The problem and promise of scale in multilayer animal social networks

Scale remains a foundational concept in ecology.Spatial scale,for instance,has become a central consideration in the way we understand landscape ecology and animal space use.Meanwhile,scale-dependent social processes can range from fine scale interactions to co-occurrence and overlapping home ranges.Furthermore,sociality can vary within and across seasons.Multilayer networks promise the explicit integration of the social,spatial,and temporal contexts.Given the complex interplay of sociality and animal space use in heterogeneous landscapes,there remains an important gap in our understanding of the influence of scale on animal social networks.Using an empirical case study,we discuss ways of considering social,spatial,and temporal scale in the context of multilayer caribou social networks.Effective integration of social and spatial processes,including biologically meaningful scales,within the context of animal social networks is an emerging area of research.We incorporate perspectives that link the social environment to spatial processes across scales in a multilayer context.     

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.     

Consistent sociality but flexible social associations across temporal and spatial foraging contexts in a colonial breeder

When the consequences of sociality differ depending on the state of individual animals and the experienced environment, individuals may benefit from altering their social behaviours in a context‐dependent manner. Thus, to fully address the hypotheses about the role of social associations it is imperative to consider the multidimensional nature of sociality by explicitly examining social associations across multiple scales and contexts. We simultaneously recorded > 8000 associations from 85% of breeding individuals from a colony of Australasian gannets (Morus serrator) over a 2‐week period, and examined gregariousness across four foraging states using multilayer social network analysis. We found that social associations varied in a context‐dependent manner, highlighting that social associations are most prevalent during foraging (local enhancement) and in regions expected to provide clustered resources. We also provide evidence of individual consistency in gregariousness, but flexibility in social associates, demonstrating that individuals can adjust their social behaviours to match experienced conditions.     

Primate sociality in evolutionary context

Much work has been done to further our understanding of the mechanisms that underlie the diversity of primate social organizations, but none has addressed the limits to that diversity or the question of what causes species to either form or not form social networks. The fact that all living primates typically live in social networks makes it highly likely that the last common ancestor of living primates already lived in social networks, and that sociality formed an integral part of the adaptive nature of primate origins. A characterization of primate sociality within the wider mammalian context is therefore essential to further our understanding of the adaptive nature of primate origins. Here we determine correlates of sociality and nonsociality in rodents as a model to infer causes of sociality in primates. We found sociality to be most strongly associated with large-bodied arboreal species that include a significant portion of fruit in their diet. Fruits and other plant products, such as flowers, seeds, and young leaves, are patchily distributed in time and space and are therefore difficult to find. These food resources are, however, predictable and dependable when their location is known. Hence, membership in a social unit can maximize food exploitation if information on feeding sites is shared. Whether sociality evolved in the primate stem lineage or whether it was already present earlier in the evolution of Euarchontoglires remains uncertain, although tentative evidence points to the former scenario. In either case, frugivory is likely to have played an important role in maintaining the presence of a social lifestyle throughout primate evolution.     

Why understanding multiplex social network structuring processes will help us better understand the evolution of human behavior

Social scientists have long appreciated that relationships between individuals cannot be described from observing a single domain, and that the structure across domains of interaction can have important effects on outcomes of interest (e.g., cooperation; Durkheim, 1893). One debate explicitly about this surrounds food sharing. Some argue that failing to find reciprocal food sharing means that some process other than reciprocity must be occurring, whereas others argue for models that allow reciprocity to span domains in the form of trade (Kaplan and Hill, 1985.). Multilayer networks, high‐dimensional networks that allow us to consider multiple sets of relationships at the same time, are ubiquitous and have consequences, so processes giving rise to them are important social phenomena. The analysis of multi‐dimensional social networks has recently garnered the attention of the network science community (Kivelä et al., 2014). Recent models of these processes show how ignoring layer interdependencies can lead one to miss why a layer formed the way it did, and/or draw erroneous conclusions (Górski et al., 2018). Understanding the structuring processes that underlie multiplex networks will help understand increasingly rich data sets, giving more accurate and complete pictures of social interactions.     

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.     

A framework to evaluate whether to pool or separate behaviors in a multilayer network

A multilayer network approach combines different network layers,which are connected by interlayer edges,to create a single mathematical object.These networks can contain a variety of information types and represent different aspects of a system.However,the process for selecting which information to include is not always straightforward.Using data on 2 agonistic behaviors in a captive population of monk parakeets(Myiopsitta monachus),we developed a framework for investigating how pooling or splitting behaviors at the scale of dyadic relationships(between 2 individuals)affects individual-and group-level social properties.We designed 2 reference models to test whether randomizing the number of interactions across behavior types results in similar structural patterns as the observed data.Although the behaviors were correlated,the first reference model suggests that the 2 behaviors convey different information about some social properties and should therefore not be pooled.However,once we controlled for data sparsity,we found that the observed measures corresponded with those from the second reference model.Hence,our initial result may have been due to the unequal frequencies of each behavior.Overall,our findings support pooling the 2 behaviors.Awareness of how selected measurements can be affected by data properties is warranted,but nonetheless our framework disentangles these efforts and as a result can be used for myriad types of behaviors and questions.This framework will help researchers make informed and data-driven decisions about which behaviors to pool or separate,prior to using the data in subsequent multilayer network analyses.     

