Collective decision‐making and fission–fusion dynamics: a conceptual framework

Sociality exists in an extraordinary range of ecological settings. For individuals to accrue the benefits associated with social interactions, they are required to maintain a degree of spatial and temporal coordination in their activities, and make collective decisions. Such coordination and decision‐making has been the focus of much recent research. However, efforts largely have been directed toward understanding patterns of collective behaviour in relatively stable and cohesive groups. Less well understood is how fission–fusion dynamics mediate the process and outcome of collective decisions making. Here, we aim to apply established concepts and knowledge to highlight the implications of fission–fusion dynamics for collective decisions, presenting a conceptual framework based on the outcome of a small‐group discussion INCORE meeting (funded by the European Community's Sixth Framework Programme). First, we discuss how the degree of uncertainty in the environment shapes social flexibility and therefore the types of decisions individuals make in different social settings. Second, we propose that the quality of social relationships and the energetic needs of each individual influence fission decisions. Third, we explore how these factors affect the probability of individuals to fuse. Fourth, we discuss how group size and fission–fusion dynamics may affect communication processes between individuals at a local or global scale to reach a consensus or to fission. Finally, we offer a number of suggestions for future research, capturing emerging ideas and concepts on the interaction between collective decisions and fission–fusion dynamics.     

How can social network analysis improve the study of primate behavior?

When living in a group, individuals have to make trade-offs, and compromise, in order to balance the advantages and disadvantages of group life. Strategies that enable individuals to achieve this typically affect inter-individual interactions resulting in nonrandom associations. Studying the patterns of this assortativity using social network analyses can allow us to explore how individual behavior influences what happens at the group, or population level. Understanding the consequences of these interactions at multiple scales may allow us to better understand the fitness implications for individuals. Social network analyses offer the tools to achieve this. This special issue aims to highlight the benefits of social network analysis for the study of primate behaviour, assessing it's suitability for analyzing individual social characteristics as well as group/population patterns. In this introduction to the special issue, we first introduce social network theory, then demonstrate with examples how social networks can influence individual and collective behaviors, and finally conclude with some outstanding questions for future primatological research.     

Contact Patterns in a High School: A Comparison between Data Collected Using Wearable Sensors,Contact Diaries and Friendship Surveys

Given their importance in shaping social networks and determining how information or transmissible diseases propagate in a population, interactions between individuals are the subject of many data collection efforts. To this aim, different methods are commonly used, ranging from diaries and surveys to decentralised infrastructures based on wearable sensors. These methods have each advantages and limitations but are rarely compared in a given setting. Moreover, as surveys targeting friendship relations might suffer less from memory biases than contact diaries, it is interesting to explore how actual contact patterns occurring in day-to-day life compare with friendship relations and with online social links. Here we make progresses in these directions by leveraging data collected in a French high school and concerning (i) face-to-face contacts measured by two concurrent methods, namely wearable sensors and contact diaries, (ii) self-reported friendship surveys, and (iii) online social links. We compare the resulting data sets and find that most short contacts are not reported in diaries while long contacts have a large reporting probability, and that the durations of contacts tend to be overestimated in the diaries. Moreover, measured contacts corresponding to reported friendship can have durations of any length but all long contacts do correspond to a reported friendship. On the contrary, online links that are not also reported in the friendship survey correspond to short face-to-face contacts, highlighting the difference of nature between reported friendships and online links. Diaries and surveys suffer moreover from a low sampling rate, as many students did not fill them, showing that the sensor-based platform had a higher acceptability. We also show that, despite the biases of diaries and surveys, the overall structure of the contact network, as quantified by the mixing patterns between classes, is correctly captured by both networks of self-reported contacts and of friendships, and we investigate the correlations between the number of neighbors of individuals in the three networks. Overall, diaries and surveys tend to yield a correct picture of the global structural organization of the contact network, albeit with much less links, and give access to a sort of backbone of the contact network corresponding to the strongest links, i.e., the contacts of longest cumulative durations.     

