Constructing, conducting and interpreting animal social network analysis

Social Interactions in Two Groups of Zoo-Housed Adult Female Asian Elephants (Elephas maximus) that Differ in Relatedness

Opportunities for positive social interaction are important in captive animals, and social interactions can be used as a welfare indicator. Wild elephants live in related multigenerational herds; however, in captivity they are often managed in less related groups, which could impact the quality of their social interactions, and thus their welfare. Here, we used a limited social network analysis to investigate the social interactions in two groups of four female captive Asian elephants, one of which contained individuals that were all related to one another, whilst the other was a mix of related and unrelated individuals. Data on pairwise social interactions was collected from eight days of video footage using an all-occurrence sampling technique. More affiliative, and fewer agonistic interactions were observed in the related elephant group. Additionally, non-contact displacement was observed at a higher frequency in the related elephant group, which we theorise represents an established functioning hierarchy, avoiding the need for overt aggression over resources. Although kinship is not likely to be the only factor affecting captive elephant social behaviour, these findings support the recommendation that for optimal welfare, elephants should be managed in multigenerational family herds. Evaluations of social interactions such as those conducted here would have wider applicability for aiding the management of any captive social species to identify when groups might be incompatible.

A periodic Markov model to formalize animal migration on a network

Regular, long-distance migrations of thousands of animal species have consequences for the ecosystems that they visit, modifying trophic interactions and transporting many non-pathogenic and pathogenic organisms. The spatial structure and dynamic properties of animal migrations and population flyways largely determine those trophic and transport effects, but are yet poorly studied. As a basis, we propose a periodic Markov model on the spatial migration network of breeding, stopover and wintering sites to formally describe the process of animal migration on the population level. From seasonally changing transition rates we derived stable, seasonal densities of animals at the network nodes. We parametrized the model with high-quality GPS and satellite telemetry tracks of white storks (Ciconia ciconia) and greater white-fronted geese (Anser a. albifrons). Topological and network flow properties of the two derived networks conform to migration properties like seasonally changing connectivity and shared, directed movement. Thus, the model realistically describes the migration movement of complete populations and can become an important tool to study the effects of climate and habitat change and pathogen spread on migratory animals. Furthermore, the property of periodically changing transition rates makes it a new type of complex model and we need to understand its dynamic properties.

Exploratory behavior is linked to stress physiology and social network centrality in free-living house finches (Haemorhous mexicanus)

Animal personality has been linked to individual variation in both stress physiology and social behaviors, but few studies have simultaneously examined covariation between personality traits, stress hormone levels, and behaviors in free-living animals. We investigated relationships between exploratory behavior (one aspect of animal personality), stress physiology, and social and foraging behaviors in wild house finches (Haemorhous mexicanus). We conducted novel environment assays after collecting samples of baseline and stress-induced plasma corticosterone concentrations from a subset of house finches. We then fitted individuals with Passive Integrated Transponder tags and monitored feeder use and social interactions at radio-frequency identification equipped bird feeders. First, we found that individuals with higher baseline corticosterone concentrations exhibit more exploratory behaviors in a novel environment. Second, more exploratory individuals interacted with more unique conspecifics in the wild, though this result was stronger for female than for male house finches. Third, individuals that were quick to begin exploring interacted more frequently with conspecifics than slow-exploring individuals. Finally, exploratory behaviors were unrelated to foraging behaviors, including the amount of time spent on bird feeders, a behavior previously shown to be predictive of acquiring a bacterial disease that causes annual epidemics in house finches. Overall, our results indicate that individual differences in exploratory behavior are linked to variation in both stress physiology and social network traits in free-living house finches. Such covariation has important implications for house finch ecology, as both traits can contribute to fitness in the wild.

Inferring influence and leadership in moving animal groups

Collective decision-making is a daily occurrence in the lives of many group-living animals, and can have critical consequences for the fitness of individuals. Understanding how decisions are reached, including who has influence and the mechanisms by which information and preferences are integrated, has posed a fundamental challenge. Here, we provide a methodological framework for studying influence and leadership in groups. We propose that individuals have influence if their actions result in some behavioural change among their group-mates, and are leaders if they consistently influence others. We highlight three components of influence (influence instances, total influence and consistency of influence), which can be assessed at two levels (individual-to-individual and individual-to-group). We then review different methods, ranging from individual positioning within groups to information-theoretic approaches, by which influence has been operationally defined in empirical studies, as well as how such observations can be aggregated to give insight into the underlying decision-making process. We focus on the domain of collective movement, with a particular emphasis on methods that have recently been, or are being, developed to take advantage of simultaneous tracking data. We aim to provide a resource bringing together methodological tools currently available for studying leadership in moving animal groups, as well as to discuss the limitations of current methodologies and suggest productive avenues for future research.This article is part of the theme issue 'Collective movement ecology'.

