Structure and resilience of the social network in an insect colony as a function of colony size

Social interactions are critical to the organization of worker activities in insect colonies and their consequent ecological success. The structure of this interaction network is therefore crucial to our understanding of colony organization and functioning. In this paper, I study the properties of the interaction network in the colonies of the social wasp Ropalidia marginata. I find that the network is characterized by a uniform connectivity among individuals with increasing heterogeneity as colonies become larger. Important network parameters are found to be correlated with colony size and I investigate how this is reflected in the organization of work in colonies of different sizes. Finally, I test the resilience of these interaction networks by experimental removal of individuals from the colony and discuss the structural properties of the network that are related to resilience in a social network. This contribution is part of the special issue “Social Networks: new perspectives” (Guest Editors: J. Krause, D. Lusseau, and R. James).     

Social network theory in the behavioural sciences: potential applications

Social network theory has made major contributions to our understanding of human social organisation but has found relatively little application in the field of animal behaviour. In this review, we identify several broad research areas where the networks approach could greatly enhance our understanding of social patterns and processes in animals. The network theory provides a quantitative framework that can be used to characterise social structure both at the level of the individual and the population. These novel quantitative variables may provide a new tool in addressing key questions in behavioural ecology particularly in relation to the evolution of social organisation and the impact of social structure on evolutionary processes. For example, network measures could be used to compare social networks of different species or populations making full use of the comparative approach. However, the networks approach can in principle go beyond identifying structural patterns and also can help with the understanding of processes within animal populations such as disease transmission and information transfer. Finally, understanding the pattern of interactions in the network (i.e. who is connected to whom) can also shed some light on the evolution of behavioural strategies.     

Olfactory discrimination of age-specific hydrocarbons generates behavioral segregation in a honeybee colony

The functioning of a honeybee colony relies on the coordination of colony activities via inter-individual interactions. While the structure of this interaction network keeps the young individuals relatively isolated from the rest of the colony, there are two possible mechanisms that can generate this organizational immunity. A spatial segregation that restricts the young bees to the center of the colony can shield them with equal effectiveness as a behavioral segregation in which old bees choose to interact with young bees less frequently. We test the role of these two mechanisms by determining the interaction frequency between different age groups and testing their correlation with the olfactory sensitivity of different age groups to the cuticular odor of each other. Young bees were found to interact with bees of all age groups with equal frequency, which correlates with their lack of olfactory bias for any specific age, while old bees interacted more with other old bees, which correlates with their higher olfactory sensitivity toward the cuticular odor of old bees. The distribution of olfactory responsiveness was found to be positively skewed for old bees, which provides a mechanistic basis for the heterogeneous connectivity of the interaction network observed in an earlier study. As old bees are more likely to be responsible for introducing a potential disease into the colony from the outside and spreading it via the interaction network, these results suggest that behavioral segregation, mediated by olfactory discrimination, plays an important role in generating the organizational immunity within the honeybee colony.     

Social network theory: new insights and issues for behavioral ecologists

Until recently, few studies have used social network theory (SNT) and metrics to examine how social network structure (SNS) might influence social behavior and social dynamics in non-human animals. Here, we present an overview of why and how the social network approach might be useful for behavioral ecology. We first note four important aspects of SNS that are commonly observed, but relatively rarely quantified: (1) that within a social group, differences among individuals in their social experiences and connections affect individual and group outcomes; (2) that indirect connections can be important (e.g., partners of your partners matter); (3) that individuals differ in their importance in the social network (some can be considered keystone individuals); and (4) that social network traits often carry over across contexts (e.g., SN position in male–male competition can influence later male mating success). We then discuss how these four points, and the social network approach in general, can yield new insights and questions for a broad range of issues in behavioral ecology including: mate choice, alternative mating tactics, male–male competition, cooperation, reciprocal altruism, eavesdropping, kin selection, dominance hierarchies, social learning, information flow, social foraging, and cooperative antipredator behavior. Finally, we suggest future directions including: (1) integrating behavioral syndromes and SNT; (2) comparing space use and SNS; (3) adaptive partner choice and SNS; (4) the dynamics and stability (or instability) of social networks, and (5) group selection shaping SNS. This contribution is part of the special issue “Social networks: new perspectives” (Guest Editors: J. Krause, D. Lusseau and R. James).     

