Social Structure of a Semi-Free Ranging Group of Mandrills (Mandrillus sphinx): A Social Network Analysis

The difficulty involved in following mandrills in the wild means that very little is known about social structure in this species. Most studies initially considered mandrill groups to be an aggregation of one-male/multifemale units, with males occupying central positions in a structure similar to those observed in the majority of baboon species. However, a recent study hypothesized that mandrills form stable groups with only two or three permanent males, and that females occupy more central positions than males within these groups. We used social network analysis methods to examine how a semi-free ranging group of 19 mandrills is structured. We recorded all dyads of individuals that were in contact as a measure of association. The betweenness and the eigenvector centrality for each individual were calculated and correlated to kinship, age and dominance. Finally, we performed a resilience analysis by simulating the removal of individuals displaying the highest betweenness and eigenvector centrality values. We found that related dyads were more frequently associated than unrelated dyads. Moreover, our results showed that the cumulative distribution of individual betweenness and eigenvector centrality followed a power function, which is characteristic of scale-free networks. This property showed that some group members, mostly females, occupied a highly central position. Finally, the resilience analysis showed that the removal of the two most central females split the network into small subgroups and increased the network diameter. Critically, this study confirms that females appear to occupy more central positions than males in mandrill groups. Consequently, these females appear to be crucial for group cohesion and probably play a pivotal role in this species.     

Being in the thick of things: context-dependent network centrality in a captive flock of American flamingos

We test the hypothesis that the relationship between networks resulting from unresolved agonistic interactions (URI) and social dominance was context-dependent in a captive group of American Flamingos (Phoenicopterus ruber ruber). URI formed networks that differed substantially from the dominance network and depended on the context in which the interactions occurred. Betweenness centrality in the URI network on the region (“the island”) where nesting took place was strongly correlated with dominance score. This correlation was particularly strong in the case of males, but, in both sexes, the dominant individual in a dyad was likely to have a higher betweenness centrality in the island URI. On the other hand, betweenness centrality in URI networks at the feeder did not show any relationship with dominance, but was associated with observed visits to the feeder. Thus, centrality in both the island URI network and the feeder URI network was associated with access to a resource over which individuals competed. Along with other results suggesting that non-dominance interactions may form social networks distinct from, but related to, dominance networks, our results support the hypothesis that relationships within animal social groups can be modeled as a series of distinct but inter-related networks.     

Network cohesion,group size and neocortex size in female-bonded Old World primates

Most primates are intensely social and spend a large amount of time servicing social relationships. In this study, we use social network analysis to examine the relationship between primate group size, total brain size, neocortex ratio and several social network metrics concerned with network cohesion. Using female grooming networks from a number of Old World monkey species, we found that neocortex size was a better predictor of network characteristics than endocranial volumes. We further found that when we controlled for group size, neocortex ratio was negatively correlated with network density, connectivity, relative clan size and proportional clan membership, while there was no effect of neocortex ratio on change in connectivity following the removal of the most central female in the network. Thus, in species with larger neocortex ratios, females generally live in more fragmented networks, belong to smaller grooming clans and are members of relatively fewer clans despite living in a closely bonded group. However, even though groups are more fragmented to begin with among species with larger neocortices, the removal of the most central individual does cause groups to fall apart, suggesting that social complexity may ultimately involve the management of highly fragmented social groups while at the same time maintaining overall social cohesion. These results emphasize a need for more detailed brain data on a wider sample of primate species.     

