Familiarity affects social network structure and discovery of prey patch locations in foraging stickleback shoals

Numerous factors affect the fine-scale social structure of animal groups, but it is unclear how important such factors are in determining how individuals encounter resources. Familiarity affects shoal choice and structure in many social fishes. Here, we show that familiarity between shoal members of sticklebacks (Gasterosteus aculeatus) affects both fine-scale social organization and the discovery of resources. Social network analysis revealed that sticklebacks remained closer to familiar than to unfamiliar individuals within the same shoal. Network-based diffusion analysis revealed that there was a strong untransmitted social effect on patch discovery, with individuals tending to discover a task sooner if a familiar individual from their group had previously done so than if an unfamiliar fish had done so. However, in contrast to the effect of familiarity, the frequency with which individuals had previously associated with one another had no effect upon the likelihood of prey patch discovery. This may have been due to the influence of fish on one another''s movements; the effect of familiarity on discovery of an empty ‘control’ patch was as strong as for discovery of an actual prey patch. Our results demonstrate that factors affecting fine-scale social interactions can also influence how individuals encounter and exploit resources.     

Aggression and social support predict long‐term cortisol levels in captive tufted capuchin monkeys (Cebus [Sapajus] apella)

Many nonhuman primates live in complex social groups in which they regularly encounter both social stressors such as aggression and social support such as that provided by long‐term affiliative relationships. Repeated exposure to social stressors may result in chronically elevated cortisol levels that can have deleterious physical effects such as impaired immune function, cardiovascular disease, and reduced brain function. In contrast, affiliative social relationships may act as a buffer, dampening the release of cortisol in response to acute and chronic stressors. Understanding how social stressors and social support predict cortisol levels is therefore essential to understanding how social situations relate to health and welfare. We studied this relationship in 16 socially housed captive brown capuchin monkeys (Cebus [Sapajus] apella) by comparing long‐term hair cortisol levels with behavioral measures of social stress (dominance rank, rank certainty, and amount of aggression received) and social support (amount of affiliation and centrality in the affiliative social network of the group). Dominance rank, rank certainty, amount of affiliation, and age were not significant predictors of long‐term cortisol levels in this population. Instead, long‐term cortisol levels were positively related to the amount of aggression received and negatively related to centrality in the affiliative social network of the group. This pattern may be attributed to the species’ socially tolerant dominance system and to the availability of social support across the dominance hierarchy.     

Social networks predict patch discovery in a wild population of songbirds

Animals use social information in a wide variety of contexts. Its extensive use by individuals to locate food patches has been documented in a number of species, and various mechanisms of discovery have been identified. However, less is known about whether individuals differ in their access to, and use of, social information to find food. We measured the social network of a wild population of three sympatric tit species (family Paridae) and then recorded individual discovery of novel food patches. By using recently developed methods for network-based diffusion analysis, we show that order of arrival at new food patches was predicted by social associations. Models based only on group searching did not explain this relationship. Furthermore, network position was correlated with likelihood of patch discovery, with central individuals more likely to locate and use novel foraging patches than those with limited social connections. These results demonstrate the utility of social network analysis as a method to investigate social information use, and suggest that the greater probability of receiving social information about new foraging patches confers a benefit on more socially connected individuals.     

Exploring the costs and benefits of social information use: an appraisal of current experimental evidence

Research on social learning has focused traditionally on whether animals possess the cognitive ability to learn novel motor patterns from tutors. More recently, social learning has included the use of others as sources of inadvertent social information. This type of social learning seems more taxonomically widespread and its use can more readily be approached as an economic decision. Social sampling information, however, can be tricky to use and calls for a more lucid appraisal of its costs. In this four-part review, we address these costs. Firstly, we address the possibility that only a fraction of group members are actually providing social information at any one time. Secondly, we review experimental research which shows that animals are circumspect about social information use. Thirdly, we consider the cases where social information can lead to incorrect decisions and finally, we review studies investigating the effect of social information quality. We address the possibility that using social information or not is not a binary decision and present results of a study showing that nutmeg mannikins combine both sources of information, a condition that can lead to the establishment of informational cascades. We discuss the importance of empirically investigating the economics of social information use.     

Bumble-bees learn the value of social cues through experience

Natural selection should lead animals to use social cues (SC) when they are useful, and disregard them when they are not. Theoretical investigation predicts that individuals should thus employ social learning ‘strategies’, but how might such context specificity be achieved on a proximate level? Operant conditioning, whereby the use of SC is reinforced through rewarding results, provides a potential mechanism. We investigate the role of reinforcement in joining behaviour in bumble-bees, Bombus terrestris. When bees visit unfamiliar flower species, they prefer to probe inflorescences where others are also foraging, and here we show that such behaviour is promoted through experience when conspecific presence reliably predicts reward. Our findings highlight a straightforward, but rarely discussed, mechanism by which animals can be selective about when to use SC.     

