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.     

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.     

Socially mediated speciation

Abstract.— We employ a simple model to show that social selection can lead to prezygotic reproductive isolation. The evolution of social discrimination causes the congealing of phenotypically similar individuals into different, spatially distinct tribes. However, tribal formation is only obtained for certain types of social behavior: altruistic and selfish acts can produce tribes, whereas spiteful and mutualistic behaviors never do. Moreover, reduced hybrid fitness at tribal borders leads to the selection of mating preferences, which then spread to the core areas of the respective tribes. Unlike models of resource competition, our model generates reproductive isolation in an ecologically homogeneous environment. We elaborate on how altruistic acts can lead to reproductive isolation, but also predict that certain types of competition can lead to the speciation effect. Our theory provides a framework for how individual-level interactions mold lineage diversification, with parapatric speciation as a possible end product.     

Multilayer network analyses as a toolkit for measuring social structure

The formalization of multilayer networks allows for new ways to measure sociality in complex social systems,including groups of animals.The same mathematical representation and methods are widely applicable across fields and study systems,and a network can represent drastically different types of data.As such,in order to apply analyses and interpret the results in a meaningful way the researcher must have a deep understanding of what their network is representing and what parts of it are being measured by a given analysis.Multilayer social networks can represent social structure with more detail than is often present in single layer networks,including multiple"types"of individuals,interactions,or relationships,and the extent to which these types are interdependent.Multilayer networks can also encompass a wider range of social scales,which can help overcome complications that are inherent to measuring sociality.In this paper,I dissect multilayer networks into the parts that correspond to different components of social structures.I then discuss common pitfalls to avoid across different stages of multilayer network analyses-some novel and some that always exist in social network analysis but are magnified in multi-layer representations.This paper serves as a primer for building a customized toolkit of multilayer network analyses,to probe components of social structure in animal social systems.     

Baboon (Papio anubis) social complexity--a network approach

Although many studies have analyzed the causes and consequences of social relationships, few studies have explicitly assessed how measures of social relationships are affected by the choice of behaviors used to quantify them. The use of many behaviors to measure social relationships in primates has long been advocated, but it was analytically difficult to implement this framework into primatological work. However, recent advances in social network analysis (SNA) now allow the comparison of multiple networks created from different behaviors. Here we use our database of baboon social behavior (Papio anubis, Gashaka Gumti National Park, Nigeria) to investigate (i) to what extent social networks created from different behaviors overlap, (ii) to what extent individuals occupy similar social positions in these networks and (iii) how sex affects social network position in this population of baboons. We used data on grooming, aggression, displacement, mounting and presenting, which were collected over a 15-month period. We calculated network parameters separately for each behavior. Networks based on displacement, mounting and presenting were very similar to each other, whereas grooming and aggression networks differed both from each other and from mounting, displacement and presenting networks. Overall, individual network positions were strongly affected by sex. Individuals central in one network tended to be central in most other networks as well, whereas other measures such as clustering coefficient were found to vary depending on the behavior analyzed. Thus, our results suggest that a baboon's social environment is best described by a multiplex network based on affiliative, aggressive and sexual behavior. Modern SNA provides a number of useful tools that will help us to better understand animals' social environment. We also discuss potential caveats related to their use.     

A framework for conceptualizing dimensions of social organization in mammals

Mammalian societies represent many different types of social systems. While some aspects of social systems have been extensively studied, there is little consensus on how to conceptualize social organization across species. Here, we present a framework describing eight dimensions of social organization to capture its diversity across mammalian societies. The framework uses simple information that is clearly separated from the three other aspects of social systems: social structure, care system, and mating system. By applying our framework across 208 species of all mammalian taxa, we find a rich multidimensional landscape of social organization. Correlation analysis reveals that the dimensions have relatively high independence, suggesting that social systems are able to evolve different aspects of social behavior without being tied to particular traits. Applying a clustering algorithm allows us to identify the relative importance of key dimensions on patterns of social organization. Finally, mapping mating system onto these clusters shows that social organization represents a distinct aspect of social systems. In the future, this framework will aid reporting on important aspects of natural history in species and facilitate comparative analyses, which ultimately will provide the ability to generate new insights into the primary drivers of social patterns and evolution of sociality.     

