Statistical physics has proven to be a fruitful framework to describe phenomena outside the realm of traditional physics. Recent years have witnessed an attempt by physicists to study collective phenomena emerging from the interactions of individuals as elementary units in social structures. A wide list of topics are reviewed ranging from opinion and cultural and language dynamics to crowd behavior, hierarchy formation, human dynamics, and social spreading. The connections between these problems and other, more traditional, topics of statistical physics are highlighted. Comparison of model results with empirical data from social systems are also emphasized.

Statistical physics of social dynamics

▪ Abstract Dominance hierarchies exist in numerous social species, and rank in such hierarchies can dramatically influence the quality of an individual's life. Rank can dramatically influence also the health of an individual, particularly with respect to stress-related disease. This chapter reviews first the nature of stress, the stress-response and stress-related disease, as well as the varieties of hierarchical systems in animals. I then review the literature derived from nonhuman species concerning the connections between rank and functioning of the adrenocortical, cardiovascular, reproductive, and immune systems. As shown here, the relationship is anything but monolithic. Finally, I consider whether rank is a relevant concept in humans and argue that socioeconomic status (SES) is the nearest human approximation to social rank and that SES dramatically influences health.

/pdf/social-status-and-health-in-humans-and-other-animals-517dtpwf1w.pdf

Social Status and Health in Humans and Other Animals

Experience in aggressive contests often affects behaviour during, and the outcome of, later contests. This review discusses evidence for, variations in, and consequences of such effects. Generally, prior winning experiences increase, and prior losing experiences decrease, the probability of winning in later contests, reflecting modifications of expected fighting ability. We examine differences in the methodologies used to study experience effects, and the relative importance and persistence of winning and losing experiences within and across taxa. We review the voluminous, but somewhat disconnected, literature on the neuroendocrine mechanisms that mediate experience effects. Most studies focus on only one of a number of possible mechanisms without providing a comprehensive view of how these mechanisms are integrated into overt behaviour. More carefully controlled work on the mechanisms underlying experience effects is needed before firm conclusions can be drawn.

Behavioural changes during contests that relate to prior experience fall into two general categories. Losing experiences decrease willingness to engage in a contest while winning experiences increase willingness to escalate a contest. As expected from the sequential assessment model of contest behaviour, experiences become less important to outcomes of contests that escalate to physical fighting.

A limited number of studies indicate that integration of multiple experiences can influence current contest behaviour. Details of multiple experience integration for any species are virtually unknown. We propose a simple additive model for this integration of multiple experiences into an individual's expected fighting ability. The model accounts for different magnitudes of experience effects and the possible decline in experience effects over time.

Predicting contest outcomes based on prior experiences requires an algorithm that translates experience differences into contest outcomes. We propose two general types of model, one based solely on individual differences in integrated multiple experiences and the other based on the probability contests reach the escalated phase. The difference models include four algorithms reflecting possible decision rules that convert the perceived fighting abilities of two rivals into their probabilities of winning. The second type of algorithm focuses on how experience influences the probability that a subsequent contest will escalate and the fact that escalated contests may not be influenced by prior experience. Neither type of algorithm has been systematically investigated.

Finally, we review models for the formation of dominance hierarchies that assume that prior experience influences contest outcome. Numerous models have reached varied conclusions depending on which factors examined in this review are included. We know relatively little about the importance of and variation in experience effects in nature and how they influence the dynamics of aggressive interactions in social groups and random assemblages of individuals. Researchers should be very active in this area in the next decade. The role of experience must be integrated with other influences on contest outcome, such as prior residency, to arrive at a more complete picture of variations in contest outcomes. We expect that this integrated view will be important in understanding other types of interactions between individuals, such as mating and predator-prey interactions, that also are affected significantly by prior experiences.

Modulation of aggressive behaviour by fighting experience: mechanisms and contest outcomes.

Network analysis has emerged as a powerful way of studying phenomena as diverse as interpersonal interaction, connections among neurons, and the structure of the Internet. Appropriate use of network analysis depends, however, on choosing the right network representation for the problem at hand.

https://science.sciencemag.org/content/sci/325/5939/414.full.pdf

Revisiting the Foundations of Network Analysis

Fish are not famous for being smart, yet they can be added to the list of animals that show the rudiments of logical thinking. Transitive inference, the ability to deduce unknown relationships from knowledge of known relationships, is essential to logical reasoning. This ability is seen as an important step in a child's development, and similar capabilities are found in nonhuman primates, rats and birds. Astatotilapia burtoni, a territorial fish in which reproductive success of males depends on their status in 'fish society', can learn an implied hierarchy among other unfamiliar fish by watching fights between them. Remarkably, fish do this indirectly, as 'bystanders', with no direct reinforcement. This behaviour calls into question previous models of transitive inference and suggests that these fish have evolved distinct mechanisms for making inferences in situations specific to their survival and reproduction. The cover image shows an A. burtoni male. Transitive inference is demonstrated in fish populations by showing that they can learn the implied hierarchy among other unfamiliar fish by watching fights between rivals. Remarkably, fish can do this indirectly, as 'bystanders', without any reinforcement; they also make sophisticated use of contextual information available to them. Transitive inference (TI) involves using known relationships to deduce unknown ones (for example, using A > B and B > C to infer A > C), and is thus essential to logical reasoning. First described as a developmental milestone in children1, TI has since been reported in nonhuman primates2,3,4, rats5,6 and birds7,8,9,10. Still, how animals acquire and represent transitive relationships and why such abilities might have evolved remain open problems. Here we show that male fish (Astatotilapia burtoni) can successfully make inferences on a hierarchy implied by pairwise fights between rival males. These fish learned the implied hierarchy vicariously (as ‘bystanders’), by watching fights between rivals arranged around them in separate tank units. Our findings show that fish use TI when trained on socially relevant stimuli, and that they can make such inferences by using indirect information alone. Further, these bystanders seem to have both spatial and featural representations related to rival abilities, which they can use to make correct inferences depending on what kind of information is available to them. Beyond extending TI to fish and experimentally demonstrating indirect TI learning in animals, these results indicate that a universal mechanism underlying TI is unlikely. Rather, animals probably use multiple domain-specific representations adapted to different social and ecological pressures that they encounter during the course of their natural lives.

https://web.stanford.edu/group/fernaldlab/pubs/2007Grosenick.pdf

Fish can infer social rank by observation alone.

Linear hierarchies, the classical pecking-order structures, are formed readily in both nature and the laboratory in a great range of species including humans. However, the probability of getting linear structures by chance alone is quite low. In this paper we investigate the two hypotheses that are proposed most often to explain linear hierarchies: they are predetermined by differences in the attributes of animals, or they are produced by the dynamics of social interaction, i.e., they are self-organizing. We evaluate these hypotheses using cichlid fish as model animals, and although differences in attributes play a significant part, we find that social interaction is necessary for high proportions of groups with linear hierarchies. Our results suggest that dominance hierarchy formation is a much richer and more complex phenomenon than previously thought, and we explore the implications of these results for evolutionary biology, the social sciences, and the use of animal models in understanding human social organization.

https://www.pnas.org/content/pnas/99/8/5744.full.pdf

Michael Manfredonia

Papers

Individual differences versus social dynamics in the formation of animal dominance hierarchies