A Voronoi diagram based population model for social species of wildlife

A population model is presented that accounts for spatial structure within habitat patches. It is designed for social species of wildlife that form social group home ranges that are much smaller than patch size. The model represents social group home ranges by Voronoi regions that tessellate a patch to form a Voronoi diagram. Neighbouring social groups are linked with habitat-confined shortest paths and form a dispersal network. The model simulates population dynamics and makes use of Voronoi diagrams and dispersal networks as a spatial component. It then produces density maps as outputs. These are maps that show predicted animal densities across the patches of a landscape. A construction procedure for the particular Voronoi diagram type used by the model is described. As a test case, the model is run for the squirrel glider (Petaurus norfolcensis), a small arboreal marsupial native to Australia. A time series of density maps are produced that show squirrel glider density changing across a landscape through time.     

The social network structure of a wild meerkat population: 1. Inter-group interactions

Groups of individuals frequently interact with each other, but typically analysis of such interactions is restricted to isolated dyads. Social network analysis (SNA) provides a method of analysing polyadic interactions and is used to analyse interactions between individuals. We use a population of 12 groups (ca. 250 animals) of wild meerkats (Suricata suricatta) to test whether SNA can also be used to describe and elucidate patterns of inter-group interactions. Using data collected over 24 months, we constructed two sets of networks, based on direct encounters between groups and instances of roving males visiting other groups. We analysed replicated networks of each type of interaction to investigate similarities between networks of different social interactions as well as testing their stability over time. The two network types were similar to each other when derived from long-term data, but showed significant differences in structure over shorter timescales where they varied according to seasonal and ecological conditions. Networks for both types of inter-group interaction constructed from data collected over 3 months reliably described long-term (12- and 24-month) patterns of interactions between groups, indicating a stable social structure despite variation in group sizes and sex ratios over time. The centrality of each meerkat group in roving interactions networks was unaffected by the sex ratio of its members, indicating that male meerkats preferentially visit geographically close groups rather than those containing most females. Indeed, the strongest predictors of network structure were spatial factors, suggesting that, in contrast to analyses of intra-group interactions, analyses of inter-group interactions using SNA must take spatial factors into account.     

Network structure and parasite transmission in a group living lizard,the gidgee skink, <Emphasis Type="Italic">Egernia stokesii</Emphasis>

Gidgee skinks (Egernia stokesii) form large social aggregations in rocky outcrops across the Flinders Ranges in South Australia. Group members share refuges (rock crevices), which may promote parasite transmission. We measured connectivity of individuals in networks constructed from patterns of common crevice use and observed patterns of parasitism by three blood parasites (Hemolivia, Schellackia and Plasmodium) and an ectoparasitic tick (Amblyomma vikirri). Data came from a 1-year mark-recapture study of four populations. Transmission networks were constructed to represent possible transmission pathways among lizards. Two lizards that used the same refuge within an estimated transmission period were considered connected in the transmission network. An edge was placed between them, directed towards the individual that occupied the crevice last. Social networks, a sub-set of same-day only associations, were small and highly fragmented compared with transmission networks, suggesting that non-synchronous crevice use leads to more transmission opportunities than direct social association. In transmission networks, lizards infested by ticks were connected to more other tick-infested lizards than uninfected lizards. Lizards infected by ticks and carrying multiple blood parasite infections were in more connected positions in the network than lizards without ticks or with one or no blood parasites. Our findings suggest higher levels of network connectivity may increase the risk of becoming infected or that parasites influence lizard behaviour and consequently their position in the network. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users. This contribution is part of the special issue “Social Networks: new perspectives” (Guest Editors: J. Krause, D. Lusseau and R. James).     

