disentangling the impact of social groups on response times and movement dynamics in evacuations.

Crowd evacuations are paradigmatic examples for collective behaviour, as interactions between individuals lead to the overall movement dynamics. Approaches assuming that all individuals interact in the same way have significantly improved our understanding of pedestrian crowd evacuations. However, this scenario is unlikely, as many pedestrians move in social groups that are based on friendship or kinship. We test how the presence of social groups affects the egress time of individuals and crowds in a representative crowd evacuation experiment. Our results suggest that the presence of social groups increases egress times and that this is largely due to differences at two stages of evacuations. First, individuals in social groups take longer to show a movement response at the start of evacuations, and, second, they take longer to move into the vicinity of the exits once they have started to move towards them. Surprisingly, there are no discernible time differences between the movement of independent individuals and individuals in groups directly in front of the exits. We explain these results and discuss their implications. Our findings elucidate behavioural differences between independent individuals and social groups in evacuations. Such insights are crucial for the control of crowd evacuations and for planning mass events.

Information use by humans during dynamic route choice in virtual crowd evacuations.

We conducted a computer-based experiment with over 450 human participants and used a Bayesian model selection approach to explore dynamic exit route choice mechanisms of individuals in simulated crowd evacuations. In contrast to previous work, we explicitly explore the use of time-dependent and time-independent information in decision-making. Our findings suggest that participants tended to base their exit choices on time-dependent information, such as differences in queue lengths and queue speeds at exits rather than on time-independent information, such as differences in exit widths or exit route length. We found weak support for similar decision-making mechanisms under a stress-inducing experimental treatment. However, under this treatment participants were less able or willing to adjust their original exit choice in the course of the evacuation. Our experiment is not a direct test of behaviour in real evacuations, but it does highlight the role different types of information and stress play in real human decision-making in a virtual environment. Our findings may be useful in identifying topics for future study on real human crowd movements or for developing more realistic agent-based simulations.

Increased costs reduce reciprocal helping behaviour of humans in a virtual evacuation experiment.

Altruistic behaviour is widespread and highly developed in humans and can also be found in some animal species. It has been suggested that altruistic tendencies can depend on costs, benefits and context. Here, we investigate the changes in the occurrence of helping behaviour in a computer-based experiment that simulates an evacuation from a building exploring the effect of varying the cost to help. Our findings illuminate a number of key mechanistic aspects of human decision-making about whether to help or not. In a novel situation where it is difficult to assess the risks associated with higher costs, we reproduce the finding that increasing costs reduce helping and find that the reduction in the frequency of helping behaviour is gradual rather than a sudden transition for a threshold cost level. Interestingly, younger and male participants were more likely to help. We provide potential explanations for this result relating to the nature of our experiment. Finally, we find no evidence that participants in our experiment plan ahead over two consecutive, inter-dependent helping opportunities when conducting cost-benefit trade-offs in spontaneous decisions. We discuss potential applications of our findings to research into decision-making during evacuations.

Human responses to multiple sources of directional information in virtual crowd evacuations.

The evacuation of crowds from buildings or vehicles is one example that highlights the importance of understanding how individual-level interactions and decision-making combine and lead to the overall behaviour of crowds. In particular, to make evacuations safer, we need to understand how individuals make movement decisions in crowds. Here, we present an evacuation experiment with over 500 participants testing individual behaviour in an interactive virtual environment. Participants had to choose between different exit routes under the influence of three different types of directional information: static information (signs), dynamic information (movement of simulated crowd) and memorized information, as well as the combined effect of these different sources of directional information. In contrast to signs, crowd movement and memorized information did not have a significant effect on human exit route choice in isolation. However, when we combined the latter two treatments with additional directly conflicting sources of directional information, for example signs, they showed a clear effect by reducing the number of participants that followed the opposing directional information. This suggests that the signals participants observe more closely in isolation do not simply overrule alternative sources of directional information. Age and gender did not consistently explain differences in behaviour in our experiments.

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.

Visual sensory networks and effective information transfer in animal groups.

Social transmission of information is vital for many group-living animals, allowing coordination of motion and effective response to complex environments. Revealing the interaction networks underlying information flow within these groups is a central challenge. Previous work has modeled interactions between individuals based directly on their relative spatial positions: each individual is considered to interact with all neighbors within a fixed distance (metric range), a fixed number of nearest neighbors (topological range), a 'shell' of near neighbors (Voronoi range), or some combination (Figure 1A). However, conclusive evidence to support these assumptions is lacking. Here, we employ a novel approach that considers individual movement decisions to be based explicitly on the sensory information available to the organism. In other words, we consider that while spatial relations do inform interactions between individuals, they do so indirectly, through individuals' detection of sensory cues. We reconstruct computationally the visual field of each individual throughout experiments designed to investigate information propagation within fish schools (golden shiners, Notemigonus crysoleucas). Explicitly considering visual sensing allows us to more accurately predict the propagation of behavioral change in these groups during leadership events. Furthermore, we find that structural properties of visual interaction networks differ markedly from those of metric and topological counterparts, suggesting that previous assumptions may not appropriately reflect information flow in animal groups.

Limited interactions in flocks: relating model simulations to empirical data.

The mechanism of self-organization resulting in coordinated collective motion has received wide attention from a range of scientists interested in both its technical and biological relevance. Models have been highly influential in highlighting how collective motion can be produced from purely local interactions between individuals. Typical models in this field are termed 'metric' because each individual only reacts to conspecifics within a fixed distance. A recent large-scale study has, however, provided evidence that interactions ruling collective behaviour occur between a fixed number of nearest neighbours ('topological' framework). Despite their importance in clarifying the nature of the mechanism underlying animal interactions, these findings have yet to be produced by either metric or topological models. Here, we present an original individual-based model of collective animal motion that reproduces the previous findings. Our approach bridges the current gap between previous model analysis and recent evidence, and presents a framework for further study.