The complex structure of hunter-gatherer social networks

In nature, many different types of complex system form hierarchical, self-similar or fractal-like structures that have evolved to maximize internal efficiency. In this paper, we ask whether hunter-gatherer societies show similar structural properties. We use fractal network theory to analyse the statistical structure of 1189 social groups in 339 hunter-gatherer societies from a published compilation of ethnographies. We show that population structure is indeed self-similar or fractal-like with the number of individuals or groups belonging to each successively higher level of organization exhibiting a constant ratio close to 4. Further, despite the wide ecological, cultural and historical diversity of hunter-gatherer societies, this remarkable self-similarity holds both within and across cultures and continents. We show that the branching ratio is related to density-dependent reproduction in complex environments and hypothesize that the general pattern of hierarchical organization reflects the self-similar properties of the networks and the underlying cohesive and disruptive forces that govern the flow of material resources, genes and non-genetic information within and between social groups. Our results offer insight into the energetics of human sociality and suggest that human social networks self-organize in response to similar optimization principles found behind the formation of many complex systems in nature.     

Geographic patterns in the distribution of social systems in terrestrial arthropods

The role of ecology in the evolution and maintenance of arthropod sociality has received increasing research attention in recent years. In some organisms, such as halictine bees, polistine wasps, and social spiders, researchers are investigating the environmental factors that may contribute to high levels of variation in the degree of sociality exhibited both among and within species. Within lineages that include only eusocial members, such as ants and termites, studies focus more on identifying extrinsic factors that may contribute to the dramatic variation in colony size, number of queens, and division of labour that is evident across these species. In this review, I propose a comparative approach that seeks to identify environmental factors that may have a common influence across such divergent social arthropod groups. I suggest that seeking common biogeographic patterns in the distribution of social systems or key social traits may help us to identify ecological factors that play a common role in shaping the evolution of sociality across different organisms. I first review previous studies of social gradients that form along latitudinal and altitudinal axes. Within families and within species, many organisms show an increasing degree of sociality at lower latitudes and altitudes. In a smaller number of cases, organisms form larger groups or found nests cooperatively at higher latitudes and altitudes. I then describe several environmental factors that vary consistently along such gradients, including climate variables and abundance of predators, and outline their proposed role in the social systems of terrestrial arthropods. Finally, I map distributions of a social trait against several climatic factors in five case studies to demonstrate how future comparative studies could inform empirical research.     

Community Structures in Bipartite Networks: A Dual-Projection Approach

Identifying communities or clusters in networked systems has received much attention across the physical and social sciences. Most of this work focuses on single layer or one-mode networks, including social networks between people or hyperlinks between websites. Multilayer or multi-mode networks, such as affiliation networks linking people to organizations, receive much less attention in this literature. Common strategies for discovering the community structure of multi-mode networks identify the communities of each mode simultaneously. Here I show that this combined approach is ineffective at discovering community structures when there are an unequal number of communities between the modes of a multi-mode network. I propose a dual-projection alternative for detecting communities in multi-mode networks that overcomes this shortcoming. The evaluation of synthetic networks with known community structures reveals that the dual-projection approach outperforms the combined approach when there are a different number of communities in the various modes. At the same time, results show that the dual-projection approach is as effective as the combined strategy when the number of communities is the same between the modes.     

The adaptive value of sociality in mammalian groups

According to behavioural ecology theory, sociality evolves when the net benefits of close association with conspecifics exceed the costs. The nature and relative magnitude of the benefits and costs of sociality are expected to vary across species and habitats. When sociality is favoured, animals may form groups that range from small pair-bonded units to huge aggregations. The size and composition of social groups have diverse effects on morphology and behaviour, ranging from the extent of sexual dimorphism to brain size, and the structure of social relationships. This general argument implies that sociality has fitness consequences for individuals. However, for most mammalian species, especially long-lived animals like primates, there are sizable gaps in the chain of evidence that links sociality and social bonds to fitness outcomes. These gaps reflect the difficulty of quantifying the cumulative effects of behavioural interactions on fitness and the lack of information about the nature of social relationships among individuals in most taxa. Here, I review what is known about the reproductive consequences of sociality for mammals.     

Coevolutionary cycling of host sociality and pathogen virulence in contact networks

Infectious diseases may place strong selection on the social organization of animals. Conversely, the structure of social systems can influence the evolutionary trajectories of pathogens. While much attention has focused on the evolution of host sociality or pathogen virulence separately, few studies have looked at their coevolution. Here we use an agent-based simulation to explore host-pathogen coevolution in social contact networks. Our results indicate that under certain conditions, both host sociality and pathogen virulence exhibit continuous cycling. The way pathogens move through the network (e.g., their interhost transmission and probability of superinfection) and the structure of the network can influence the existence and form of cycling.     