Young-boy networks without kin clusters in a lek-mating manakin

I use 10 years of data from a long-term study of lek-mating long-tailed manakins to relate the social network among males to their spatial and genetic structure. Previously, I showed that the network connectivity of young males predicts their future success. Here, I ask whether kinship might shape the organization of this “young-boy network”. Not surprisingly, males that were more socially distant (linked by longer network paths) were affiliated with perch zones (lek arenas) that were further apart. Relatedness (r) among males within the network decreased as social distance increased, as might be expected under kin selection. Nevertheless, any role for indirect inclusive fitness benefits is refuted by the slightly negative mean relatedness among males at all social distances within the network (overall mean r = −0.06). That is, relatedness ranged from slightly negative (−0.04) to more negative (−0.2). In contrast, relatedness in dyads for which at least one of the males was outside the social network (involving at least one blood-sampled male not documented to have interacted with other banded males) was slightly above the random expectation (mean r = 0.05). The slight variations around r = 0 among males of different categories likely reflect dispersal dynamics, rather than any influence of kinship on social organization. Relatedness did not covary with the age difference between males. These results, together with previous results for lack of relatedness between alpha and beta male partners, refute any role for kin selection in the evolution of cooperative display in this lek-mating system. This contribution is part of the special issue “Social Networks: new perspectives” (Guest Editors: J. Krause, D. Lusseau, and R. James).     

Is the bee louse Braula coeca (Diptera) using chemical camouflage to survive within honeybee colonies?

The bee louse Braula coeca is a highly specialised flattened, wingless fly that spends its entire adult life on adult honeybees. It feeds by stealing food directly from bees during social feeding (trophallaxis). The Braula fly has a preference to infest the honeybee queen. The queen is the most attended individual in the colony but despite this the adult flies remain undetected by the workers. This is due to Braula possessing a cuticular hydrocarbon profile that mirrors that of their host honeybee colony, despite Diptera and Hymenoptera orders having separated over 290 million years ago. This chemical camouflage is most likely through odour acquisition from the honeybee host since even small colony-specific differences in the alkene isomer patterns present in the honeybees were also detected in the Braula’s profile. This finding further supports the idea that the honeybee recognition cues are contained within the alkene part of their hydrocarbon profile and Braula exploit this to remain undetected within an otherwise hostile colony.     

Animal social networks: an introduction

Network analysis has a long history in the mathematical and social sciences and the aim of this introduction is to provide a brief overview of the potential that it holds for the study of animal behaviour. One of the most attractive features of the network paradigm is that it provides a single conceptual framework with which we can study the social organisation of animals at all levels (individual, dyad, group, population) and for all types of interaction (aggressive, cooperative, sexual etc.). Graphical tools allow a visual inspection of networks which often helps inspire ideas for testable hypotheses. Network analysis itself provides a multitude of novel statistical tools that can be used to characterise social patterns in animal populations. Among the important insights that networks have facilitated is that indirect social connections matter. Interactions between individuals generate a social environment at the population level which in turn selects for behavioural strategies at the individual level. A social network is often a perfect means by which to represent heterogeneous relationships in a population. Probing the biological drivers for these heterogeneities, often as a function of time, forms the basis of many of the current uses of network analysis in the behavioural sciences. This special issue on social networks brings together a diverse group of practitioners whose study systems range from social insects over reptiles to birds, cetaceans, ungulates and primates in order to illustrate the wide-ranging applications of network analysis. This contribution is part of the special issue “Social Networks: new perspectives” (Guest Editors: J. Krause, D. Lusseau and R. James).     

Network structure and prevalence of Cryptosporidium in Belding’s ground squirrels

Although pathogen transmission dynamics are profoundly affected by population social and spatial structure, few studies have empirically demonstrated the population-level implications of such structure in wildlife. In particular, epidemiological models predict that the extent to which contact patterns are clustered decreases a pathogen’s ability to spread throughout an entire population, but this effect has yet to be demonstrated in a natural population. Here, we use network analysis to examine patterns of transmission of an environmentally transmitted parasite, Cryptosporidium spp., in Belding’s ground squirrels (Spermophilus beldingi). We found that the prevalence of Cryptosporidium was negatively correlated with transitivity, a measure of network clustering, and positively correlated with the percentage of juvenile males. Additionally, network transitivity decreased when there were higher percentages of juvenile males; the exploratory behavior demonstrated by juvenile males may have altered the structure of the network by reducing clustering, and low clustering was associated with high prevalence. We suggest that juvenile males are critical in mediating the ability of Cryptosporidium to spread through colonies, and thus may function as “super-spreaders.” Our results demonstrate the utility of a network approach in quantifying mechanistically how differences in contact patterns may lead to system-level differences in infection patterns.     