The conceptual foundations of network-based diffusion analysis: choosing networks and interpreting results

Network-based diffusion analysis (NBDA) is a statistical technique for detecting the social transmission of behavioural innovations in groups of animals, including humans. The strength of social transmission is inferred from the extent to which the diffusion (spread) of the innovation follows a social network. NBDA can have two goals: (a) to establish whether social transmission is occurring and how strong its effects are; and/or (b) to establish the typical pathways of information transfer. The technique has been used in a range of taxa, including primates, cetaceans, birds and fish, using a range of different types of network. Here I investigate the conceptual underpinnings of NBDA, in order to establish the meaning of results using different networks. I develop a model of the social transmission process where each individual observation of the target behaviour affects the rate at which the observer learns that behaviour. I then establish how NBDAs using different networks relate to this underlying process, and thus how we can interpret the results of each. My analysis shows that a different network or networks are appropriate depending on the specific goal or goals of the study, and establishes how the parameter estimates yielded from an NBDA can be interpreted for different networks.This article is part of the themed issue 'Process and pattern in innovations from cells to societies'.

Social thermoregulation as a potential mechanism linking sociality and fitness: Barbary macaques with more social partners form larger huddles

Individuals with more or stronger social bonds experience enhanced survival and reproduction in various species, though the mechanisms mediating these effects are unclear. Social thermoregulation is a common behaviour across many species which reduces cold stress exposure, body heat loss, and homeostatic energy costs, allowing greater energetic investment in growth, reproduction, and survival, with larger aggregations providing greater benefits. If more social individuals form larger thermoregulation aggregations due to having more potential partners, this would provide a direct link between sociality and fitness. We conducted the first test of this hypothesis by studying social relationships and winter sleeping huddles in wild Barbary macaques (Macaca sylvanus), wherein individuals with more social partners experience greater probability of winter survival. Precipitation and low temperature increased huddle sizes, supporting previous research that huddle size influences thermoregulation and energetics. Huddling relationships were predicted by social (grooming) relationships. Individuals with more social partners therefore formed larger huddles, suggesting reduced energy expenditure and exposure to environmental stressors than less social individuals, potentially explaining how sociality affects survival in this population. This is the first evidence that social thermoregulation may be a direct proximate mechanism by which increased sociality enhances fitness, which may be widely applicable across taxa.

Concede or clash? Solitary sharks competing for food assess rivals to decide

To adapt to their environment, organisms can either directly interact with their surroundings or use social information (i.e. information provided by neighbouring individuals). Social information relates to the external features of surrounding peers, and little is known about its use by solitary species. Here, we investigated the use of social cues in a solitary marine predator by creating artificial aggregations of free-ranging sicklefin lemon sharks (Negaprion acutidens). Using a novel monitoring protocol, we analysed both dominance interactions and tolerance associations between sharks competing for food in relation with the number, the morphology and the behaviour of rivals. Sharks produced more agonistic displays and spent more time around the bait as competitors were more abundant. Moreover, the morphological attributes of competitors had very limited influence on the structure of shark social interactions. Instead, sharks appeared to establish tolerance relationships with competitors according to their individual behaviour. Furthermore, the more two sharks were observed together at a given study site, the fewer agonistic interactions they exchanged. We discuss these findings as evidence of the use of social cues in a non-gregarious predatory species and suggest directions for future research.

