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.     

Active colonization dynamics and diversity patterns are influenced by dendritic network connectivity and species interactions

Habitat network connectivity influences colonization dynamics, species invasions, and biodiversity patterns. Recent theoretical work suggests dendritic networks, such as those found in rivers, alter expectations regarding colonization and dispersal dynamics compared with other network types. As many native and non‐native species are spreading along river networks, this may have important ecological implications. However, experimental studies testing the effects of network structure on colonization and diversity patterns are scarce. Up to now, experimental studies have only considered networks where sites are connected with small corridors, or dispersal was experimentally controlled, which eliminates possible effects of species interactions on colonization dynamics. Here, we tested the effect of network connectivity and species interactions on colonization dynamics using continuous linear and dendritic (i.e., river‐like) networks, which allow for active dispersal. We used a set of six protist species and one rotifer species in linear and dendritic microcosm networks. At the start of the experiment, we introduced species, either singularly or as a community within the networks. Species subsequently actively colonized the networks. We periodically measured densities of species throughout the networks over 2 weeks to track community dynamics, colonization, and diversity patterns. We found that colonization of dendritic networks was faster compared with colonization of linear networks, which resulted in higher local mean species richness in dendritic networks. Initially, community similarity was also greater in dendritic networks compared with linear networks, but this effect vanished over time. The presence of species interactions increased community evenness over time, compared with extrapolations from single‐species setups. Our experimental findings confirm previous theoretical work and show that network connectivity, species‐specific dispersal ability, and species interactions greatly influence the dispersal and colonization of dendritic networks. We argue that these factors need to be considered in empirical studies, where effects of network connectivity on colonization patterns have been largely underestimated.     

Application of network methods for understanding evolutionary dynamics in discrete habitats

In populations occupying discrete habitat patches, gene flow between habitat patches may form an intricate population structure. In such structures, the evolutionary dynamics resulting from interaction of gene‐flow patterns with other evolutionary forces may be exceedingly complex. Several models describing gene flow between discrete habitat patches have been presented in the population‐genetics literature; however, these models have usually addressed relatively simple settings of habitable patches and have stopped short of providing general methodologies for addressing nontrivial gene‐flow patterns. In the last decades, network theory – a branch of discrete mathematics concerned with complex interactions between discrete elements – has been applied to address several problems in population genetics by modelling gene flow between habitat patches using networks. Here, we present the idea and concepts of modelling complex gene flows in discrete habitats using networks. Our goal is to raise awareness to existing network theory applications in molecular ecology studies, as well as to outline the current and potential contribution of network methods to the understanding of evolutionary dynamics in discrete habitats. We review the main branches of network theory that have been, or that we believe potentially could be, applied to population genetics and molecular ecology research. We address applications to theoretical modelling and to empirical population‐genetic studies, and we highlight future directions for extending the integration of network science with molecular ecology.     

Effect of agricultural land‐use change on the structure of a temperate forest ant–plant interaction network

Studies on the responses of ant–plant interactions to land‐use change have mainly focused on tropical habitats, usually without considering the impacts on the structure of interaction networks. Here we show that land‐use modifies the structure of the ant–plant interaction networks in a temperate habitat. Ant–plant interactions and plant diversity were recorded in an oak forest and agricultural land in central Mexico. We registered five ant species in the oak forest, and four ant species in the agricultural land. Plant diversity was higher in the agricultural land than in the oak forest. In the ant–plant networks of both sites, our results showed a higher dependence of ants on the plants on which they feed than vice versa, and the ants Formica spp. and the plants Barkleyanthus salicifolius were the species with the most strength and greatest influence in the network structure. The ant–plant network in the oak forest showed a nested structure. However, the network at the agricultural land site showed non‐nestedness; the identity of both ants and plants with the highest values of specialization was different and the number of ant species in the network was decreased, but the number of plant species with which they interacted significantly increased. Both ant–plant networks were equally tolerant to simulated extinction of individual species. We conclude that temperate forest ant–plant networks can be inherently fragile and susceptible to the effects of agricultural land‐use change, not on the number of interacting species but on their identity.     