Aging and demographic plasticity in response to experimental age structures in honeybees (<Emphasis Type="Italic">Apis mellifera</Emphasis> L)

Honeybee colonies are highly integrated functional units characterized by a pronounced division of labor. Division of labor among workers is mainly age-based, with younger individuals focusing on in-hive tasks and older workers performing the more hazardous foraging activities. Thus, experimental disruption of the age composition of the worker hive population is expected to have profound consequences for colony function. Adaptive demography theory predicts that the natural hive age composition represents a colony-level adaptation and thus results in optimal hive performance. Alternatively, the hive age composition may be an epiphenomenon, resulting from individual life history optimization. We addressed these predictions by comparing individual worker longevity and brood production in hives that were composed of a single-age cohort, two distinct age cohorts, and hives that had a continuous, natural age distribution. Four experimental replicates showed that colonies with a natural age composition did not consistently have a higher life expectancy and/or brood production than the single-cohort or double-cohort hives. Instead, a complex interplay of age structure, environmental conditions, colony size, brood production, and individual mortality emerged. A general tradeoff between worker life expectancy and colony productivity was apparent, and the transition from in-hive tasks to foraging was the most significant predictor of worker lifespan irrespective of the colony age structure. We conclude that the natural age structure of honeybee hives is not a colony-level adaptation. Furthermore, our results show that honeybees exhibit pronounced demographic plasticity in addition to behavioral plasticity to react to demographic disturbances of their societies.     

An oligarchy of nest-site scouts triggers a honeybee swarm’s departure from the hive

Animals that travel in groups must synchronize the timing of their departures to assure cohesion of the group. While most activities in large colonies of social insects have decentralized control, certain activities (e.g., colony migration) can have centralized control, with only a special subset of well-informed individuals making a decision that affects the entire colony. We recently discovered that a small minority of individuals in a honeybee colony—an oligarchy—decides when to trigger the departure of a swarm from its hive. The departure process begins with some bees producing the worker-piping signal (the primer for departure) and is followed by these bees producing the buzz-run signal (the releaser for departure). In this study, we determined the identity of these signalers. We found that a swarm’s nest-site scouts search for potential nest cavities prior to the departure of the swarm from its hive. Furthermore, we found that the predeparture nest-site scouts are the sole producers of the worker-piping signal and that they are the first producers of the buzz-run signal. The control of the departure of a honeybee swarm from its hive shows how a small minority of well-informed individuals in a large social insect colony can make important decisions about when a colony should take action.     

Association networks in spider monkeys (<Emphasis Type="Italic">Ateles geoffroyi</Emphasis>)

We use two novel techniques to analyze association patterns in a group of wild spider monkeys (Ateles geoffroyi) studied continuously for 8 years. Permutation tests identified association rates higher or lower than chance expectation, indicating active processes of companionship and avoidance as opposed to passive aggregation. Network graphs represented individual adults as nodes and their association rates as weighted edges. Strength and eigenvector centrality (a measure of how strongly linked an individual is to other strongly linked individuals) were used to quantify the particular role of individuals in determining the network's structure. Female–female dyads showed higher association rates than any other type of dyad, but permutation tests revealed that these associations cannot be distinguished from random aggregation. Females formed tightly linked clusters that were stable over time, with the exception of immigrant females who showed little association with any adult in the group. Eigenvector centrality was higher for females than for males. Adult males were associated mostly among them, and although their strength of association with others was lower than that of females, their association rates revealed a process of active companionship. Female–male bonds were weaker than those between same-sex pairs, with the exception of those involving young male adults, who by virtue of their strong connections both with female and male adults, appear as temporary brokers between the female and male clusters of the network. This analytical framework can serve to develop a more complete explanation of social structure in species with high levels of fission–fusion dynamics. This contribution is part of the special issue “Social Networks: new perspectives” (Guest Editors: J. Krause, D. Lusseau and R. James)     

Ovariole number—a predictor of differential reproductive success among worker subfamilies in queenless honeybee (Apis mellifera L.) colonies