The organisational structure of protein networks: revisiting the centrality–lethality hypothesis

Protein networks, describing physical interactions as well as functional associations between proteins, have been unravelled for many organisms in the recent past. Databases such as the STRING provide excellent resources for the analysis of such networks. In this contribution, we revisit the organisation of protein networks, particularly the centrality–lethality hypothesis, which hypothesises that nodes with higher centrality in a network are more likely to produce lethal phenotypes on removal, compared to nodes with lower centrality. We consider the protein networks of a diverse set of 20 organisms, with essentiality information available in the Database of Essential Genes and assess the relationship between centrality measures and lethality. For each of these organisms, we obtained networks of high-confidence interactions from the STRING database, and computed network parameters such as degree, betweenness centrality, closeness centrality and pairwise disconnectivity indices. We observe that the networks considered here are predominantly disassortative. Further, we observe that essential nodes in a network have a significantly higher average degree and betweenness centrality, compared to the network average. Most previous studies have evaluated the centrality–lethality hypothesis for Saccharomyces cerevisiae and Escherichia coli; we here observe that the centrality–lethality hypothesis hold goods for a large number of organisms, with certain limitations. Betweenness centrality may also be a useful measure to identify essential nodes, but measures like closeness centrality and pairwise disconnectivity are not significantly higher for essential nodes.     

The dining etiquette of desert baboons: the roles of social bonds, kinship, and dominance in co-feeding networks

To better understand how individual relationships influence patterns of social foraging in primate groups, we explored networks of co-feeding in wild desert baboons (Papio ursinus). To minimize the risk of aggression and injury associated with contest competition, we expected that individual group members would choose to co-feed with those group-mates that are most likely to show tolerance and a willingness to share food patches. We tested two alternative hypotheses about who those group-mates might be: the "social bonds hypothesis" predicts that preferred foraging partners will be those with whom individuals share strong social bonds, indexed by grooming, whereas the "kinship hypothesis" predicts that preferred foraging partners will be relatives. We also investigated and controlled for the effects of dominance rank, given that competitive ability is known to shape foraging patterns. Social network analyses of over 5,000 foraging events for 14 adults in a single troop revealed that baboon co-feeding was significantly correlated with grooming relationships but not genetic relatedness, and this finding was also true of the female-only co-feeding network. Dominant individuals were also found to be central to the co-feeding network, frequently sharing food patches with multiple group-mates. This polyadic analysis of foraging associations between individuals underlines the importance of dominance and affiliation to patterns of primate social foraging.     

Fitness consequences of centrality in mutualistic individual-based networks

The relationships among the members of a population can be visualized using individual networks, where each individual is a node connected to each other by means of links describing the interactions. The centrality of a given node captures its importance within the network. We hypothesize that in mutualistic networks, the centrality of a node should benefit its fitness. We test this idea studying eight individual-based networks originated from the interaction between Erysimum mediohispanicum and its flower visitors. In these networks, each plant was considered a node and was connected to conspecifics sharing flower visitors. Centrality indicates how well connected is a given E. mediohispanicum individual with the rest of the co-occurring conspecifics because of sharing flower visitors. The centrality was estimated by three network metrics: betweenness, closeness and degree. The complex relationship between centrality, phenotype and fitness was explored by structural equation modelling. We found that the centrality of a plant was related to its fitness, with plants occupying central positions having higher fitness than those occupying peripheral positions. The structural equation models (SEMs) indicated that the centrality effect on fitness was not merely an effect of the abundance of visits and the species richness of visitors. Centrality has an effect even when simultaneously accounting for these predictors. The SEMs also indicated that the centrality effect on fitness was because of the specific phenotype of each plant, with attractive plants occupying central positions in networks, in relation to the distribution of conspecific phenotypes. This finding suggests that centrality, owing to its dependence on social interactions, may be an appropriate surrogate for the interacting phenotype of individuals.     

Dominance rank predicts social network position across developmental stages in rhesus monkeys