Social transmission of nectar-robbing behaviour in bumble-bees

Social transmission of acquired foraging techniques is rarely considered outside of a vertebrate context. Here, however, we show that nectar robbing by bumble-bees (Bombus terrestris)-an invertebrate behaviour of considerable ecological significance-has the potential to spread through a population at the accelerated rates typical of social transmission. Nectar robbing occurs when individuals either bite through the base of a flower to 'steal' nectar (primary robbing) or use robbing holes that others have made (secondary robbing). We found that experience of foraging from robbed flowers significantly promoted the development of primary robbing in previously legitimate foragers, thus implying that the acquisition of nectar robbing by one individual will facilitate its adoption in others. Our findings suggest that the positive feedback effects of social transmission may potentially play an ecologically important role in the relationship between plants and pollinators.     

When to use social information: the advantage of large group size in individual decision making

Correct decision making is crucial for animals to maximize foraging success and minimize predation risk. Group-living animals can make such decisions by using their own personal information or by pooling information with other group members (i.e. social information). Here, we investigate how individuals might best balance their use of personal and social information. We use a simple modelling approach in which individual decisions based upon social information are more likely to be correct when more individuals are involved and their personal information is more accurate. Our model predicts that when the personal information of group members is poor (accurate less than half the time), individuals should avoid pooling information. In contrast, when personal information is reliable (accurate at least half the time), individuals should use personal information less often and social information more often, and this effect should grow stronger in larger groups. One implication of this pattern is that social information allows less well-informed members of large groups to reach a correct decision with the same probability as more well-informed members of small groups. Thus, animals in larger groups may be able to minimize the costs of collecting personal information without impairing their ability to make correct decisions.     

Alarm communication networks as a driver of community structure in African savannah herbivores

Social information networks have the potential to shape the spatial structure of ecological communities by promoting the formation of mixed‐species groups. However, what actually drives social affinity between species in the wild will depend on the characteristics of the species available to group. Here we first present an agent‐based model that predicts trait‐related survival benefits from mixed‐species group formation in a multi‐species community and we then test the model predictions in a community‐wide field study of African savannah herbivores using multi‐layered network analysis. We reveal benefits from information transfer about predators as a key determinant of mixed‐species group formation, and that dilution benefits alone are not enough to explain patterns in interspecific sociality. The findings highlight the limitations of classical ecological approaches focusing only on direct trophic interactions when analysing community structure and suggest that declines in species occupying central social network positions, such as key informants, can have significant repercussions throughout communities.     

Hierarchical networks of food exchange in the black garden ant Lasius niger

In most eusocial insects, the division of labor results in relatively few individuals foraging for the entire colony. Thus, the survival of the colony depends on its efficiency in meeting the nutritional needs of all its members. Here, we characterize the network topology of a eusocial insect to understand the role and centrality of each caste in this network during the process of food dissemination. We constructed trophallaxis networks from 34 food-exchange experiments in black garden ants (Lasius niger). We tested the influence of brood and colony size on (i) global indices at the network level (i.e., efficiency, resilience, centralization, and modularity) and (ii) individual values (i.e., degree, strength, betweenness, and the clustering coefficient). Network resilience, the ratio between global efficiency and centralization, was stable with colony size but increased in the presence of broods, presumably in response to the nutritional needs of larvae. Individual metrics highlighted the major role of foragers in food dissemination. In addition, a hierarchical clustering analysis suggested that some domestics acted as intermediaries between foragers and other domestics. Networks appeared to be hierarchical rather than random or centralized exclusively around foragers. Finally, our results suggested that networks emerging from social insect interactions can improve group performance and thus colony fitness.     

Network analysis as a tool to understand social development in spider monkeys

The emerging field of network science has demonstrated that an individual's connectedness within their social network has cascading effects to other dimensions of life. Like humans, spider monkeys live in societies with high fission–fusion dynamics, and are remarkably social. Social network analysis (SNA) is a powerful tool for quantifying connections that may vary as a function of initiating or receiving social behaviors, which has been described as shifting social roles. In primatology, the SNA literature is dominated by work in catarrhines, and has yet to be applied to the study of development in a platyrrhine model. Here, SNA was utilized in combination with R-Index social role calculation to characterize social interaction patterns in juvenile and adult Colombian spider monkeys (Ateles fusciceps rufiventris). Connections were examined across five behaviors: embrace, face-embrace, grooming, agonism, and tail-wrapping from 186 hr of observation and four network metrics. Mann–Whitney U tests were utilized to determine differences between adult and juvenile social network patterns for each behavior. Face-embrace emerged as the behavior with different network patterns for adults and juveniles for every network metric. With regard to social role, juveniles were receivers, not initiators, for embrace, face-embrace, and grooming (ps < .05). Network and social role differences are discussed in light of social development and aspects of the different behaviors.     