A honeybee queen normally mates with 10–20 drones, and reproductive conflicts may arise among a colony’s different worker patrilines, especially after a colony has lost its single queen and the workers commence egg laying. In this study, we employed microsatellite markers to study aspects of worker reproductive competition in two queenless Africanized honeybee colonies. First, we determined whether there was a bias among worker patrilines in their maternity of drones and, second, we asked whether this bias could be attributed to differences in the degree of ovary activation of workers. Third, we relate these behavioral and physiological factors to ontogenetic differences between workers with respect to ovariole number. Workers from each of three (colony A) and one (colony B) patrilineal genotypes represented less than 6% of the worker population, yet each produced at least 13% of the drones in a colony, and collectively they produced 73% of the drones. Workers representing these genotypes also had more developed follicles and a greater number of ovarioles per ovary. Across all workers, ovariole development and number were closely correlated. This suggests a strong effect of worker genotype on the development of the ovary already in the postembryonic stages and sets a precedent to adult fertility, so that “workers are not born equal”. We hypothesize a frequency-dependent or “rare patriline” advantage to queenless workers over the parentage of males and discuss the maintenance of genetic variance in the reproductive capacity of workers.Electronic supplementary material Supplementary material is available for this article at and is accessible for authorized users.     

Social networks and non-market valuations

This paper considers the role of social networks in the non-market valuation of public goods. In the model individuals derive utility both from their own direct enjoyment of the public good and from the enjoyment of those in their network. We find that network structure almost always matters, both for utility and for valuation. The network increases aggregate valuation when it assigns higher importance, that is, stronger connections, to individuals with higher private values for the public good. The model provides a theoretical foundation for the idea of opinion leaders who have disproportionate influence over their communities. Specifically, opinion leaders are individuals assigned high importance by the network, and projects favored by opinion leaders tend to be favored by the network as a whole. The model can also guide future empirical studies by enabling a more structural approach to non-market valuation in a socially connected group.     

Social synchronization of the activity rhythms of honeybees within a colony

Colonies and isolated bees of the Cape honeybee, Apis mellifera capensis Esch., were observed for evidence of circadian rhythmicity under constant conditions. It was found that colonies develop free-running activity rhythms in self-selected light-dark cycles, which are slightly shorter than 24 h. The periods of the activity rhythms of individual isolated bees were longer than 24 h in self-selected light-dark and constant light, while they were shorter than 24 h in constant darkness. A greater variability in period was found in the isolated bees than in the colonies. When the rhythms of colonies and individual bees from these colonies were measured simultaneously, the activities of the isolated bees drifted with respect to that of the colonies, their period being either longer or shorter than that of their own colony. After 12 days of isolation of individual bees from their colony, all coincidence between the phases of the two rhythms was lost. We conclude that the periods of common activity and common rest of the bees within a colony result from a mutual (social) synchronization of the rhythms of the individual bees.     

Division of labor in a dynamic environment: response by honeybees (Apis mellifera) to graded changes in colony pollen stores

 A fundamental requirement of task regulation in social groups is that it must allow colony flexibility. We tested assumptions of three task regulation models for how honeybee colonies respond to graded changes in need for a specific task, pollen foraging. We gradually changed colony pollen stores and measured behavioral and genotypic changes in the foraging population. Colonies did not respond in a graded manner, but in six of seven cases showed a stepwise change in foraging activity as pollen storage levels moved beyond a set point. Changes in colony performance resulted from changes in recruitment of new foragers to pollen collection, rather than from changes in individual foraging effort. Where we were able to track genotypic variation, increases in pollen foraging were accompanied by a corresponding increase in the genotypic diversity of pollen foragers. Our data support previous findings that genotypic variation plays an important role in task regulation. However, the stepwise change in colony behavior suggests that colony foraging flexibility is best explained by an integrated model incorporating genotypic variation in task choice, but in which colony response is amplified by social interactions. Received: 17 October 1998 / Received in revised form: 11 March 1999 / Accepted: 12 March 1999     

Potential banana skins in animal social network analysis

Social network analysis is an increasingly popular tool for the study of the fine-scale and global social structure of animals. It has attracted particular attention by those attempting to unravel social structure in fission–fusion populations. It is clear that the social network approach offers some exciting opportunities for gaining new insights into social systems. However, some of the practices which are currently being used in the animal social networks literature are at worst questionable and at best over-enthusiastic. We highlight some of the areas of method, analysis and interpretation in which greater care may be needed in order to ensure that the biology we extract from our networks is robust. In particular, we suggest that more attention should be given to whether relational data are representative, the potential effect of observational errors and the choice and use of statistical tests. The importance of replication and manipulation must not be forgotten, and the interpretation of results requires care. This contribution is part of the special issue “Social Networks: new perspectives” (Guest Editors: J. Krause, D. Lusseau and R. James).