Social network analysis is increasingly common in studying complex interactions among individuals. Across a range of primates, high-ranking adults are generally more socially connected, which results in better fitness outcomes. However, it still remains unclear whether this relationship between social network position and dominance rank emerges in infancy and whether, in species with a social transmission of dominance rank, social network positions are driven by the presence of the mother. To fill this gap, we first explored whether dominance ranks were related to social network position, measured via eigenvector centrality, in infants, juveniles, and adults in a troop of semi-free-ranging rhesus macaques (Macaca mulatta). We then examined relationships between dominance rank and eigenvector centrality in a peer-only group of yearlings who were reared with their mothers in either a rich, socially complex environment of multigenerational (MG) kin support or a unigenerational group of mothers and their infants from birth through 8 months. In Experiment 1, we found that mother's network position predicted offspring network position and that dominants across all age categories were more central in affiliative networks (social contact, social grooming, and social play). Experiment 2 showed that high-ranking yearlings in a peer-only group were more central only in the social contact network. Moreover, yearlings reared in a socially complex environment of MG kin support were more central. Our findings suggest that the relationship between dominance rank and social network position begins early in life, and that complex early social environments can promote later social competency. Our data add to the growing body of evidence that the presence/absence of the mother and kin influence how dominance rank affects social network position. These findings have important implications for the role of caregivers in the social status of developing primates, which ultimately ties to health and fitness outcomes.     

Formidable females redux:male social integration into female networks and the value of dynamic multilayer networks

The development of multilayer network techniques is a boon for researchers who wish to understand how different interaction layers might influence each other,and how these in turn might influence group dynamics.Here,we investigate how integration between male and female grooming and aggression interaction networks influences male power trajectories in vervet monkeys Chlorocebus pygerythrus.Our previous analyses of this phenomenon used a monolayer approach,and our aim here is to extend these analyses using a dynamic multilayer approach.To do so,we constructed a temporal series of male and female interaction layers.We then used a multivariate multilevel autoregression model to compare cross-lagged associations between a male's centrality in the female grooming layer and changes in male Elo ratings.Our results confirmed our original findings:changes in male centrality within the female grooming network were weakly but positively tied to changes in their Elo ratings.However,the multilayer network approach offered additional insights into this social process,identifying how changes in a male's centrality cascade through the other network layers.This dynamic view indicates that the changes in Elo ratings are likely to be short-lived,but that male centrality within the female network had a much stronger impact throughout the multilayer network as a whole,especially on reducing intermale aggression(i.e.,aggression directed by males toward other males).We suggest that multilayer social network approaches can take advantage of increased amounts of social data that are more commonly collected these days,using a variety of methods.Such data are inherently multilevel and multilayered,and thus offer the ability to quantify more precisely the dynamics of animal social behaviors.     

Spatial familial networks to infer demographic structure of wild populations

1. In social species, reproductive success and rates of dispersal vary among individuals resulting in spatially structured populations. Network analyses of familial relationships may provide insights on how these parameters influence population‐level demographic patterns. These methods, however, have rarely been applied to genetically derived pedigree data from wild populations.
2. Here, we use parent–offspring relationships to construct familial networks from polygamous boreal woodland caribou (Rangifer tarandus caribou) in Saskatchewan, Canada, to inform recovery efforts. We collected samples from 933 individuals at 15 variable microsatellite loci along with caribou‐specific primers for sex identification. Using network measures, we assess the contribution of individual caribou to the population with several centrality measures and then determine which measures are best suited to inform on the population demographic structure. We investigate the centrality of individuals from eighteen different local areas, along with the entire population.
3. We found substantial differences in centrality of individuals in different local areas, that in turn contributed differently to the full network, highlighting the importance of analyzing networks at different scales. The full network revealed that boreal caribou in Saskatchewan form a complex, interconnected familial network, as the removal of edges with high betweenness did not result in distinct subgroups. Alpha, betweenness, and eccentricity centrality were the most informative measures to characterize the population demographic structure and for spatially identifying areas of highest fitness levels and family cohesion across the range. We found varied levels of dispersal, fitness, and cohesion in family groups.
4. Synthesis and applications: Our results demonstrate the value of different network measures in assessing genetically derived familial networks. The spatial application of the familial networks identified individuals presenting different fitness levels, short‐ and long‐distance dispersing ability across the range in support of population monitoring and recovery efforts.

