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.     

Network position: a key component in the characterization of social personality types

In recent years, animal social interactions have received much attention in terms of personality research (e.g. aggressive or cooperative interactions). However, other components of social behaviour such as those describing the intensity, frequency, directedness and individual repeatability of interactions in animal groups have largely been neglected. Network analysis offers a valuable opportunity to characterize individual consistency of traits in labile social groups and therein provide novel insights to personality research in ways previously not possible using traditional techniques. Should individual network positions be consistently different between individuals under changing conditions, they might reflect expressions of an individual's personality. Here, we discuss a conceptual framework for using network analyses to infer the presence of individual differences and present a statistical test based on randomization techniques for testing the consistency of network positions in individuals. The statistical tools presented are useful because if particular individuals consistently occupy key positions in social networks, then this is also likely to have consequences for their fitness as well as for that of others in the population. These consequences may be particularly significant since individual network position has been shown to be important for the transmission of diseases, socially learnt information and genetic material between individuals and populations.     

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).     

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 foundation for developing a methodology for social network sampling

Researchers are increasingly turning to network theory to understand the social nature of animal populations. We present a computational framework that is the first step in a series of works that will allow us to develop a quantitative methodology of social network sampling to aid ecologists in their social network data collection. To develop our methodology, we need to be able to generate networks from which to sample. Ideally, we need to perform a systematic study of sampling protocols on different known network structures, as network structure might affect the robustness of any particular sampling methodology. Thus, we present a computational tool for generating network structures that have user-defined distributions for network properties and for key measures of interest to ecologists. The user defines the values of these measures and the tool will generate appropriate network randomizations with those properties. This tool will be used as a framework for developing a sampling methodology, although we do not present a full methodology here. We describe the method used by the tool, demonstrate its effectiveness, and discuss how the tool can now be utilized. We provide a proof-of-concept example (using the assortativity measure) of how such networks can be used, along with a simulated egocentric sampling regime, to test the level of equivalence of the sampled network to the actual network. This contribution is part of the special issue “Social Networks: new perspectives” (Guest Editors: J. Krause, D. Lusseau and R. James).     

Social structure and co-operative interactions in a wild population of guppies (Poecilia reticulata)

In contrast to the substantial number of theoretical papers that have examined the mechanisms by which cooperation may evolve, very few studies have investigated patterns of co-operation in natural animal populations. In the current study, we use a novel approach, social network analysis, to investigate the structure of co-operative interactions in the context of predator inspection in a wild population of guppies (Poecilia reticulata). Female guppies showed social preferences for stable partners, fulfilling a key assumption made by models of reciprocity. In the laboratory, wild female guppies disproportionately engaged in predator inspection with others with whom they had strong social associations. Furthermore, pairs of fish that frequently engaged in predator inspection did so in a particularly co-operative way, potentially reducing costs associated with predator inspection. Taken together, these results provide evidence for assortative interactions forming the basis of co-operation during predator inspection in a natural fish population. The occurrence of highly interconnected social networks between stable partners suggests the existence of co-operation networks in free-ranging populations of the guppy.     

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).     

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).     

Sampling animal association networks with the gambit of the group

Ecologists increasingly use network theory to examine animal association patterns. The gambit of the group (GoG) is a simple and useful assumption for accumulating the data necessary for a network analysis. The gambit of the group implies that each animal in a group is associating with every other individual in that group. Sampling is an important issue for networks in wild populations collected assuming GoG. Due to time, effort, and resource constraints and the difficulty of tracking animals, sampled data are usually a subset of the actual network. Ecologists often use association indexes to calculate the frequency of associations between individuals. These indexes are often transformed by applying a filter to produce a binary network. We explore GoG sampling using model networks. We examine assortment at the level of the group by a single dichotomous trait, along with many other network measures, to examine the effect of different sampling regimes, and choice of filter on the accuracy and precision with which measures are estimated. We find strong support for the use of weighted, rather than filtered, network measures and show that different filters have different effects depending on the nature of the sampling. We make several practical recommendations for ecologists planning GoG sampling.     

Using home range estimates to construct social networks for species with indirect behavioral interactions

Social network analysis has become a vital tool for studying patterns of individual interactions that influence a variety of processes in behavior, ecology, and evolution. Taxa in which interactions are indirect or whose social behaviors are difficult to observe directly are being excluded from this rapidly expanding field. Here, we introduce a method that uses a probabilistic and spatially implicit technique for delineating social interactions. Kernel density estimators (KDE) are nonparametric techniques that are often used in home range analyses and allow researchers studying social networks to generate interaction matrices based on shared space use. We explored the use of KDE analysis and the effects of altering KDE input parameters on social network metrics using data from a natural population of the spatially persistent forked fungus beetle, Bolitotherus cornutus.     

The social network structure of a wild meerkat population: 2. Intragroup interactions

Knowledge of the structure of networks of social interactions is important for understanding the evolution of cooperation, transmission of disease, and patterns of social learning, yet little is known of how environmental, ecological, or behavioural factors relate to such structures within groups. We observed grooming, dominance, and foraging competition interactions in eight groups of wild meerkats (Suricata suricatta) and constructed interaction networks for each behaviour. We investigated relationships between networks for different social interactions and explored how group attributes (size and sex ratio), individual attributes (tenure of dominants), and ecological factors (ectoparasite load) are related to variation in network structure. Network structures varied within a group according to interaction type. Further, network structure varied predictably with group attributes, individual attributes, and ecological factors. Networks became less dense as group size increased suggesting that individuals were limited in their number of partners. Groups with more established dominant females were more egalitarian in their grooming and foraging competition interactions, but more despotic in their dominance interactions. The distribution of individuals receiving grooming became more skewed at higher parasite loads, but more equitable at low parasite loads. We conclude that the pattern of interactions between members of meerkat groups is not consistent between groups but instead depends on general attributes of the group, the influence of specific individuals within the group, and ecological factors acting on group members. We suggest that the variation observed in interaction patterns between members of meerkat groups may have fitness consequences both for individual group members and the group itself.     