Going through the motions: incorporating movement analyses into disease research

Though epidemiology dates back to the 1700s, most mathematical representations of epidemics still use transmission rates averaged at the population scale, especially for wildlife diseases. In simplifying the contact process, we ignore the heterogeneities in host movements that complicate the real world, and overlook their impact on spatiotemporal patterns of disease burden. Movement ecology offers a set of tools that help unpack the transmission process, letting researchers more accurately model how animals within a population interact and spread pathogens. Analytical techniques from this growing field can also help expose the reverse process: how infection impacts movement behaviours, and therefore other ecological processes like feeding, reproduction, and dispersal. Here, we synthesise the contributions of movement ecology in disease research, with a particular focus on studies that have successfully used movement-based methods to quantify individual heterogeneity in exposure and transmission risk. Throughout, we highlight the rapid growth of both disease and movement ecology and comment on promising but unexplored avenues for research at their overlap. Ultimately, we suggest, including movement empowers ecologists to pose new questions, expanding our understanding of host-pathogen dynamics and improving our predictive capacity for wildlife and even human diseases.

Social network and dominance hierarchy analyses at Chimpanzee Sanctuary Northwest

Different aspects of sociality bear considerable weight on the individual- and group-level welfare of captive nonhuman primates. Social Network Analysis (SNA) is a useful tool for gaining a holistic understanding of the dynamic social relationships of captive primate groups. Gaining a greater understanding of captive chimpanzees through investigations of centrality, preferred and avoided relationships, dominance hierarchy, and social network diagrams can be useful in advising current management practices in sanctuaries and other captive settings. In this study, we investigated the dyadic social relationships, group-level social networks, and dominance hierarchy of seven chimpanzees (Pan troglodytes) at Chimpanzee Sanctuary Northwest. We used focal-animal and instantaneous scan sampling to collect 106.75 total hours of associative, affiliative, and agonistic data from June to September 2016. We analyzed our data using SOCPROG to derive dominance hierarchies and network statistics, and we diagrammed the group's social networks in NetDraw. Three individuals were most central in the grooming network, while two others had little connection. Through agonistic networks, we found that group members reciprocally exhibited agonism, and the group's dominance hierarchy was statistically non-linear. One chimpanzee emerged as the most dominant through agonism but was least connected to other group members across affiliative networks. Our results indicate that the conventional methods used to calculate individuals' dominance rank may be inadequate to wholly depict a group's social relationships in captive sanctuary populations. Our results have an applied component that can aid sanctuary staff in a variety of ways to best ensure the improvement of group welfare.

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.

Disease implications of animal social network structure: A synthesis across social systems

The disease costs of sociality have largely been understood through the link between group size and transmission. However, infectious disease spread is driven primarily by the social organization of interactions in a group and not its size. We used statistical models to review the social network organization of 47 species, including mammals, birds, reptiles, fish and insects by categorizing each species into one of three social systems, relatively solitary, gregarious and socially hierarchical. Additionally, using computational experiments of infection spread, we determined the disease costs of each social system. We find that relatively solitary species have large variation in number of social partners, that socially hierarchical species are the least clustered in their interactions, and that social networks of gregarious species tend to be the most fragmented. However, these structural differences are primarily driven by weak connections, which suggest that different social systems have evolved unique strategies to organize weak ties. Our synthetic disease experiments reveal that social network organization can mitigate the disease costs of group living for socially hierarchical species when the pathogen is highly transmissible. In contrast, highly transmissible pathogens cause frequent and prolonged epidemic outbreaks in gregarious species. We evaluate the implications of network organization across social systems despite methodological challenges, and our findings offer new perspective on the debate about the disease costs of group living. Additionally, our study demonstrates the potential of meta-analytic methods in social network analysis to test ecological and evolutionary hypotheses on cooperation, group living, communication and resilience to extrinsic pressures.

Social network community structure and the contact-mediated sharing of commensal E. coli among captive rhesus macaques (Macaca mulatta)