Group size, grooming and fission in primates: a modeling approach based on group structure

In social animals, fission is a common mode of group proliferation and dispersion and may be affected by genetic or other social factors. Sociality implies preserving relationships between group members. An increase in group size and/or in competition for food within the group can result in decrease certain social interactions between members, and the group may split irreversibly as a consequence. One individual may try to maintain bonds with a maximum of group members in order to keep group cohesion, i.e. proximity and stable relationships. However, this strategy needs time and time is often limited. In addition, previous studies have shown that whatever the group size, an individual interacts only with certain grooming partners. There, we develop a computational model to assess how dynamics of group cohesion are related to group size and to the structure of grooming relationships. Groups’ sizes after simulated fission are compared to observed sizes of 40 groups of primates. Results showed that the relationship between grooming time and group size is dependent on how each individual attributes grooming time to its social partners, i.e. grooming a few number of preferred partners or grooming equally or not all partners. The number of partners seemed to be more important for the group cohesion than the grooming time itself. This structural constraint has important consequences on group sociality, as it gives the possibility of competition for grooming partners, attraction for high-ranking individuals as found in primates’ groups. It could, however, also have implications when considering the cognitive capacities of primates.     

Food Transfer in Sichuan Snub-nosed Monkeys (<Emphasis Type="Italic">Rhinopithecus roxellana</Emphasis>)

Food transfer behavior provides a way to distribute food resources among individuals. It is not confined to kin, but also occurs among genetically unrelated individuals. Food transfer among nonkin may result from byproduct mutualism, reciprocal altruism (RA), or tolerated scrounging (TS). Sichuan snub-nosed monkeys (Rhinopithecus roxellana) exhibit a high level of social tolerance, and researchers have observed food transfer behavior in the wild. However, little is known about how tolerant social relations influence food transfer in this species. We recorded food-related interactions and social behavior in a group of captive Sichuan snub-nosed monkeys. Our findings suggest that the monkeys develop partner preference in food transfer behaviors. Moreover, individuals rely primarily on nonharassed approaches to claim food, suggesting that the TS model alone cannot explain their food transfer. Food transfer in this species may be a form of mutualism, in which an individual benefits on an immediate basis by fostering a preferred and tolerant relationship. However, we cannot rule out the possibility of reciprocal altruism. Future studies should record the temporal delay of social exchange to distinguish between mutualism and reciprocal altruism.     

Using multilayer network analysis to explore the temporal dynamics of collective behavior

Social organisms often show collective behaviors such as group foraging or movement.Collective behaviors can emerge from interactions between group members and may depend on the behavior of key individuals.When social interactions change over time,collective behaviors may change because these behaviors emerge from interactions among individuals.Despite the importance of,and growing interest in,the temporal dynamics of social interactions,it is not clear how to quantify changes in interactions over time or measure their stability.Furthermore,the temporal scale at which we should observe changes in social networks to detect biologically meaningful changes is not always apparent.Here we use multilayer network analysis to quantify temporal dynamics of social networks of the social spider Stegodyphus dumicola and determine how these dynamics relate to individual and group behaviors.We found that social interactions changed over time at a constant rate.Variation in both network structure and the identity of a keystone individual was not related to the mean or variance of the collective prey attack speed.Individuals that maintained a large and stable number of connections,despite changes in network structure,were the boldest individuals in the group.Therefore,social interactions and boldness are linked across time,but group collective behavior is not influenced by the stability of the social network.Our work demonstrates that dynamic social networks can be modeled in a multilayer framework.This approach may reveal biologically important temporal changes to social structure in other systems.     

The ties that bind: genetic relatedness predicts the fission and fusion of social groups in wild African elephants

Many social animals live in stable groups. In contrast, African savannah elephants (Loxodonta africana) live in unusually fluid, fission-fusion societies. That is, 'core' social groups are composed of predictable sets of individuals; however, over the course of hours or days, these groups may temporarily divide and reunite, or they may fuse with other social groups to form much larger social units. Here, we test the hypothesis that genetic relatedness predicts patterns of group fission and fusion among wild, female African elephants. Our study of a single Kenyan population spans 236 individuals in 45 core social groups, genotyped at 11 microsatellite and one mitochondrial DNA (mtDNA) locus. We found that genetic relatedness predicted group fission; adult females remained with their first order maternal relatives when core groups fissioned temporarily. Relatedness also predicted temporary fusion between social groups; core groups were more likely to fuse with each other when the oldest females in each group were genetic relatives. Groups that shared mtDNA haplotypes were also significantly more likely to fuse than groups that did not share mtDNA. Our results suggest that associations between core social groups persist for decades after the original maternal kin have died. We discuss these results in the context of kin selection and its possible role in the evolution of elephant sociality.     