Chimpanzee identification and social network construction through an online citizen science platform

Citizen science has grown rapidly in popularity in recent years due to its potential to educate and engage the public while providing a means to address a myriad of scientific questions. However, the rise in popularity of citizen science has also been accompanied by concerns about the quality of data emerging from citizen science research projects. We assessed data quality in the online citizen scientist platform Chimp&See, which hosts camera trap videos of chimpanzees (Pan troglodytes) and other species across Equatorial Africa. In particular, we compared detection and identification of individual chimpanzees by citizen scientists with that of experts with years of experience studying those chimpanzees. We found that citizen scientists typically detected the same number of individual chimpanzees as experts, but assigned far fewer identifications (IDs) to those individuals. Those IDs assigned, however, were nearly always in agreement with the IDs provided by experts. We applied the data sets of citizen scientists and experts by constructing social networks from each. We found that both social networks were relatively robust and shared a similar structure, as well as having positively correlated individual network positions. Our findings demonstrate that, although citizen scientists produced a smaller data set based on fewer confirmed IDs, the data strongly reflect expert classifications and can be used for meaningful assessments of group structure and dynamics. This approach expands opportunities for social research and conservation monitoring in great apes and many other individually identifiable species.     

Vocal networks remain stable after a disturbance in Emei music frogs

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

社会网络分析法及其在动物行为学研究中的应用

近年来,社会网络分析法被广泛用于动物行为学研究。它通过量化动物社会关系中的特定属性 (如中心度和中心势),可辨识动物群体中的关键个体及其在群体中的作用,揭示动物社会交往的形成机制,深化人们对动物社会性起源、个体行为与种群动态格局间关系的理解。本文简要介绍了社会网络分析法的发展史和基本概念,然后阐述了如何建立网络及选择常用指标,强调了创建原模型的必要性及途径。最后着重评述了社会网络分析法在动物行为学研究中的应用现状,并提出未来应当关注直接身体接触 (如打斗和理毛) 和非肢体接触 (如声音通讯) 等不同交往形式的变动过程,以此构建社会交往的动态网络。同时也需要加强种间社交网络的研究,以便增进人们对社会行为的生态功能以及合作理论等问题的理解。     

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.     

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.     

Social network structure in wintering golden‐crowned sparrows is not correlated with kinship

Stable social organization in a wide variety of organisms has been linked to kinship, which can minimize conflict due to the indirect fitness benefits from cooperating with relatives. In birds, kin selection has been mostly studied in the context of reproduction or in species that are social year round. Many birds however are migratory, and the role of kinship in the winter societies of these species is virtually unexplored. In a previous study, we discovered striking social complexity and stability in a wintering population of migratory golden‐crowned sparrows (Zonotrichia atricapilla) – individuals repeatedly form close associations with the same social partners, including across multiple winters. Here, we test the possibility that kinship might be involved in these close and stable social affiliations. We examine the relationship between kinship and social structure for two of the consecutive wintering seasons from the previous study. We found no evidence that social structure was influenced by kinship. Relatedness between most pairs of individuals was at most that of first cousins (and mostly far lower). Genetic networks based on relatedness do not correspond to the social networks, and Mantel tests revealed no relationship between kinship and pairwise interaction frequency. Kinship also failed to predict social structure in more fine‐grained analyses, including analyses of each sex separately (in the event that sex‐biased migration might limit kin selection to one sex), and separate analyses for each social community. The complex winter societies of golden‐crowned sparrows appear to be based on cooperative benefits unrelated to kin selection.     

Dynamic tubulation of mitochondria drives mitochondrial network formation

Mitochondria form networks. Formation of mitochondrial networks is important for maintaining mitochondrial DNA integrity and interchanging mitochondrial material, whereas disruption of the mitochondrial network affects mitochondrial functions. According to the current view, mitochondrial networks are formed by fusion of individual mitochondria. Here, we report a new mechanism for formation of mitochondrial networks through KIF5B-mediated dynamic tubulation of mitochondria. We found that KIF5B pulls thin, highly dynamic tubules out of mitochondria. Fusion of these dynamic tubules, which is mediated by mitofusins, gives rise to the mitochondrial network. We further demonstrated that dynamic tubulation and fusion is sufficient for mitochondrial network formation, by reconstituting mitochondrial networks in vitro using purified fusion-competent mitochondria, recombinant KIF5B, and polymerized microtubules. Interestingly, KIF5B only controls network formation in the peripheral zone of the cell, indicating that the mitochondrial network is divided into subzones, which may be constructed by different mechanisms. Our data not only uncover an essential mechanism for mitochondrial network formation, but also reveal that different parts of the mitochondrial network are formed by different mechanisms.     