In group-living animals, heterogeneity in individuals' social connections may mediate the sharing of microbial infectious agents. In this regard, the genetic relatedness of individuals' commensal gut bacterium Escherichia coli may be ideal to assess the potential for pathogen transmission through animal social networks. Here we use microbial phylogenetics and population genetics approaches, as well as host social network reconstruction, to assess evidence for the contact-mediated sharing of E. coli among three groups of captively housed rhesus macaques (Macaca mulatta), at multiple organizational scales. For each group, behavioral data on grooming, huddling, and aggressive interactions collected for a six-week period were used to reconstruct social network communities via the Data Cloud Geometry (DCG) clustering algorithm. Further, an E. coli isolate was biochemically confirmed and genotypically fingerprinted from fecal swabs collected from each macaque. Population genetics approaches revealed that Group Membership, in comparison to intrinsic attributes like age, sex, and/or matriline membership of individuals, accounted for the highest proportion of variance in E. coli genotypic similarity. Social network approaches revealed that such sharing was evident at the community-level rather than the dyadic level. Specifically, although we found no links between dyadic E. coli similarity and social contact frequencies, similarity was significantly greater among macaques within the same social network communities compared to those across different communities. Moreover, tests for one of our study-groups confirmed that E. coli isolated from macaque rectal swabs were more genotypically similar to each other than they were to isolates from environmentally deposited feces. In summary, our results suggest that among frequently interacting, spatially constrained macaques with complex social relationships, microbial sharing via fecal-oral, social contact-mediated routes may depend on both individuals' direct connections and on secondary network pathways that define community structure. They lend support to the hypothesis that social network communities may act as bottlenecks to contain the spread of infectious agents, thereby encouraging disease control strategies to focus on multiple organizational scales. Future directions includeincreasing microbial sampling effort per individual to better-detect dyadic transmission events, and assessments of the co-evolutionary links between sociality, infectious agent risk, and host immune function.

Understanding Tail-Biting in Pigs through Social Network Analysis

The objective of this study was to investigate the association between social structure and incidence of tail-biting in pigs. Pigs (n = 144, initial weight = 7.2 ± 1.57 kg, 4 weeks of age) were grouped based on their litter origin: littermates, non-littermates, and half-group of littermates. Six pens (8 pigs/pen) of each litter origin were studied for 6 weeks. Incidence of tail injury and growth performance were monitored. Behavior of pigs was video recorded for 6 h at 6 and 8 weeks of age. Video recordings were scanned at 10 min intervals to register pigs that were lying together (1) or not (0) in binary matrices. Half weight association index was used for social network construction. Social network analysis was performed using the UCINET software. Littermates had lower network density (0.119 vs. 0.174; p < 0.05), more absent social ties (20 vs. 12; p < 0.05), and fewer weak social ties (6 vs. 14, p < 0.05) than non-littermates, indicating that littermates might be less socially connected. Fifteen percent of littermates were identified as victimized pigs by tail-biting, and no victimized pigs were observed in other treatment groups. These results suggest that littermates might be less socially connected among themselves which may predispose them to development of tail-biting.

Quantifying direct and indirect contacts for the potential transmission of infection between species using a multilayer contact network

Detecting opportunities for between-species transmission of pathogens can be challenging, particularly if rare behaviours or environmental transmission are involved. We present a multilayer network framework to quantify transmission potential in multi-host systems, incorporating environmental transmission, by using empirical data on direct and indirect contacts between European badgers Meles meles and domestic cattle. We identify that indirect contacts via the environment at badger latrines on pasture are likely to be important for transmission within badger populations and between badgers and cattle. We also find a positive correlation between the role of individual badgers within the badger social network, and their role in the overall badger-cattle-environment network, suggesting that the same behavioural traits contribute to the role of individual badgers in within- and between-species transmission. These findings have implications for disease management interventions in this system, and our novel network approach can provide general insights into transmission in other multi-host disease systems.

Structure of sexual networks determines the operation of sexual selection

Sexual selection is a fundamental evolutionary process but remains debated, particularly in the complexity of polyandrous populations where females mate with multiple males. This lack of resolution is partly because studies have largely ignored the structure of the sexual network, that is, the pattern of mate sharing. Here, we quantify what we call mating assortment with network analysis to specify explicitly the indirect as well as direct relationships between partners. We first review empirical studies, showing that mating assortment varies considerably in nature, due largely to basic properties of the sexual network (size and density) and partly to nonrandom patterns of mate sharing. We then use simulations to show how variation in mating assortment interacts with population-level polyandry to determine the strength of sexual selection on males. Controlling for average polyandry, positive mating assortment, arising when more polygynous males tend to mate with more polyandrous females, drastically decreases the intensity of precopulatory sexual selection on male mating success (Bateman gradient) and the covariance between male mating success and postcopulatory paternity share. Average polyandry independently weakened some measures of sexual selection and crucially also impacted sexual selection indirectly by constraining mating assortment through the saturation of the mating network. Mating assortment therefore represents a key-albeit overlooked-modulator of the strength of sexual selection. Our results show that jointly considering sexual network structure and average polyandry more precisely describes the strength of sexual selection.