Relationship quality affects fission decisions in wild spider monkeys (Ateles geoffroyi)

Fission–fusion dynamics are thought to be mainly a response to differential availability of food resources. However, social factors may also play a role. Here, we examined whether the quality of social relationships between group members affects fission decisions. During 21 months, we collected data on social interactions and fission events of 22 spider monkeys (Ateles geoffroyi) living in a community in the protected area of Otoch Ma'ax Yetel Kooh, Yucatan, Mexico. By entering seven indexes of social interactions into a principal component analysis, we obtained three components of relationship quality, which we labelled “compatibility,” “value” and “insecurity” given the relative loadings of the indexes. Our results showed that individuals were more likely to fission into the same subgroup with community members with whom they shared higher levels of compatibility and value and lower levels of insecurity. In addition, individuals preferred to fission into the same subgroup with same‐sex group members, as expected based on what is known for the species. Our findings highlight the role of social factors in fission decisions. Adjustments in subgroup size are based on multifaceted social preferences, incorporating previously unexamined aspects of relationship quality, which are independent from overall levels of affiliative interactions.     

Defecting or not defecting: how to "read" human behavior during cooperative games by EEG measurements

Understanding the neural mechanisms responsible for human social interactions is difficult, since the brain activities of two or more individuals have to be examined simultaneously and correlated with the observed social patterns. We introduce the concept of hyper-brain network, a connectivity pattern representing at once the information flow among the cortical regions of a single brain as well as the relations among the areas of two distinct brains. Graph analysis of hyper-brain networks constructed from the EEG scanning of 26 couples of individuals playing the Iterated Prisoner's Dilemma reveals the possibility to predict non-cooperative interactions during the decision-making phase. The hyper-brain networks of two-defector couples have significantly less inter-brain links and overall higher modularity--i.e., the tendency to form two separate subgraphs--than couples playing cooperative or tit-for-tat strategies. The decision to defect can be "read" in advance by evaluating the changes of connectivity pattern in the hyper-brain network.     

Social and spatial effects on genetic variation between foraging flocks in a wild bird population

Social interactions are rarely random. In some instances, animals exhibit homophily or heterophily, the tendency to interact with similar or dissimilar conspecifics, respectively. Genetic homophily and heterophily influence the evolutionary dynamics of populations, because they potentially affect sexual and social selection. Here, we investigate the link between social interactions and allele frequencies in foraging flocks of great tits (Parus major) over three consecutive years. We constructed co‐occurrence networks which explicitly described the splitting and merging of 85,602 flocks through time (fission–fusion dynamics), at 60 feeding sites. Of the 1,711 birds in those flocks, we genotyped 962 individuals at 4,701 autosomal single nucleotide polymorphisms (SNPs). By combining genomewide genotyping with repeated field observations of the same individuals, we were able to investigate links between social structure and allele frequencies at a much finer scale than was previously possible. We explicitly accounted for potential spatial effects underlying genetic structure at the population level. We modelled social structure and spatial configuration of great tit fission–fusion dynamics with eigenvector maps. Variance partitioning revealed that allele frequencies were strongly affected by group fidelity (explaining 27%–45% of variance) as individuals tended to maintain associations with the same conspecifics. These conspecifics were genetically more dissimilar than expected, shown by genomewide heterophily for pure social (i.e., space‐independent) grouping preferences. Genomewide homophily was linked to spatial configuration, indicating spatial segregation of genotypes. We did not find evidence for homophily or heterophily for putative socially relevant candidate genes or any other SNP markers. Together, these results demonstrate the importance of distinguishing social and spatial processes in determining population structure.     