Offspring social network structure predicts fitness in families

Social structures such as families emerge as outcomes of behavioural interactions among individuals, and can evolve over time if families with particular types of social structures tend to leave more individuals in subsequent generations. The social behaviour of interacting individuals is typically analysed as a series of multiple dyadic (pair-wise) interactions, rather than a network of interactions among multiple individuals. However, in species where parents feed dependant young, interactions within families nearly always involve more than two individuals simultaneously. Such social networks of interactions at least partly reflect conflicts of interest over the provision of costly parental investment. Consequently, variation in family network structure reflects variation in how conflicts of interest are resolved among family members. Despite its importance in understanding the evolution of emergent properties of social organization such as family life and cooperation, nothing is currently known about how selection acts on the structure of social networks. Here, we show that the social network structure of broods of begging nestling great tits Parus major predicts fitness in families. Although selection at the level of the individual favours large nestlings, selection at the level of the kin-group primarily favours families that resolve conflicts most effectively.     

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.     

Selection for territory acquisition is modulated by social network structure in a wild songbird

The social environment may be a key mediator of selection that operates on animals. In many cases, individuals may experience selection not only as a function of their phenotype, but also as a function of the interaction between their phenotype and the phenotypes of the conspecifics they associate with. For example, when animals settle after dispersal, individuals may benefit from arriving early, but, in many cases, these benefits will be affected by the arrival times of other individuals in their local environment. We integrated a recently described method for calculating assortativity on weighted networks, which is the correlation between an individual's phenotype and that of its associates, into an existing framework for measuring the magnitude of social selection operating on phenotypes. We applied this approach to large‐scale data on social network structure and the timing of arrival into the breeding area over three years. We found that late‐arriving individuals had a reduced probability of breeding. However, the probability of breeding was also influenced by individuals’ social networks. Associating with late‐arriving conspecifics increased the probability of successfully acquiring a breeding territory. Hence, social selection could offset the effects of nonsocial selection. Given parallel theoretical developments of the importance of local network structure on population processes, and increasing data being collected on social networks in free‐living populations, the integration of these concepts could yield significant insights into social evolution.     

Invariant antagonistic network structure despite high spatial and temporal turnover of interactions

Recent work has suggested that emergent ecological network structure exhibits very little spatial or temporal variance despite changes in community composition. However, the changes in network interactions associated with turnover in community composition have seldom been assessed. Here we examine whether changes in ecological networks are best detected by standard emergent network metrics or by assessing internal network changes (i.e. interaction and composition turnover). To eliminate possible spatial or phylogenetic effects, that in large‐scale studies may obscure mechanisms structuring networks and interactions, we sampled multiple antagonistic (plant–herbivore) networks for a single diverse plant family (the Restionaceae) in the hyperdiverse Cape Floristic Region. These are the first plant–herbivore networks constructed for this global biodiversity hotspot. We found invariant emergent network structure despite considerable changes in insect and plant composition across communities over time and space. In contrast, there was high interaction turnover between networks. Seasonally, this was driven by turnover in insect species and insect host switching. Spatially, this was driven by simultaneous turnover in plant and insect species, suggesting that many insects are host specific or that both groups exhibit parallel responses to environmental gradients. Spatial interaction turnover was also driven by turnover in plants, showing that many insects can utilise multiple (possibly closely related) hosts and this may create divergent selection gradients that promote insect speciation. Thus we show highly variable interaction fidelity, despite invariant emergent network structure. We suggest that evaluating internal network changes may be more effective at elucidating the processes structuring networks, and many fine‐scale changes may be obscured when only calculating emergent network metrics.     

传粉网络的研究进展:网络的结构和动态

植物与传粉者之间相互作用,构成了复杂的传粉网络。近年来,社会网络分析技术的发展使得复杂生态网络的研究成为可能。从群落水平上研究植物与传粉者之间的互惠关系,为理解群落的结构和动态以及花部特征的演化提供了全新的视角。传粉网络的嵌套结构说明自然界的传粉服务存在冗余,而且是相对泛化的物种主导了传粉。在多年或者多季度的传粉网络中,虽然有很高的物种替换率,但是其网络结构仍然保持相对稳定,说明传粉网络对干扰有很强的抗性。尽管有关网络结构和动态的研究逐渐增多,但传粉网络维持的机制仍不清楚。网络结构可以部分由花部特征与传粉者的匹配来解释,也受到系统发生的制约,影响因素还包括群落构建的时间和物种多样性,以及物种在群落中的位置。开展大尺度群落动态的研究,为探索不同时间尺度、不同物种多样性水平上的传粉网络的生态学意义提供了条件。但已有的研究仍存在不足,比如基于访问观察的网络无法准确衡量传粉者的访问效率和植物间的花粉流动,以及结果受到调查精度区域研究不平衡的制约等。目前的研究只深入到传粉者携带花粉构成成分的水平,传粉者访问植物的网络不能代表植物的整个传粉过程。因此,研究应当更多地深入到物种之间关系对有性生殖的切实影响上。     