Ambiguity in Social Network Data for Presence,Sensitive-Attribute,Degree and Relationship Privacy Protection

Maintaining privacy in network data publishing is a major challenge. This is because known characteristics of individuals can be used to extract new information about them. Recently, researchers have developed privacy methods based on k-anonymity and l-diversity to prevent re-identification or sensitive label disclosure through certain structural information. However, most of these studies have considered only structural information and have been developed for undirected networks. Furthermore, most existing approaches rely on generalization and node clustering so may entail significant information loss as all properties of all members of each group are generalized to the same value. In this paper, we introduce a framework for protecting sensitive attribute, degree (the number of connected entities), and relationships, as well as the presence of individuals in directed social network data whose nodes contain attributes. First, we define a privacy model that specifies privacy requirements for the above private information. Then, we introduce the technique of Ambiguity in Social Network data (ASN) based on anatomy, which specifies how to publish social network data. To employ ASN, individuals are partitioned into groups. Then, ASN publishes exact values of properties of individuals of each group with common group ID in several tables. The lossy join of those tables based on group ID injects uncertainty to reconstruct the original network. We also show how to measure different privacy requirements in ASN. Simulation results on real and synthetic datasets demonstrate that our framework, which protects from four types of private information disclosure, preserves data utility in tabular, topological and spectrum aspects of networks at a satisfactory level.     

前额叶皮层在社交行为中的作用

社交行为对于个体身心健康和社会发展都极其重要。社交行为障碍已成为多种精神类疾病的典型临床表征,对个体的发展有严重不良影响。前额叶皮层作为调节社交行为的关键脑区之一,参与了社交、情绪、决策等高级功能,其内部神经元、神经胶质细胞的活动变化及相互作用对调节社交行为有着重要影响,而且前额叶皮层与其他脑区之间的协作也会影响不同的社会行为。本文回顾了前额叶皮层中神经元、神经胶质细胞以及脑区投射与社交行为关系的最新研究,系统综述了前额叶皮层在社交行为调节中的作用,以期为社交障碍的神经机制和有效诊疗提供参考。     

Network analysis as a tool to understand social development in spider monkeys

The emerging field of network science has demonstrated that an individual's connectedness within their social network has cascading effects to other dimensions of life. Like humans, spider monkeys live in societies with high fission–fusion dynamics, and are remarkably social. Social network analysis (SNA) is a powerful tool for quantifying connections that may vary as a function of initiating or receiving social behaviors, which has been described as shifting social roles. In primatology, the SNA literature is dominated by work in catarrhines, and has yet to be applied to the study of development in a platyrrhine model. Here, SNA was utilized in combination with R-Index social role calculation to characterize social interaction patterns in juvenile and adult Colombian spider monkeys (Ateles fusciceps rufiventris). Connections were examined across five behaviors: embrace, face-embrace, grooming, agonism, and tail-wrapping from 186 hr of observation and four network metrics. Mann–Whitney U tests were utilized to determine differences between adult and juvenile social network patterns for each behavior. Face-embrace emerged as the behavior with different network patterns for adults and juveniles for every network metric. With regard to social role, juveniles were receivers, not initiators, for embrace, face-embrace, and grooming (ps < .05). Network and social role differences are discussed in light of social development and aspects of the different behaviors.     

The regulation of social recognition, social communication and aggression: vasopressin in the social behavior neural network

Neuropeptides in the arginine vasotocin/arginine vasopressin (AVT/AVP) family play a major role in the regulation of social behavior by their actions in the brain. In mammals, AVP is found within a circuit of recriprocally connected limbic structures that form the social behavior neural network. This review examines the role played by AVP within this network in controlling social processes that are critical for the formation and maintenance of social relationships: social recognition, social communication and aggression. Studies in a number of mammalian species indicate that AVP and AVP V1a receptors are ideally suited to regulate the expression of social processes because of their plasticity in response to factors that influence social behavior. The pattern of AVP innervation and V1a receptors across the social behavior neural network may determine the potential range and intensity of social responses that individuals display in different social situations. Although fundamental information on how social behavior is wired in the brain is still lacking, it is clear that different social behaviors can be influenced by the actions of AVP in the same region of the network and that AVP can act within multiple regions of this network to regulate the expression of individual social behaviors. The existing data suggest that AVP can influence social behavior by modulating the interpretation of sensory information, by influencing decision making and by triggering complex motor outputs. This article is part of a Special Issue entitled Oxytocin, Vasopressin, and Social Behavior.     

