Darren P. Croft

Exploring Animal Social Networks

Preface vii Chapter 1: Introduction to Social Networks 1 Chapter 2: Data Collection 19 Chapter 3: Visual Exploration 42 Chapter 4: Node-Based Measures 64 Chapter 5: Statistical Tests of Node-Based Measures 88 Chapter 6: Searching for Substructures 117 Chapter 7: Comparing Networks 141 Chapter 8: Conclusions 163 Glossary of Frequently Used Terms 173 References 175 Index 187

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.

Social networks in the guppy (Poecilia reticulata)

Social network theory is used to elicit details of the social structure of a population of free–ranging guppies, Poecilia reticulata. They were found to have a complex and highly structured social network, which exhibited characteristics consistent with the ‘small world’ phenomenon. Stable partner associations between individuals were observed, a finding that fulfils the basic prerequisite for the evolution of reciprocal altruism. The findings are discussed in relation to the ecology and evolution of the wild population, highlighting the potential application of network theory to social associations in animals.

Assortative interactions and social networks in fish

The mechanisms underpinning the structure of social networks in multiple fish populations were investigated. To our knowledge this is the first study to provide replication of social networks and therefore probably the first that allows general conclusions to be drawn. The social networks were all found to have a non-random structure and exhibited ‘social cliquishness’. A number of factors were observed to contribute to this structuring. Firstly, social network structure was influenced by body length and shoaling tendency, with individuals interacting more frequently with conspecifics of similar body length and shoaling tendency. Secondly, individuals with many social contacts were found to interact with each other more often than with other conspecifics, a phenomenon known as a ‘positive degree correlation’. Finally, repeated interactions between pairs of individuals occurred within the networks more often than expected by random interactions. The observed network structures will have ecological and evolutionary implications. For example, the occurrence of positive degree correlations suggests the possibility that pathogens and information (that are socially transmitted) could spread very fast within the populations. Furthermore, the occurrence of repeated interactions between pairs of individuals fulfils an important pre-requisite for the evolution of reciprocal altruism.

Hypothesis testing in animal social networks

Behavioural ecologists are increasingly using social network analysis to describe the social organisation of animal populations and to test hypotheses. However, the statistical analysis of network data presents a number of challenges. In particular the non-independent nature of the data violates the assumptions of many common statistical approaches. In our opinion there is currently confusion and uncertainty amongst behavioural ecologists concerning the potential pitfalls when hypotheses testing using social network data. Here we review what we consider to be key considerations associated with the analysis of animal social networks and provide a practical guide to the use of null models based on randomisation to control for structure and non-independence in the data.

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.

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.

Personality in the context of social networks

There is great interest in environmental effects on the development and evolution of animal personality traits. An important component of an individuals environment is its social environment. However, few studies look beyond dyadic relationships and try to place the personality of individuals in the context of a social network. Social network analysis provides us with many new metrics to characterize the social fine-structure of populations and, therefore, with an opportunity to gain an understanding of the role that different personalities play in groups, communities and populations regarding information or disease transmission or in terms of cooperation and policing of social conflicts. The network position of an individual is largely a consequence of its interactive strategies. However, the network position can also shape an individuals experiences (especially in the case of juveniles) and therefore can influence the way in which it interacts with others in future. Finally, over evolutionary time, the social fine-structure of animal populations (as quantified by social network analysis) can have important consequences for the evolution of personalities—an approach that goes beyond the conventional game-theoretic analyses that assumed random mixing of individuals in populations.

Sex-biased movement in the guppy (Poecilia reticulata)

The movement strategies of birds and mammals are often closely linked to their mating system, but few studies have examined the relationship between mating systems and movement in fishes. We examined the movement patterns of the guppy (Poecilia reticulata) in the Arima river of Trinidad and predicted that sexual asymmetry in reproductive investment would result in male-biased movement. Since male guppies maximize their reproductive success by mating with as many different females as possible, there should be strong selection for males to move in search of mates. In agreement with our prediction, the percentage of fish that emigrated from release pools was higher for males than females (27.3% vs. 6.9%, respectively). Sex ratio was highly variable among pools and may influence a males decision to emigrate or continue moving. We also detected a positive relationship between body length and the probability of emigration for males and a significant bias for upstream movement by males. Among the few females that did emigrate, a positive correlation was observed between body length and distance moved. Sex-biased movement appears to be related to mating systems in fishes, but the evidence is very limited. Given the implications for ecology, evolution, and conservation, future studies should explicitly address the influence of sex and mating systems on movement patterns.

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.