Quantitative analysis of protein interaction network dynamics in yeast

Many cellular functions are mediated by protein–protein interaction networks, which are environment dependent. However, systematic measurement of interactions in diverse environments is required to better understand the relative importance of different mechanisms underlying network dynamics. To investigate environment‐dependent protein complex dynamics, we used a DNA‐barcode‐based multiplexed protein interaction assay in Saccharomyces cerevisiae to measure in vivo abundance of 1,379 binary protein complexes under 14 environments. Many binary complexes (55%) were environment dependent, especially those involving transmembrane transporters. We observed many concerted changes around highly connected proteins, and overall network dynamics suggested that “concerted” protein‐centered changes are prevalent. Under a diauxic shift in carbon source from glucose to ethanol, a mass‐action‐based model using relative mRNA levels explained an estimated 47% of the observed variance in binary complex abundance and predicted the direction of concerted binary complex changes with 88% accuracy. Thus, we provide a resource of yeast protein interaction measurements across diverse environments and illustrate the value of this resource in revealing mechanisms of network dynamics.     

Modelling dendritic ecological networks in space: an integrated network perspective

Dendritic ecological networks (DENs) are a unique form of ecological networks that exhibit a dendritic network topology (e.g. stream and cave networks or plant architecture). DENs have a dual spatial representation; as points within the network and as points in geographical space. Consequently, some analytical methods used to quantify relationships in other types of ecological networks, or in 2‐D space, may be inadequate for studying the influence of structure and connectivity on ecological processes within DENs. We propose a conceptual taxonomy of network analysis methods that account for DEN characteristics to varying degrees and provide a synthesis of the different approaches within the context of stream ecology. Within this context, we summarise the key innovations of a new family of spatial statistical models that describe spatial relationships in DENs. Finally, we discuss how different network analyses may be combined to address more complex and novel research questions. While our main focus is streams, the taxonomy of network analyses is also relevant anywhere spatial patterns in both network and 2‐D space can be used to explore the influence of multi‐scale processes on biota and their habitat (e.g. plant morphology and pest infestation, or preferential migration along stream or road corridors).     

Spread of two linked social norms on complex interaction networks

In this paper, we study the spread of social norms, such as rules and customs that are components of human cultures. We consider the spread of two social norms, which are linked through individual behaviors. Spreading social norms depend not only on the social network structure, but also on the learning system. We consider four social network structures: (1) complete mixing, in which each individual interacts with the others at random, (2) lattice, in which each individual interacts with its neighbors with some probability and with the others at random, (3) power-law network, in which a few influential people have more social contacts than the others, and (4) random graph network, in which the number of contacts follows a Poisson distribution. Using the lattice model, we also investigate the effect of the small-world phenomenon on the dynamics of social norms. In our models, each individual learns a social norm by trial and error (individual learning) and also imitates the other's social norm (social learning). We investigate how social network structure and learning systems affect the spread of two linked social norms. Our main results are: (1) Social learning does not lead to coexistence of social norms. Individual learning produces coexistence, and the dynamics of coexistence depend on which social norms are learned individually. (2) Social norms spread fastest in the power-law network model, followed by the random graph model, the complete mixing model, the two-dimensional lattice model and the one-dimensional lattice. (3) We see a "small world effect" in the one-dimensional model, but not in two dimensions.     

Agricultural intensification drives changes in hybrid network robustness by modifying network structure

Within ecological communities, species engage in myriad interaction types, yet empirical examples of hybrid species interaction networks composed of multiple types of interactions are still scarce. A key knowledge gap is understanding how the structure and stability of such hybrid networks are affected by anthropogenic disturbance. Using 15,169 interaction observations, we constructed 16 hybrid herbivore‐plant‐pollinator networks along an agricultural intensification gradient to explore changes in network structure and robustness to local extinctions. We found that agricultural intensification led to declines in modularity but increases in nestedness and connectance. Notably, network connectance, a structural feature typically thought to increase robustness, caused declines in hybrid network robustness, but the directionality of changes in robustness along the gradient depended on the order of local species extinctions. Our results not only demonstrate the impacts of anthropogenic disturbance on hybrid network structure, but they also provide unexpected insights into the structure‐stability relationship of hybrid networks.