Learning and robustness to catch-and-release fishing in a shark social network

Individuals can play different roles in maintaining connectivity and social cohesion in animal populations and thereby influence population robustness to perturbations. We performed a social network analysis in a reef shark population to assess the vulnerability of the global network to node removal under different scenarios. We found that the network was generally robust to the removal of nodes with high centrality. The network appeared also highly robust to experimental fishing. Individual shark catchability decreased as a function of experience, as revealed by comparing capture frequency and site presence. Altogether, these features suggest that individuals learnt to avoid capture, which ultimately increased network robustness to experimental catch-and-release. Our results also suggest that some caution must be taken when using capture-recapture models often used to assess population size as assumptions (such as equal probabilities of capture and recapture) may be violated by individual learning to escape recapture.

Sociospatial structure explains marked variation in brucellosis seroprevalence in an Alpine ibex population

In a context of (re)emerging infectious diseases with wildlife reservoirs, understanding how animal ecology shapes epidemiology is a key issue, particularly in wild ungulates that share pathogens with domestic herbivores and have similar food requirements. For the first time in Europe, brucellosis (Brucella melitensis), a virulent zoonosis, persisted in an Alpine ibex (Capra ibex) population and was transmitted to cattle and humans. To better understand disease dynamics, we investigated the relationships between the spatial ecology of ibex and the epidemiology of brucellosis. Combining home range overlap between 37 GPS-collared individuals and visual observations of 148 visually-marked individuals monitored during the 2013-2016 period, we showed that females were spatially segregated in at least 4 units all year round, whereas males were more prone to move between female units, in particular during the rutting period. In addition to ibex age, the spatial structure in females largely contributed to variation in seroprevalence in the whole population. These results suggest that non-sexual routes are the most likely pathways of intraspecific transmission, crucial information for management. Accounting for wildlife spatial ecology was hence decisive in improving our ability to better understand this health challenge involving a wildlife reservoir.

The influence of phylogeny, social style, and sociodemographic factors on macaque social network structure

Among nonhuman primates, the evolutionary underpinnings of variation in social structure remain debated, with both ancestral relationships and adaptation to current conditions hypothesized to play determining roles. Here we assess whether interspecific variation in higher-order aspects of female macaque (genus: Macaca) dominance and grooming social structure show phylogenetic signals, that is, greater similarity among more closely-related species. We use a social network approach to describe higher-order characteristics of social structure, based on both direct interactions and secondary pathways that connect group members. We also ask whether network traits covary with each other, with species-typical social style grades, and/or with sociodemographic characteristics, specifically group size, sex-ratio, and current living condition (captive vs. free-living). We assembled 34-38 datasets of female-female dyadic aggression and allogrooming among captive and free-living macaques representing 10 species. We calculated dominance (transitivity, certainty), and grooming (centrality coefficient, Newman's modularity, clustering coefficient) network traits as aspects of social structure. Computations of K statistics and randomization tests on multiple phylogenies revealed moderate-strong phylogenetic signals in dominance traits, but moderate-weak signals in grooming traits. GLMMs showed that grooming traits did not covary with dominance traits and/or social style grade. Rather, modularity and clustering coefficient, but not centrality coefficient, were strongly predicted by group size and current living condition. Specifically, larger groups showed more modular networks with sparsely-connected clusters than smaller groups. Further, this effect was independent of variation in living condition, and/or sampling effort. In summary, our results reveal that female dominance networks were more phylogenetically conserved across macaque species than grooming networks, which were more labile to sociodemographic factors. Such findings narrow down the processes that influence interspecific variation in two core aspects of macaque social structure. Future directions should include using phylogeographic approaches, and addressing challenges in examining the effects of socioecological factors on primate social structure.

