The initial fitness benefits of group living are considered to be the greatest hurdle to the evolution of sociality, and evolutionary theory predicts that these benefits need to arise at very small group sizes. Such benefits are thought to emerge partly from scaling effects that increase efficiency as group size increases. In social insects and other taxa, the benefits of group living have been proposed to stem from division of labour, which is characterized by between-individual variability and within-individual consistency (specialization) in task performance. However, at the onset of sociality groups were probably small and composed of similar individuals with potentially redundant-rather than complementary-function. Self-organization theory suggests that division of labour can emerge even in relatively small, simple groups. However, empirical data on the effects of group size on division of labour and on fitness remain equivocal. Here we use long-term automated behavioural tracking in clonal ant colonies, combined with mathematical modelling, to show that increases in the size of social groups can generate division of labour among extremely similar workers, in groups as small as six individuals. These early effects on behaviour were associated with large increases in homeostasis-the maintenance of stable conditions in the colony-and per capita fitness. Our model suggests that increases in homeostasis are primarily driven by increases in group size itself, and to a smaller extent by a higher division of labour. Our results indicate that division of labour, increased homeostasis and higher fitness can emerge naturally in social groups that are small and homogeneous, and that scaling effects associated with increasing group size can thus promote social cohesion at the incipient stages of group living.

The effects of heterogeneity in group composition remain a major hurdle to our understanding of collective behavior across disciplines. In social insects, division of labor (DOL) is an emergent, colony-level trait thought to depend on colony composition. Theoretically, behavioral response threshold models have most commonly been employed to investigate the impact of heterogeneity on DOL. However, empirical studies that systematically test their predictions are lacking because they require control over colony composition and the ability to monitor individual behavior in groups, both of which are challenging. Here, we employ automated behavioral tracking in 120 colonies of the clonal raider ant with unparalleled control over genetic, morphological, and demographic composition. We find that each of these sources of variation in colony composition generates a distinct pattern of behavioral organization, ranging from the amplification to the dampening of inherent behavioral differences in heterogeneous colonies. Furthermore, larvae modulate interactions between adults, exacerbating the apparent complexity. Models based on threshold variation alone only partially recapitulate these empirical patterns. However, by incorporating the potential for variability in task efficiency among adults and task demand among larvae, we account for all the observed phenomena. Our findings highlight the significance of previously overlooked parameters pertaining to both larvae and workers, allow the formulation of theoretical predictions for increasing colony complexity, and suggest new avenues of empirical study.

The precise mechanisms by which the information ecosystem polarizes society remain elusive. Focusing on political sorting in networks, we develop a computational model that examines how social network structure changes when individuals participate in information cascades, evaluate their behavior, and potentially rewire their connections to others as a result. Individuals follow proattitudinal information sources but are more likely to first hear and react to news shared by their social ties and only later evaluate these reactions by direct reference to the coverage of their preferred source. Reactions to news spread through the network via a complex contagion. Following a cascade, individuals who determine that their participation was driven by a subjectively “unimportant” story adjust their social ties to avoid being misled in the future. In our model, this dynamic leads social networks to politically sort when news outlets differentially report on the same topic, even when individuals do not know others’ political identities. Observational follow network data collected on Twitter support this prediction: We find that individuals in more polarized information ecosystems lose cross-ideology social ties at a rate that is higher than predicted by chance. Importantly, our model reveals that these emergent polarized networks are less efficient at diffusing information: Individuals avoid what they believe to be “unimportant” news at the expense of missing out on subjectively “important” news far more frequently. This suggests that “echo chambers”—to the extent that they exist—may not echo so much as silence.

Differences between sexes of the same species are widespread and are variable in nature. While it is often assumed that males are more ornamented than females, in the nymphalid butterfly genus Bicyclus, females have, on average, more eyespot wing color patterns than males. Here we extend these studies by surveying eyespot pattern sexual dimorphism across the Nymphalidae family of butterflies. Eyespot presence or absence was scored from a total of 38 wing compartments for two males and two females of each of 450 nymphalid species belonging to 399 different genera. Differences in eyespot number between sexes of each species were tallied for each wing surface (e.g., dorsal and ventral) of forewings and hindwings. In roughly 44% of the species with eyespots, females had more eyespots than males, in 34%, males had more eyespots than females, and, in the remaining 22% of the species, there was monomorphism in eyespot number. Dorsal and forewing surfaces were less patterned, but proportionally more dimorphic, than ventral and hindwing surfaces, respectively. In addition, wing compartments that frequently displayed eyespots were among the least sexually dimorphic. This survey suggests that dimorphism arises predominantly in “hidden” or “private” surfaces of a butterfly's wing, as previously demonstrated for the genus Bicyclus.