     

Network stability is a balancing act of personality, power, and conflict dynamics in rhesus macaque societies

Stability in biological systems requires evolved mechanisms that promote robustness. Cohesive primate social groups represent one example of a stable biological system, which persist in spite of frequent conflict. Multiple sources of stability likely exist for any biological system and such robustness, or lack thereof, should be reflected and thus detectable in the group's network structure, and likely at multiple levels. Here we show how network structure and group stability are linked to the fundamental characteristics of the individual agents in groups and to the environmental and social contexts in which these individuals interact. Both internal factors (e.g., personality, sex) and external factors (e.g., rank dynamics, sex ratio) were considered from the level of the individual to that of the group to examine the effects of network structure on group stability in a nonhuman primate species. The results yielded three main findings. First, successful third-party intervention behavior is a mechanism of group stability in rhesus macaques in that successful interventions resulted in less wounding in social groups. Second, personality is the primary factor that determines which individuals perform the role of key intervener, via its effect on social power and dominance discrepancy. Finally, individuals with high social power are not only key interveners but also key players in grooming networks and receive reconciliations from a higher diversity of individuals. The results from this study provide sound evidence that individual and group characteristics such as personality and sex ratio influence network structures such as patterns of reconciliation, grooming and conflict intervention that are indicators of network robustness and consequent health and well-being in rhesus macaque societies. Utilizing this network approach has provided greater insight into how behavioral and social processes influence social stability in nonhuman primate groups.     

Discovering Implicit Entity Relation with the Gene-Citation-Gene Network

In this paper, we apply the entitymetrics model to our constructed Gene-Citation-Gene (GCG) network. Based on the premise there is a hidden, but plausible, relationship between an entity in one article and an entity in its citing article, we constructed a GCG network of gene pairs implicitly connected through citation. We compare the performance of this GCG network to a gene-gene (GG) network constructed over the same corpus but which uses gene pairs explicitly connected through traditional co-occurrence. Using 331,411 MEDLINE abstracts collected from 18,323 seed articles and their references, we identify 25 gene pairs. A comparison of these pairs with interactions found in BioGRID reveal that 96% of the gene pairs in the GCG network have known interactions. We measure network performance using degree, weighted degree, closeness, betweenness centrality and PageRank. Combining all measures, we find the GCG network has more gene pairs, but a lower matching rate than the GG network. However, combining top ranked genes in both networks produces a matching rate of 35.53%. By visualizing both the GG and GCG networks, we find that cancer is the most dominant disease associated with the genes in both networks. Overall, the study indicates that the GCG network can be useful for detecting gene interaction in an implicit manner.     

Network measures for dyadic interactions: stability and reliability

Social network analysis (SNA) is a general heading for a collection of statistical tools that aim to describe social interactions and social structure by representing individuals and their interactions as graph objects. It was originally developed for the social sciences, but more recently it was also adopted by behavioral ecologists. However, although SNA offers a full range of exciting possibilities for the study of animal societies, some authors have raised concerns about the correct application and interpretation of network measures. In this article, we investigate how reliable and how stable network measures are (i.e. how much variation they show under re-sampling and how much they are influenced by erroneous observations). For this purpose, we took a data set of 44 nonhuman primate grooming networks and studied the effects of re-sampling at lower re-sampling rates than the originally observed ones and the inclusion of two types of errors, "mis-identification" and "mis-classification," on six different network metrics, i.e. density, degree variance, vertex strength variance, edge weight disparity, clustering coefficient, and closeness centrality. Although some measures were tolerant toward reduced sample sizes, others were sensitive and even slightly reduced samples could yield drastically different results. How strongly a metric is affected seems to depend on both the sample size and the structure of the specific network. The same general effects were found for the inclusion of sampling errors. We, therefore, emphasize the importance of calculating valid confidence intervals for network measures and, finally, we suggest a rough research plan for network studies.     

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.     

Is human conversation more efficient than chimpanzee grooming?