Inter-group associations in Mongolian gerbils: Quantitative evidence from social network analysis

Animals often interact non-randomly with conspecifics, and association preferences can differ across life-history stages to maximize individuals' fitness. Mongolian gerbils (Meriones unguiculatus) are a social rodent that live in highly seasonal habitats and display seasonal fluctuations in population density, growth rate and the size of overlapped home ranges. Nevertheless, whether gerbils modify their social relationships at different life-history stages remains unknown. Here, we used social network analysis to examine whether social associations differ between the sexes and between life-history stages in a wild population of Mongolian gerbils. We quantified social attributes at both group level (assortativity) and individual level (social differentiation and degree, closeness and betweenness centrality); these attributes reflect individuals' social preferences and their potential influence on others in the network. We found that both male and female gerbils established fewer inter-group social connections during the food-hoarding season than during the breeding season, revealing constraints on sociality. Similarly, during the food-hoarding season, degree centrality and social differentiation increased significantly whereas closeness and betweenness centrality decreased significantly. Together, these results suggest that gerbils have relatively more partners and preferred associations and decreased influence over others in the network during the food-hoarding season. In addition, we found no significant difference in any of the social attribute between males and females, but there was a significant interaction effect between sex and season on degree, closeness and betweenness centrality. Our results demonstrate that Mongolian gerbils adjust their association strategies to adapt to the changes of life history. Such adjustments may balance the costs/benefits associated with survival and reproduction.

The dynamics of transmission and the dynamics of networks

A toy example depicted here highlighting the results of a study in this issue of the Journal of Animal Ecology that investigates the impact of network dynamics on potential disease outbreaks. Infections (stars) that spread by contact only (left) reduce the predicted outbreak size compared to situations where individuals can become infected by moving through areas that previously contained infected individuals (right). This is potentially important in species where individuals, or in this case groups, have overlapping ranges (as depicted on the top right). Incorporating network dynamics that maintain information about the ordering of contacts (central blocks; including the ordering of spatial overlap as noted by the arrows that highlight the blue group arriving after the red group in top-right of the figure) is important for capturing how a disease might not have the opportunity to spread to all individuals. By contrast, a static or 'average' network (lower blocks) does not capture any of these dynamics. Interestingly, although static networks generally predict larger outbreak sizes, the authors find that in cases when transmission probability is low, this prediction can switch as a result of changes in the estimated intensity of contacts among individuals. [Colour figure can be viewed at wileyonlinelibrary.com]. Springer, A., Kappeler, P.M. & Nunn, C.L. (2017) Dynamic vs. static social networks in models of parasite transmission: Predicting Cryptosporidium spread in wild lemurs. Journal of Animal Ecology, 86, 419-433. The spread of disease or information through networks can be affected by several factors. Whether and how these factors are accounted for can fundamentally change the predicted impact of a spreading epidemic. Springer, Kappeler & Nunn () investigate the role of different modes of transmission and network dynamics on the predicted size of a disease outbreak across several groups of Verreaux's sifakas, a group-living species of lemur. While some factors, such as seasonality, led to consistent differences in the structure of social networks, using dynamic vs. static representations of networks generated differences in the predicted outbreak size of an emergent disease. These findings highlight some of the challenges associated with studying disease dynamics in animal populations, and the importance of continuing efforts to develop the network tools needed to study disease spread.

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.

Assortment and the analysis of natural selection on social traits

A central problem in evolutionary biology is to determine whether and how social interactions contribute to natural selection. A key method for phenotypic data is social selection analysis, in which fitness effects from social partners contribute to selection only when there is a correlation between the traits of individuals and their social partners (nonrandom phenotypic assortment). However, there are inconsistencies in the use of social selection that center around the measurement of phenotypic assortment. Here, we use data analysis and simulations to resolve these inconsistencies, showing that: (i) not all measures of assortment are suitable for social selection analysis; and (ii) the interpretation of assortment, and how to detect nonrandom assortment, will depend on the scale at which it is measured. We discuss links to kin selection theory and provide a practical guide for the social selection approach.

Porous Chambers, Echoes of Valence and Stereotypes

Selective exposure to one-sided news coverage, especially of controversial geopolitical events, may contribute to growing social polarization. Existing research on “echo chambers”—fragmented information environments that amplify homogeneous perspectives—focuses on the degree to which individuals and social media platforms shape informational segregation. Here, we explore whether news organizations directly contribute to echo chambers through the hyperlinks they embed in online articles. Using network and text analysis, we examined coverage of the 2014 shooting of Michael Brown in Ferguson, MO, and found that online news media exhibited weak community structure and high connectivity across news outlets. However, analyses also indicated that media sources were more likely to link to coverage that was similar to their own in terms of emotional valence and stereotype-relevant aspects of the events. While hyperlinking to diverse news sources may ameliorate fragmented information environments, selectively linking to similar coverage may contribute to growing polarization.