In social systems ranging from ant colonies to human society, behavioural specialization—consistent individual differences in behaviour—is commonplace: individuals can specialize in the tasks they perform (division of labour (DOL)), the political behaviour they exhibit (political polarization) or the non-task behaviours they exhibit (personalities). Across these contexts, behavioural specialization often co-occurs with modular and assortative social networks, such that individuals tend to associate with others that have the same behavioural specialization. This raises the question of whether a common mechanism could drive co-emergent behavioural specialization and social network structure across contexts. To investigate this question, here we extend a model of self-organized DOL to account for social influence and interaction bias among individuals—social dynamics that have been shown to drive political polarization. We find that these same social dynamics can also drive emergent DOL by forming a feedback loop that reinforces behavioural differences between individuals, a feedback loop that is impacted by group size. Moreover, this feedback loop also results in modular and assortative social network structure, whereby individuals associate strongly with those performing the same task. Our findings suggest that DOL and political polarization—two social phenomena not typically considered together—may actually share a common social mechanism. This mechanism may result in social organization in many contexts beyond task performance and political behaviour.

The composition of social groups has profound effects on their function, from collective decision-making to foraging efficiency. But few social systems afford sufficient control over group composition to precisely quantify its effects on individual and collective behavior. Here we combine experimental and theoretical approaches to study the effect of group composition on individual behavior and division of labor (DOL) in a social insect. Experimentally, we use automated behavioral tracking to monitor 120 colonies of the clonal raider ant, Ooceraea biroi, with controlled variation in three key correlates of social insect behavior: genotype, age, and morphology. We find that each of these sources of heterogeneity generates a distinct pattern of behavioral organization, including the amplification or dampening of inherent behavioral differences in colonies with mixed types. Theoretically, we use a well-studied model of DOL to explore potential mechanisms underlying the experimental findings. We find that the simplest implementation of this model, which assumes that heterogeneous individuals differ only in response thresholds, could only partially recapitulate the empirically observed patterns of behavior. However, the full spectrum of observed phenomena was recapitulated by extending the model to incorporate two factors that are biologically meaningful but theoretically rarely considered: variation among workers in task performance efficiency and among larvae in task demand. Our results thus show that different sources of heterogeneity within social groups can generate different, sometimes non-intuitive, behavioral effects, but that relatively simple models can capture these dynamics and thereby begin to elucidate the basic organizational principles of DOL in social insects.Significance StatementWhen individuals interact in an aggregate, many factors that are not known a priori affect group dynamics. A social group will therefore show emergent properties that cannot easily be predicted from how its members behave in isolation. This problem is exacerbated in mixed groups, where different individuals have different behavioral tendencies. Here we describe different facets of collective behavioral organization in mixed groups of the clonal raider ant, and show that a simple theoretical model can capture even non-intuitive aspects of the behavioral data. These results begin to reveal the principles underlying emergent behavioral organization in social insects. Importantly, our insights might apply to complex biological systems more generally and be used to help engineer collective behavior in artificial systems.

Environmental influences on immune phenotypes are well-documented, but our understanding of which elements of the environment affect immune systems, and how, remains vague. Behaviors, including socializing with others, are central to an individual's interaction with its environment. We tracked behavior of rewilded laboratory mice of three inbred strains in outdoor enclosures and examined contributions of behavior, including social associations, to immune phenotypes. We found that the more associated two individuals were, the more similar their immune phenotypes were. Social association was particularly predictive of similar memory T and B cell profiles and was more influential than sibling relationships or worm infection status. These results highlight the importance of social networks for immune phenotype and reveal important immunological correlates of social life.

The potential for groups to outperform the cognitive capabilities of even highly skilled individuals, known as the “wisdom of the crowd”, is crucial to the functioning of democratic institutions. In recent years, increasing polarization has led to concern about its effects on the accuracy of electorates, juries, courts, and congress. While there is empirical evidence of collective wisdom in partisan crowds, a general theory has remained elusive. Central to the challenge is the difficulty of disentangling the effect of limited interaction between opposing groups (homophily) from their tendency to hold opposing viewpoints (partisanship). To overcome this challenge, we develop an agent-based model of collective wisdom parameterized by the experimentally-measured behaviour of participants across the political spectrum. In doing so, we reveal that differences across the political spectrum in how individuals express and respond to knowledge interact with the structure of the network to either promote or undermine wisdom. We verify these findings experimentally and construct a more general theoretical framework. Finally, we provide evidence that incidental, context-specific differences across the political spectrum likely determine the impact of polarization. Overall, our results show that whether polarized groups benefit from collective wisdom is generally predictable but highly context-specific.