Cyclicity in the structure of female baboon social networks

There is an established and very influential view that primate societies have identifiable, persistent social organizations. It assumes that association patterns reflect long-term strategic interests that are not qualitatively perturbed by short-term environmental variability. We used data from two baboon troops in markedly different habitats over three consecutive seasons to test this assumption. Our results demonstrate pronounced cyclicity in the extent to which females maintained differentiated relationships. When food was plentiful, the companionships identified by social network analysis in the food-scarce season disappeared and were replaced by casual acquaintanceships more representative of mere gregariousness. Data from the fourth, food-scarce, season at one site indicated that few companions were re-united. It is likely that this reflected stochastic variation in individual circumstances. These results suggest that attention could profitably be paid to the effects of short-term local contingencies on social dynamics, and has implications for current theories of primate cognitive evolution. 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.     

Shark personalities? Repeatability of social network traits in a widely distributed predatory fish

Interest in animal personalities has generated a burgeoning literature on repeatability in individual traits such as boldness or exploration through time or across different contexts. Yet, repeatability can be influenced by the interactive social strategies of individuals, for example, consistent inter-individual variation in aggression is well documented. Previous work has largely focused on the social aspects of repeatability in animal behaviour by testing individuals in dyadic pairings. Under natural conditions, individuals interact in a heterogeneous polyadic network. However, the extent to which there is repeatability of social traits at this higher order network level remains unknown. Here, we provide the first empirical evidence of consistent and repeatable animal social networks. Using a model species of shark, a taxonomic group in which repeatability in behaviour has yet to be described, we repeatedly quantified the social networks of ten independent shark groups across different habitats, testing repeatability in individual network position under changing environments. To understand better the mechanisms behind repeatable social behaviour, we also explored the coupling between individual preferences for specific group sizes and social network position. We quantify repeatability in sharks by demonstrating that despite changes in aggregation measured at the group level, the social network position of individuals is consistent across treatments. Group size preferences were found to influence the social network position of individuals in small groups but less so for larger groups suggesting network structure, and thus, repeatability was driven by social preference over aggregation tendency.     

Behavioural trait assortment in a social network: patterns and implications

The social fine structure of a population plays a central role in ecological and evolutionary processes. Whilst many studies have investigated how morphological traits such as size affect social structure of populations, comparatively little is known about the influence of behaviours such as boldness and shyness. Using information on social interactions in a wild population of Trinidadian guppies (Poecilia reticulata), we construct a social network. For each individual in the network, we quantify its behavioural phenotype using two measures of boldness, predator inspection tendency, a repeatable and reliably measured behaviour well studied in the context of co-operation, and shoaling tendency. We observe striking heterogeneity in contact patterns, with strong ties being positively assorted and weak ties negatively assorted by our measured behavioural traits. Moreover, shy fish had more network connections than bold fish and these were on average stronger. In other words, social fine structure is strongly influenced by behavioural trait. We assert that such structure will have implications for the outcome of selection on behavioural traits and we speculate that the observed positive assortment may act as an amplifier of selection contributing to the maintenance of co-operation during predator inspection.     

Social network properties within a fish assemblage invaded by non-native sunbleak Leucaspius delineatus

Network theory is commonly used to reveal social interactions and the organisation of interconnected nodes—but has not yet been applied to animal invasions. Non-native species invasions are now considered one of the foremost threats to natural ecosystems and biodiversity. This is the first attempt to assess social network properties within a freshwater fish assemblage invaded by a non-native fish species. We show that invasive sunbleak Leucaspius delineatus is socially more strongly interconnected with native species than the native species with each other. The social networks also reveal characteristics of a ‘small world’ such as low clustering coefficients C and short path lengths L. The findings may indicate potential traits of successful invaders and the implication for the spread of pathogens between individuals within a group of animals that contain a non-native invasive species. The success of establishment and subsequent invasion may be highlighted not only by the capacity of the new species to adapt to the new environment, but also in its capacity to penetrate the social circle of the native community.     

Social attributes and associated performance measures in marmots: bigger male bullies and weakly affiliating females have higher annual reproductive success

Studying the structure of social interactions is fundamental in behavioral ecology as social behavior often influences fitness and thus natural selection. However, social structure is often complex, and determining the most appropriate measures of variation in social behavior among individuals can be difficult. Social network analysis generates numerous, but often correlated, measures of individual connectedness derived from a network of interactions. We used measures of individual connectedness in networks of affiliative and agonistic interactions in yellow-bellied marmots, Marmota flaviventris, to first determine how variance was structured among network measures. Principal component analysis reduced our set of network measures to four “social attributes” (unweighted connectedness, affiliation strength, victimization, and bullying), which revealed differences between patterns of affiliative and agonistic interactions. We then used these extracted social attributes to examine the relationship between an individual’s social attributes and several performance measures: annual reproductive success, parasite infection, and basal stress. In male marmots, bullying was positively associated with annual reproductive success, while in females, affiliation strength was negatively associated with annual reproductive success. No other social attributes were significantly associated with any performance measures. Our study highlights the utility of considering multiple dimensions when measuring the structure and functional consequences of social behavior.     

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)     

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.