Interspecific social networks promote information transmission in wild songbirds

Understanding the functional links between social structure and population processes is a central aim of evolutionary ecology. Multiple types of interactions can be represented by networks drawn for the same population, such as kinship, dominance or affiliative networks, but the relative importance of alternative networks in modulating population processes may not be clear. We illustrate this problem, and a solution, by developing a framework for testing the importance of different types of association in facilitating the transmission of information. We apply this framework to experimental data from wild songbirds that form mixed-species flocks, recording the arrival (patch discovery) of individuals to novel foraging sites. We tested whether intraspecific and interspecific social networks predicted the spread of information about novel food sites, and found that both contributed to transmission. The likelihood of acquiring information per unit of connection to knowledgeable individuals increased 22-fold for conspecifics, and 12-fold for heterospecifics. We also found that species varied in how much information they produced, suggesting that some species play a keystone role in winter foraging flocks. More generally, these analyses demonstrate that this method provides a powerful approach, using social networks to quantify the relative transmission rates across different social relationships.     

When to use social information: the advantage of large group size in individual decision making

Correct decision making is crucial for animals to maximize foraging success and minimize predation risk. Group-living animals can make such decisions by using their own personal information or by pooling information with other group members (i.e. social information). Here, we investigate how individuals might best balance their use of personal and social information. We use a simple modelling approach in which individual decisions based upon social information are more likely to be correct when more individuals are involved and their personal information is more accurate. Our model predicts that when the personal information of group members is poor (accurate less than half the time), individuals should avoid pooling information. In contrast, when personal information is reliable (accurate at least half the time), individuals should use personal information less often and social information more often, and this effect should grow stronger in larger groups. One implication of this pattern is that social information allows less well-informed members of large groups to reach a correct decision with the same probability as more well-informed members of small groups. Thus, animals in larger groups may be able to minimize the costs of collecting personal information without impairing their ability to make correct decisions.     

EVOLUTION OF HELPING AND HARMING IN HETEROGENEOUS GROUPS

Social groups are often composed of individuals who differ in many respects. Theoretical studies on the evolution of helping and harming behaviors have largely focused upon genetic differences between individuals. However, nongenetic variation between group members is widespread in natural populations, and may mediate differences in individuals’ social behavior. Here, we develop a framework to study how variation in individual quality mediates the evolution of unconditional and conditional social traits. We investigate the scope for the evolution of social traits that are conditional on the quality of the actor and/or recipients. We find that asymmetries in individual quality can lead to the evolution of plastic traits with different individuals expressing helping and harming traits within the same group. In this context, population viscosity can mediate the evolution of social traits, and local competition can promote both helping and harming behaviors. Furthermore, asymmetries in individual quality can lead to the evolution of competition‐like traits between clonal individuals. Overall, we highlight the importance of asymmetries in individual quality, including differences in reproductive value and the ability to engage in successful social interactions, in mediating the evolution of helping and harming behaviors.     

Exploring the causes and consequences of cooperative behaviour in wild animal populations using a social network approach

Understanding why individuals carry out behaviours that benefit others, especially genetically unrelated others, has been a major undertaking in many fields and particularly in biology. Here, we focus on the cooperation literature from natural populations and present the benefits of a social network approach in terms of how it can help to identify and understand factors that influence the maintenance and spread of cooperation, but are not easily captured when solely considering independent dyadic interactions. We describe how various routes to cooperation can be tested within the social network framework. Applying the social network approach to data from natural populations can help to uncover the evolutionary and ecological pressures that lead to differences in cooperation and other social processes.     

A guide to choosing and implementing reference models for social network analysis

Analysing social networks is challenging. Key features of relational data require the use of non-standard statistical methods such as developing system-specific null, or reference, models that randomize one or more components of the observed data. Here we review a variety of randomization procedures that generate reference models for social network analysis. Reference models provide an expectation for hypothesis testing when analysing network data. We outline the key stages in producing an effective reference model and detail four approaches for generating reference distributions: permutation, resampling, sampling from a distribution, and generative models. We highlight when each type of approach would be appropriate and note potential pitfalls for researchers to avoid. Throughout, we illustrate our points with examples from a simulated social system. Our aim is to provide social network researchers with a deeper understanding of analytical approaches to enhance their confidence when tailoring reference models to specific research questions.     