Communicative roots of complex sociality and cognition

Mammals living in more complex social groups typically have large brains for their body size and many researchers have proposed that the primary driver of the increase in brain size through primate and hominin evolution was the selection pressures associated with sociality. Many mammals, and especially primates, use flexible signals that show a high degree of voluntary control and these signals may play an important role in forming and maintaining social relationships between group members. However, the specific role that cognitive skills play in this complex communication, and how in turn this relates to sociality, is still unclear. The hypothesis for the communicative roots of complex sociality and cognition posits that cognitive demands behind the communication needed to form and maintain bonded social relationships in complex social settings drives the link between brain size and sociality. We review the evidence in support of this hypothesis and why key features of cognitively complex communication such as intentionality and referentiality should be more effective in forming and maintaining bonded relationships as compared with less cognitively complex communication. Exploring the link between cognition, communication and sociality provides insights into how increasing flexibility in communication can facilitate the emergence of social systems characterised by bonded social relationships, such as those found in non‐human primates and humans. To move the field forward and carry out both within‐ and among‐species comparisons, we advocate the use of social network analysis, which provides a novel way to describe and compare social structure. Using this approach can lead to a new, systematic way of examining social and communicative complexity across species, something that is lacking in current comparative studies of social structure.     

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.     

Experimental manipulation of avian social structure reveals segregation is carried over across contexts

Our current understanding of animal social networks is largely based on observations or experiments that do not directly manipulate associations between individuals. Consequently, evidence relating to the causal processes underlying such networks is limited. By imposing specified rules controlling individual access to feeding stations, we directly manipulated the foraging social network of a wild bird community, thus demonstrating how external factors can shape social structure. We show that experimentally imposed constraints were carried over into patterns of association at unrestricted, ephemeral food patches, as well as at nesting sites during breeding territory prospecting. Hence, different social contexts can be causally linked, and constraints at one level may have consequences that extend into other aspects of sociality. Finally, the imposed assortment was lost following the cessation of the experimental manipulation, indicating the potential for previously perturbed social networks of wild animals to recover from segregation driven by external constraints.     

The effects of data collection and observation methods on uncertainty of social networks in wild primates

In social species, network centralities of group members shape social transmission and other social phenomena. Different factors have been found to influence the measurement of social networks, such as data collection and observation methods. In this study, we collected data on adults and juveniles and examined the effect of data collection method (ad libitum sampling vs. focal animal sampling) and observation method (interaction—grooming; play—vs. association—arm-length; 2 m; 5 m proximities—) on social networks in wild vervet monkeys. First, we showed using a bootstrapping method, that uncertainty of ad libitum grooming and play matrices were lesser than uncertainty of focal matrices. Nevertheless, grooming and play networks constructed from ad libitum and focal animal sampling were very similar and highly correlated. We improved the certainty of both grooming and play networks by pooling focal and ad libitum matrices. Second, we reported a high correlation between the proximity arm-length network and the focal grooming one making an arm-length proximity network a reasonable proxy for a grooming one in vervet monkeys. However, we did not find such a correlation between proximity networks and the play one. Studying the effects of methodological issues as data collection and observation methods can help improve understanding of what shapes social networks and which data collection method to choose to study sociality.     

Networks in ecology

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Recently, ecology has shown a strong interest in network theory. The question, as with any other emerging field, is to what extent we are making real progress in understanding ecological and evolutionary processes or just telling the same stories with fancy new words. I first present a biased overview of the development of network theory, focusing on its search for common patterns across seemingly different systems. I then proceed by discussing some applications of network theory in ecology, namely, species interactions, spatial ecology, epidemiology, and evolution in social groups . Finally, I suggest important contributions of the network approach such as identifying the consequences of heterogeneity for population and community dynamics, potential pitfalls, and future directions.     

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.     

Does the sociality of pollinators shape the organisation of pollination networks?

A striking structural pattern of pollination networks is the presence of a few highly connected species which has implications for ecological and evolutionary processes that create and maintain diversity. To understand the structure and dynamics of pollination networks we need to know which mechanisms allow the emergence of highly connected species. We investigate whether social pollinator species are highly connected in pollination networks, and whether network structure is affected by the presence of high proportions of social pollinator species. Social insects are abundant, with long activity periods and, at the highest level of social organisation, specialised foraging castes. These three attributes are likely to increase the number of interactions of social species and, consequently, their role in pollination networks. We find that social species have, on average, more prominent network roles than solitary species, a possible mechanism being the individual‐rich colonies of social insects. However, when accounting for the shared evolutionary history of pollinators, sociality is only associated with highly interactive roles in Apidae. For apid bees, our structural equation analysis shows that the effect of sociality on species network roles is an indirect result of their high levels of interaction frequency. Despite the relative importance of sociality at a species‐level, an increasing proportion of social species in pollination networks did not affect overall network structure. Our results suggest that behavioural traits may shape patterns of interaction of individual species but not the network‐level organisation of species interactions. Instead, network structure appears to be determined by more general aspects of ecological systems such as interaction intimacy, patterns of niche overlap, and species abundance distributions.