The social fabric of citizen science—drivers for long-term engagement in the German butterfly monitoring scheme

Insect conservation needs sound information on species distribution trends. Developing this evidence relies—in practice—on long-term engagement of volunteers who observe and record species over large spatial and temporal scales. Many biodiversity monitoring schemes, including those for insects, are highly dependent on conservation-based citizen science programs with a long-term continuity. As these schemes are built entirely on good will, the nature of social relations and networks is pivotal to success. We assess the working mechanism of a monitoring scheme that is citizen-based as a case study. The German Butterfly Monitoring Scheme (hereafter TMD for “Tagfalter-Monitoring Deutschland”) operates, as many other citizen science monitoring schemes, through an overarching national network of regional subnetworks of volunteers and a central scientific coordination. Using a questionnaire survey paired with a visual social network assessment, we investigate how participants interact within these networks and assess their motivations to engage. We characterise the functionality of this social network based on mechanism of coordination and participation, flows of information and knowledge exchange among recorders, regional and central coordinators, academic scientists and institutions. By analyzing the interactions, we show how the social network facilitates and ensures various communication modes and thereby fosters long-term engagement, stability and growth of the scheme. We identify the central role of project coordination and the importance of social relations within citizen-based monitoring programs for engagement and personal satisfaction. Based on our empirical study, we derive a set of recommendations for establishing and maintaining successful volunteer networks in insect citizen-based monitoring programs.     

Behavioural phenotype affects social interactions in an animal network

Animal social networks can be extremely complex and are characterized by highly non-random interactions between group members. However, very little is known about the underlying factors affecting interaction preferences, and hence network structure. One possibility is that behavioural differences between individuals, such as how bold or shy they are, can affect the frequency and distribution of their interactions within a network. We tested this using individually marked three-spined sticklebacks (Gasterosteus aculeatus), and found that bold individuals had fewer overall interactions than shy fish, but tended to distribute their interactions more evenly across all group members. Shy fish, on the other hand, tended to associate preferentially with a small number of other group members, leading to a highly skewed distribution of interactions. This was mediated by the reduced tendency of shy fish to move to a new location within the tank when they were interacting with another individual; bold fish showed no such tendency and were equally likely to move irrespective of whether they were interacting or not. The results show that animal social network structure can be affected by the behavioural composition of group members and have important implications for understanding the spread of information and disease in social groups.     

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.     

Nutritional ecology beyond the individual: a conceptual framework for integrating nutrition and social interactions

Over recent years, modelling approaches from nutritional ecology (known as Nutritional Geometry) have been increasingly used to describe how animals and some other organisms select foods and eat them in appropriate amounts in order to maintain a balanced nutritional state maximising fitness. These nutritional strategies profoundly affect the physiology, behaviour and performance of individuals, which in turn impact their social interactions within groups and societies. Here, we present a conceptual framework to study the role of nutrition as a major ecological factor influencing the development and maintenance of social life. We first illustrate some of the mechanisms by which nutritional differences among individuals mediate social interactions in a broad range of species and ecological contexts. We then explain how studying individual‐ and collective‐level nutrition in a common conceptual framework derived from Nutritional Geometry can bring new fundamental insights into the mechanisms and evolution of social interactions, using a combination of simulation models and manipulative experiments.     

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.     

Social features of online networks: the strength of intermediary ties in online social media

An increasing fraction of today's social interactions occur using online social media as communication channels. Recent worldwide events, such as social movements in Spain or revolts in the Middle East, highlight their capacity to boost people's coordination. Online networks display in general a rich internal structure where users can choose among different types and intensity of interactions. Despite this, there are still open questions regarding the social value of online interactions. For example, the existence of users with millions of online friends sheds doubts on the relevance of these relations. In this work, we focus on Twitter, one of the most popular online social networks, and find that the network formed by the basic type of connections is organized in groups. The activity of the users conforms to the landscape determined by such groups. Furthermore, Twitter's distinction between different types of interactions allows us to establish a parallelism between online and offline social networks: personal interactions are more likely to occur on internal links to the groups (the weakness of strong ties); events transmitting new information go preferentially through links connecting different groups (the strength of weak ties) or even more through links connecting to users belonging to several groups that act as brokers (the strength of intermediary ties).     

Evolution of Cooperation on Stochastic Dynamical Networks

Cooperative behavior that increases the fitness of others at a cost to oneself can be promoted by natural selection only in the presence of an additional mechanism. One such mechanism is based on population structure, which can lead to clustering of cooperating agents. Recently, the focus has turned to complex dynamical population structures such as social networks, where the nodes represent individuals and links represent social relationships. We investigate how the dynamics of a social network can change the level of cooperation in the network. Individuals either update their strategies by imitating their partners or adjust their social ties. For the dynamics of the network structure, a random link is selected and breaks with a probability determined by the adjacent individuals. Once it is broken, a new one is established. This linking dynamics can be conveniently characterized by a Markov chain in the configuration space of an ever-changing network of interacting agents. Our model can be analytically solved provided the dynamics of links proceeds much faster than the dynamics of strategies. This leads to a simple rule for the evolution of cooperation: The more fragile links between cooperating players and non-cooperating players are (or the more robust links between cooperators are), the more likely cooperation prevails. Our approach may pave the way for analytically investigating coevolution of strategy and structure.     