Characterizing selection in black‐throated blue warblers using a sexual network approach

Our understanding of trait evolution is built upon studies that examine the correlation between traits and fitness, most of which implicitly assume all individuals experience similar selective environments. However, accounting for differences in selective pressures, such as variation in the social environment, can advance our understanding of how selection shapes individual traits and subsequent fitness. In this study, we test whether variation in the social environment affects selection on individual phenotype. We apply a new sexual network framework to quantify each male's social environment as the mean body size of his primary competitors. We test for direct and social selection on male body size using a 10‐year data set on black‐throated blue warblers (Setophaga caerulescens), a territorial species for which body size is hypothesized to mediate competition for mates. We found that direct selection on body size was weak and nonsignificant, as was social selection via the body size of the males' competitors. Analysing both types of selection simultaneously allows us to firmly reject a role for body size in competitive interactions between males and subsequent male fitness in this population. We evaluate the application of the sexual network approach to empirical data and suggest that other phenotypic traits such as song characteristics and plumage may be more relevant than body size for male–male competition in this small passerine bird.     

基于多层次稀疏编码预测蛋白质亚细胞定位

文中提出了一种简单有效的蛋白质亚细胞区间定位预测方法,为进一步了解蛋白质的功能和性质提供理论基础。运用稀疏编码,结合氨基酸组成信息提取蛋白质序列特征,基于不同字典大小对得到的特征进行多层次池化整合,并送入支持向量机进行分类。经Jackknife检验,在数据集ZD98、CH317和Gram1253上的预测成功率分别达到95.9%、93.4%和94.7%。实验证明基于多层次稀疏编码的分类预测算法能显著提高蛋白质亚细胞区间定位的预测精度。     

Social neuroscience of disgust

Disgust can be thought of as an affective system that has evolved to detect signs of pathogens, parasite and toxins as well as to stimulate behaviors that reduce the risk of their acquisition. Disgust incorporates social cognitive mechanisms to regulate exposure to and, or anticipate and avoid exposure to pathogens and toxins. Social cognition entails the acquisition of social information about others (ie, social recognition) and from others (ie, social learning). This involves recognizing and assessing other individuals and the pathogen/parasite/contamination/toxin threat they pose and deciding about when and how to interact with and, or avoid them. Social cognition provides a frame‐work for examining the expression of disgust and the associated neurobiological mechanisms. Here, we briefly consider the relations between social cognition and pathogen/parasite/toxin avoidance behaviors. We briefly discuss aspects of: (1) the odor mediated social recognition of actual and potentially infected individuals and the impact of parasite/pathogen threat on disgust mate and social partner choice; (2) the roles of “out‐groups” (strangers, unfamiliar individuals) and “in‐groups” (familiar individuals) in the expression of disgust and pathogen avoidance behaviors; (3) individual and social learning of disgust and empathy for disgust; (4) toxin elicited disgust and anticipatory disgust; (5) the neurobiological mechanisms, and in particular the roles of the nonapeptide, oxytocin and estrogenic mechanism associated with social cognition and the expression of disgust. These findings on the social neuroscience of disgust have a direct bearing on our understanding of the roles of disgust in shaping human and nonhuman social behavior.     

Linking social identity,risk perception,and behavioral psychology to understand predator management by livestock producers

Human behaviors can determine the success of efforts to restore predators to ecosystems. While behaviors such as lethal predator control may impede predator restoration, other land management practices can facilitate coexistence between predators and humans. Socio‐psychological theories provide useful tools for understanding and improving these human behaviors. We explore three frameworks to understand what shapes Australian livestock graziers' behaviors with regards to management of the threat that dingoes pose to livestock. These frameworks are the theory of reasoned action (incorporating values and beliefs about dingoes), the social identity approach, and perception of risk. We distributed a survey to Australian graziers by mail and online (n = 138) which allowed recording of information on these three frameworks and their engagement in lethal dingo control. Among the respondents, we found that all three frameworks were linked with lethal dingo control when assessed individually, but when combined in a hierarchical regression, only social identity (specifically, identifying as an “environmentalist” or “pest controller”) was significant in predicting behavior. This result reveals the strength of social norms and normative beliefs over perceived risk in shaping behavior. As such, social identity is a useful metric for predicting and understanding environmental management behavior. Determining what these social identities mean in a given context is important for identifying how to implement behavior change to promote evidence‐based management that facilitates restoration of wildlife such as predators to landscapes where conflict with humans occurs.