Clique sizes for chimpanzee (Pan troglodytes) grooming and for human conversation are compared in order to test Robin Dunbar’s hypothesis that human language is almost three times as efficient a bonding mechanism as primate grooming. Recalculation of the data provided by Dunbar et al. (1995) reveals that the average clique size for human conversation is 2.72 whereas that of chimpanzee grooming is shown to be 2.18. The efficiency of human conversation and actual chimpanzee grooming over Dunbar’s primate grooming model (always one-to-one and a one-way interaction) is 1.27 and 1.25, respectively, when we take role alternation into account. Chimpanzees can obtain about the same efficiency as humans in terms of quantity of social interactions because their grooming is often mutual and polyadic. The fieldwork was supported by a grant from the International Scientific Research Program (07041138 to T. Nishida) of the Monbusho (Japanese Ministry of Education, Science, Sports, and Culture). Michio Nakamura is a research fellow at Japan Monkey Centre. He received his Master of Science degree from Kyoto University in 1996. He is carrying out research on the grooming behavior of chimpanzees at Mahale, Tanzania, for his doctorate.     

Vocal networks remain stable after a disturbance in Emei music frogs

Social network analysis has been widely used to investigate the dynamics of social interactions and the evolution of social complexity across a range of taxa. Anuran species are highly dependent on vocal communication in mate choice; however, these species have rarely been the subject of social network analysis. The present study used social network analysis to investigate whether vocal network structures are consistent in Emei music frog (Babina daunchina) after the introduction of a simulated exotic rival of varying competitiveness into the social group. We broadcasted six categories of artificial calls (either highly sexually attractive calls produced from inside male nests or calls of low sexual attractiveness produced outside nests with three, five or seven notes, respectively) to simulate an intruder with different levels of competitiveness. We then constructed vocal networks for two time periods (before and after the disturbance) and quantified three network metrics (strength, closeness, and betweenness) that measure different aspects of individual‐level position. We used the mean values of these network metrics to evaluate group‐level changes in network structure. We found that the mean strength, mean closeness and mean betweenness were consistent between two time periods in all ponds, despite the fact that the positions of some individuals had changed markedly after disturbance. In addition, there was no significant interaction effect between period and numbers of notes on the three network metrics. These finding suggest that the structure of vocal networks in Emei music frogs remain stable at the group level after a conspecific disturbance, regardless of the intruder's competitiveness.     

Alternative approaches of transforming bimodal into unimodal mutualistic networks. The usefulness of preserving weighted information

Pollination and seed dispersal networks are by definition bimodal, linking two sets of species, plants and animals. Bimodal networks are often analysed after being transformed into unimodal ones, since most attributes in network theory are defined for the latter. Such unimodal projections (e.g. of plants sharing flower visitors or seed dispersers) map potential inter-specific competition or facilitation, and can thus be useful for instance when identifying native species potentially sensitive to aliens in the communities. In this work, we introduce procedures to project unweighted and weighted bimodal networks into unimodals, for animals or plants, and calculate two centrality measures that inform us about the species’ role in the communities. By using 20 empirical weighted networks worldwide, we obtained 160 unimodal networks via four projection methods and evaluated correlations among centrality parameters across the different methodologies to assess how consistent the results are when including different link weights between species. Degree centralities obtained by projecting unweighted and weighted bimodal networks were not significantly correlated, suggesting that the role of the species differs when considering link weights in the original bimodal networks. By contrast, betweenness centralities were highly correlated, indicating the consistent importance of the species as connectors regardless of the projection method used. We conclude that preserving the weighted information when transforming bimodal into unimodal networks may allow us to make more realistic predictions on the potential competitive or facilitative interactions among species of one set (e.g. plants) that share species of the other (e.g. flower visitors or dispersers).     

Aggression, grooming and group-level cooperation in white-faced capuchins (Cebus capucinus): insights from social networks