Social traits,social networks and evolutionary biology

The social environment is both an important agent of selection for most organisms, and an emergent property of their interactions. As an aggregation of interactions among members of a population, the social environment is a product of many sets of relationships and so can be represented as a network or matrix. Social network analysis in animals has focused on why these networks possess the structure they do, and whether individuals’ network traits, representing some aspect of their social phenotype, relate to their fitness. Meanwhile, quantitative geneticists have demonstrated that traits expressed in a social context can depend on the phenotypes and genotypes of interacting partners, leading to influences of the social environment on the traits and fitness of individuals and the evolutionary trajectories of populations. Therefore, both fields are investigating similar topics, yet have arrived at these points relatively independently. We review how these approaches are diverged, and yet how they retain clear parallelism and so strong potential for complementarity. This demonstrates that, despite separate bodies of theory, advances in one might inform the other. Techniques in network analysis for quantifying social phenotypes, and for identifying community structure, should be useful for those studying the relationship between individual behaviour and group‐level phenotypes. Entering social association matrices into quantitative genetic models may also reduce bias in heritability estimates, and allow the estimation of the influence of social connectedness on trait expression. Current methods for measuring natural selection in a social context explicitly account for the fact that a trait is not necessarily the property of a single individual, something the network approaches have not yet considered when relating network metrics to individual fitness. Harnessing evolutionary models that consider traits affected by genes in other individuals (i.e. indirect genetic effects) provides the potential to understand how entire networks of social interactions in populations influence phenotypes and predict how these traits may evolve. By theoretical integration of social network analysis and quantitative genetics, we hope to identify areas of compatibility and incompatibility and to direct research efforts towards the most promising areas. Continuing this synthesis could provide important insights into the evolution of traits expressed in a social context and the evolutionary consequences of complex and nuanced social phenotypes.     

Dyadic associations reveal clan size and social network structure in the fission–fusion society of spotted hyaenas

Estimating the size and dynamics of populations is of paramount importance in ecology. In species with uniquely marked individuals, capture–recapture methods can be used to establish population size and to explore associations between individuals. However, very few studies have used cameras traps to focus on group composition in social carnivores, despite being of particular interest in species characterised by “fission–fusion” formation of sub-groups. Here, we provide estimates of (a) population size, (b) density, (c) clan size, (d) association patterns and (e) social network structure in spotted hyaenas (Crocuta crocuta) based on images from camera traps deployed at waterholes on Ongava Game Reserve (northern Namibia). In a 15 week study period, we identified 32 individuals. Dyadic associations and the resulting social network showed that all but two hyaenas associated directly or indirectly with each other, indicating the presence of one clan of at least 30 individuals, resulting in a density of 8.1 hyaenas/100 km². We found a very high variability in the tendency of individuals to associate with others. This study confirms a highly dynamic fission–fusion society in spotted hyaenas. We argue that camera traps can provide relevant insights into large carnivore social network structure where associations between individuals are difficult to observe directly.     

网络分析法在动物声音通讯及生物声学研究中的应用与前景

动物社会网络分析法(animal social network analysis,ASNA)是一套用于研究动物社会性、量化个体间各种社会关系、揭示个体行为与社会结构动态之间联系的工具,被广泛应用于多种动物类群的行为学研究。该分析方法所提供的一系列指标也非常适用于探究动物的声音交流及鸣声结构。在此,本文首先简要介绍了网络分析法的基本概念及一些常用的指标;然后基于野外和室内研究实例,阐述了如何利用ASNA建立声音通讯网络、量化声音交流,以及将ASNA与被动声学监测技术相结合的应用前景;随后探讨了ASNA在分析鸣声相似性及鸣声地理变异中的优势;最后概述了ASNA在解析鸣声结构和句法规则中的应用。ASNA为研究动物通讯网络以及声音信号的适应性进化提供了新的视角和新的思路。