Consistency of fish‐shoal social network structure under laboratory conditions

We investigated the consistency of association network structure for groups of sticklebacks Gasterosteus aculeatus. Each group was observed twice and we varied the duration between observations and the size of the experimental arena that they were observed in. At the dyad level, we found positive correlations between dyad interaction frequencies across observations. At the group level we found variation in four network metrics between observations, but only in treatments where the duration between observations was short. Specifically, fish formed more and smaller groups in the second observation in this treatment. Fish were also organized into more subunits in the larger arenas. Finally, we saw positive correlations between some group network metrics across observations suggesting relative consistency at the group level. There are several processes that might drive these interaction patterns. Our findings have implications for experimental design and the comparison and integration of findings of experiments from different studies carried out under different conditions.     

Social structure modulates the evolutionary consequences of social plasticity: A social network perspective on interacting phenotypes

Organisms express phenotypic plasticity during social interactions. Interacting phenotype theory has explored the consequences of social plasticity for evolution, but it is unclear how this theory applies to complex social structures. We adapt interacting phenotype models to general social structures to explore how the number of social connections between individuals and preference for phenotypically similar social partners affect phenotypic variation and evolution. We derive an analytical model that ignores phenotypic feedback and use simulations to test the predictions of this model. We find that adapting previous models to more general social structures does not alter their general conclusions but generates insights into the effect of social plasticity and social structure on the maintenance of phenotypic variation and evolution. Contribution of indirect genetic effects to phenotypic variance is highest when interactions occur at intermediate densities and decrease at higher densities, when individuals approach interacting with all group members, homogenizing the social environment across individuals. However, evolutionary response to selection tends to increase at greater network densities as the effects of an individual's genes are amplified through increasing effects on other group members. Preferential associations among similar individuals (homophily) increase both phenotypic variance within groups and evolutionary response to selection. Our results represent a first step in relating social network structure to the expression of social plasticity and evolutionary responses to selection.     

Sex‐specific responses to territorial intrusions in a communication network: Evidence from radio‐tagged great tits

Signals play a key role in the ecology and evolution of animal populations, influencing processes such as sexual selection and conflict resolution. In many species, sexually selected signals have a dual function: attracting mates and repelling rivals. Yet, to what extent males and females under natural conditions differentially respond to such signals remains poorly understood, due to a lack of field studies that simultaneously track both sexes. Using a novel spatial tracking system, we tested whether or not the spatial behavior of male and female great tits (Parus major) changes in relation to the vocal response of a territorial male neighbor to an intruder. We tracked the spatial behavior of male and female great tits (N = 44), 1 hr before and 1 hr after simulating territory intrusions, employing automatized Encounternet radio‐tracking technology. We recorded the spatial and vocal response of the challenged males and quantified attraction and repulsion of neighboring males and females to the intrusion site. We additionally quantified the direct proximity network of the challenged male. The strength of a male's vocal response to an intruder induced sex‐dependent movements in the neighborhood, via female attraction and male repulsion. Stronger vocal responders were older and in better body condition. The proximity networks of the male vocal responders, including the number of sex‐dependent connections and average time spent with connections, however, did not change directly following the intrusion. The effects on neighbor movements suggest that the strength of a male's vocal response can provide relevant social information to both the males and the females in the neighborhood, resulting in both sexes adjusting their spatial behavior in contrasting ways, while the social proximity network remained stable. This study underlines the importance of “silent” eavesdroppers within communication networks for studying the dual functioning and evolution of sexually selected signals.     

Interspecific social networks promote information transmission in wild songbirds

Understanding the functional links between social structure and population processes is a central aim of evolutionary ecology. Multiple types of interactions can be represented by networks drawn for the same population, such as kinship, dominance or affiliative networks, but the relative importance of alternative networks in modulating population processes may not be clear. We illustrate this problem, and a solution, by developing a framework for testing the importance of different types of association in facilitating the transmission of information. We apply this framework to experimental data from wild songbirds that form mixed-species flocks, recording the arrival (patch discovery) of individuals to novel foraging sites. We tested whether intraspecific and interspecific social networks predicted the spread of information about novel food sites, and found that both contributed to transmission. The likelihood of acquiring information per unit of connection to knowledgeable individuals increased 22-fold for conspecifics, and 12-fold for heterospecifics. We also found that species varied in how much information they produced, suggesting that some species play a keystone role in winter foraging flocks. More generally, these analyses demonstrate that this method provides a powerful approach, using social networks to quantify the relative transmission rates across different social relationships.     

Processing power limits social group size: computational evidence for the cognitive costs of sociality

Sociality is primarily a coordination problem. However, the social (or communication) complexity hypothesis suggests that the kinds of information that can be acquired and processed may limit the size and/or complexity of social groups that a species can maintain. We use an agent-based model to test the hypothesis that the complexity of information processed influences the computational demands involved. We show that successive increases in the kinds of information processed allow organisms to break through the glass ceilings that otherwise limit the size of social groups: larger groups can only be achieved at the cost of more sophisticated kinds of information processing that are disadvantageous when optimal group size is small. These results simultaneously support both the social brain and the social complexity hypotheses.