The form of animal social systems depends on the nature of agonistic and affiliative interactions. Social network theory provides tools for characterizing social structure that go beyond simple dyadic interactions and consider the group as a whole. We show three groups of capuchin monkeys from Barro Colorado Island, Panama, where there are strong connections between key aspects of aggression, grooming, and proximity networks, and, at least among females, those who incur risk to defend their group have particular "social personalities." Although there is no significant correlation for any of the network measures between giving and receiving aggression, suggesting that dominance relationships do not follow a simple hierarchy, strong correlations emerge for many measures between the aggression and grooming networks. At the local, but not global, scale, receiving aggression and giving grooming are strongly linked in all groups. Proximity shows no correlation with aggression at either the local or the global scale, suggesting that individuals neither seek out nor avoid aggressors. Yet, grooming has a global but not local connection to proximity. Extensive groomers who tend to direct their efforts at other extensive groomers also spend time in close proximity to many other individuals. These results indicate the important role that prosociality plays in shaping female social relationships. We also show that females who receive the least aggression, and thus pay low costs for group living, are most likely to participate in group defense. No consistent "social personality" traits characterize the males who invest in group defense.     

Inter-individual relationships in proboscis monkeys: a preliminary comparison with other non-human primates

This is the first report on inter-individual relationships within a one-male group of proboscis monkeys (Nasalis larvatus) based on detailed identification of individuals. From May 2005 to 2006, focal and ad libitum data of agonistic and grooming behaviour were collected in a forest along the Menanggul River, Sabah, Malaysia. During the study period, we collected over 1,968 h of focal data on the adult male and 1,539 h of focal data on the six females. Their social interactions, including agonistic and grooming behaviour, appeared to follow typical patterns reported for other colobines: the incidence of social interaction within groups is low. Of 39 agonistic events, 26 were displacement from sleeping places along the river, 6 were the α male threatening other monkeys to mediate quarrels between females and between females and juveniles, and 7 were displacement from feeding places. Although the agonistic behaviour matrix based on the 33 intra-group agonistic events (excluding events between adults and juveniles and between adults and infants) was indicative of non-significant linearity, there were some specific dominated individuals within the group of proboscis monkeys. Nonetheless, grooming behaviour among adult females within a group were not affected by the dominance hierarchy. This study also conducted initial comparisons of grooming patterns among proboscis monkeys and other primate species. On the basis of comparison of their grooming networks, similar grooming patterns among both-sex-disperse and male-philopatric/female-disperse species were detected. Because adult females in these species migrate to groups repeatedly, it may be difficult to establish the firm grooming exchange relationship for particular individuals within groups, unlike in female-philopatric/male-disperse species. However, grooming distribution patterns within groups among primate species were difficult to explain solely on the basis of their dispersal patterns. Newly immigrated females in some species including proboscis monkeys are eager to have social interactions with senior group members to improve their social position.     

Information Flow Analysis of Interactome Networks

Recent studies of cellular networks have revealed modular organizations of genes and proteins. For example, in interactome networks, a module refers to a group of interacting proteins that form molecular complexes and/or biochemical pathways and together mediate a biological process. However, it is still poorly understood how biological information is transmitted between different modules. We have developed information flow analysis, a new computational approach that identifies proteins central to the transmission of biological information throughout the network. In the information flow analysis, we represent an interactome network as an electrical circuit, where interactions are modeled as resistors and proteins as interconnecting junctions. Construing the propagation of biological signals as flow of electrical current, our method calculates an information flow score for every protein. Unlike previous metrics of network centrality such as degree or betweenness that only consider topological features, our approach incorporates confidence scores of protein–protein interactions and automatically considers all possible paths in a network when evaluating the importance of each protein. We apply our method to the interactome networks of Saccharomyces cerevisiae and Caenorhabditis elegans. We find that the likelihood of observing lethality and pleiotropy when a protein is eliminated is positively correlated with the protein's information flow score. Even among proteins of low degree or low betweenness, high information scores serve as a strong predictor of loss-of-function lethality or pleiotropy. The correlation between information flow scores and phenotypes supports our hypothesis that the proteins of high information flow reside in central positions in interactome networks. We also show that the ranks of information flow scores are more consistent than that of betweenness when a large amount of noisy data is added to an interactome. Finally, we combine gene expression data with interaction data in C. elegans and construct an interactome network for muscle-specific genes. We find that genes that rank high in terms of information flow in the muscle interactome network but not in the entire network tend to play important roles in muscle function. This framework for studying tissue-specific networks by the information flow model can be applied to other tissues and other organisms as well.