Social control is associated with increased reproductive skew in a wild mammal.

In group-living species, reproductive variation among individuals of the same sex is widespread. By identifying the mechanisms underlying this reproductive skew, we gain fundamental insights into the evolution and maintenance of sociality. A common mechanism, social control, is typically studied by quantifying dominance, which is one of many attributes of sociality that describes how individuals exert influence on others and is an incomprehensive measure of social control as it accounts only for direct relationships. Here, we use the global reaching centrality (GRC), which quantifies the degree of hierarchy in a social network by accounting for both direct and indirect social relationships. Using a wild, free-living population of adult female yellow-bellied marmots (Marmota flaviventris), we found a positive relationship between the reproductive skew index and GRC: more despotic social groups have higher reproductive skew. The GRC was stronger predictor for skew than traditional measures of social control (i.e. dominance). This allows deeper insights into the diverse ways individuals control other group members' reproduction, a core component in the evolution of sociality. Future studies of skew across taxa may profit by using more comprehensive, network-based measures of social control.

Group-level differences in social network structure remain repeatable after accounting for environmental drivers.

Individuals show consistent between-individual behavioural variation when they interact with conspecifics or heterospecifics. Such patterns might underlie emergent group-specific behavioural patterns and between-group behavioural differences. However, little is known about (i) how social and non-social drivers (external drivers) shape group-level social structures and (ii) whether animal groups show consistent between-group differences in social structure after accounting for external drivers. We used automated tracking to quantify daily social interactions and association networks in 12 colonies of zebra finches (Taeniopygia guttata). We quantified the effects of five external drivers (group size, group composition, ecological factors, physical environments and methodological differences) on daily interaction and association networks and tested whether colonies expressed consistent differences in day-to-day network structure after controlling for these drivers. Overall, we found that external drivers contribute significantly to network structure. However, even after accounting for the contribution of external drivers, there remained significant support for consistent between-group differences in both interaction (repeatability R: up to 0.493) and association (repeatability R: up to 0.736) network structures. Our study demonstrates how group-level differences in social behaviour can be partitioned into different drivers of variation, with consistent contributions from both social and non-social factors.

Fear in urban landscapes: conspecific flock size drives escape decisions in tropical birds.

Human-induced disturbances affect animal behaviours such as anti-predatory responses. Animals in urban environments tend to exhibit a reduced escape response, measured as a shorter flight initiation distance (FID), compared to their rural counterparts. While FID has been evaluated in animals dwelling in contrasting habitats (e.g. urban versus rural), little is known about how this response varies within urban environments, especially in tropical cities. Here, we studied the FID of 15 resident bird species in Bogota, Colombia, at 22 sites grouped into four categories (natural sites, metropolitan parks, zonal parks and residential areas) that differed in landscape features and evaluated which factors affected the escape responses of birds. We showed that birds foraging in larger flocks are more tolerant when being approached but they do not seem to be influenced by other factors such as heterospecific flock size, noise levels, pedestrian density, predator density, natural cover or body length. Also, birds inhabiting residential areas and parks showed a shorter FID compared to birds in natural areas suggesting that they are more tolerant of human-related disturbances compared to their conspecifics that live in natural areas within the city. Our study shows important differences in bird anti-predatory responses within the city and suggests that social strategies (i.e. flocking patterns) may be a mechanism for adapting to human-induced disturbances in urban tropical environments.

Machine learning reveals cryptic dialects that explain mate choice in a songbird.

Culturally transmitted communication signals - such as human language or bird song - can change over time through cultural drift, and the resulting dialects may consequently enhance the separation of populations. However, the emergence of song dialects has been considered unlikely when songs are highly individual-specific, as in the zebra finch (Taeniopygia guttata). Here we show that machine learning can nevertheless distinguish the songs from multiple captive zebra finch populations with remarkable precision, and that 'cryptic song dialects' predict strong assortative mating in this species. We examine mating patterns across three consecutive generations using captive populations that have evolved in isolation for about 100 generations. We cross-fostered eggs within and between these populations and used an automated barcode tracking system to quantify social interactions. We find that females preferentially pair with males whose song resembles that of the females' adolescent peers. Our study shows evidence that in zebra finches, a model species for song learning, individuals are sensitive to differences in song that have hitherto remained unnoticed by researchers.

The importance of individual-to-society feedbacks in animal ecology and evolution.

The social decisions that individuals make-who to interact with and how frequently-give rise to social structure. The resulting social structure then determines how individuals interact with their surroundings-resources and risks, pathogens and predators, competitors and cooperators. However, despite intensive research on (a) how individuals make social decisions and (b) how social structure shapes social processes (e.g. cooperation, competition and conflict), there are still few studies linking these two perspectives. These perspectives represent two halves of a feedback loop: individual behaviour scales up to define the social environment, and this environment, in turn, feeds back by shaping the selective agents that drive individual behaviour. We first review well-established research areas that have captured both elements of this feedback loop-host-pathogen dynamics and cultural transmission. We then highlight areas where social structure is well studied but the two perspectives remain largely disconnected. Finally, we synthesise existing research on 14 distinct research topics to identify new prospects where the interplay between social structure and social processes are likely to be important but remain largely unexplored. Our review shows that the inherent links between individuals' traits, their social decisions, social structure and social evolution, warrant more consideration. By mapping the existing and missing connections among many research areas, our review highlights where explicitly considering social structure and the individual-to-society feedbacks can reveal new dimensions to old questions in ecology and evolution.

Transient LTRE analysis reveals the demographic and trait-mediated processes that buffer population growth.

Temporal variation in environmental conditions affects population growth directly via its impact on vital rates, and indirectly through induced variation in demographic structure and phenotypic trait distributions. We currently know very little about how these processes jointly mediate population responses to their environment. To address this gap, we develop a general transient life table response experiment (LTRE) which partitions the contributions to population growth arising from variation in (1) survival and reproduction, (2) demographic structure, (3) trait values and (4) climatic drivers. We apply the LTRE to a population of yellow-bellied marmots (Marmota flaviventer) to demonstrate the impact of demographic and trait-mediated processes. Our analysis provides a new perspective on demographic buffering, which may be a more subtle phenomena than is currently assumed. The new LTRE framework presents opportunities to improve our understanding of how trait variation influences population dynamics and adaptation in stochastic environments.

Linking the fine-scale social environment to mating decisions: a future direction for the study of extra-pair paternity.

Variation in extra-pair paternity (EPP) among individuals of the same population could result from stochastic demography or from individual differences in mating strategies. Although the adaptive value of EPP has been widely studied, much less is known about the characteristics of the social environment that drive the observed patterns of EPP. Here, we demonstrate how concepts and well-developed tools for the study of social behaviour (such as social network analysis) can enhance the study of extra-pair mating decisions (focussing in particular on avian mating systems). We present several hypotheses that describe how characteristics of the social environment in which individuals are embedded might influence the levels of EPP in a socially monogamous population. We use a multi-level social approach (Hinde, 1976) to achieve a detailed description of the social structure and social dynamics of individuals in a group. We propose that the pair-bond, the direct (local) social environment and the indirect (extended) social environment, can contribute in different ways to the variation observed in the patterns of EPP, at both the individual and the population level. A strength of this approach is that it integrates into the analysis (indirect) interactions with all potential mates in a population, thus extending the current framework to study extra-pair mating behaviour. We also encourage the application of social network methods such as temporal dynamic analysis to depict temporal changes in the patterns of interactions among individuals in a group, and to study how this affects mating behaviour. We argue that this new framework will contribute to a better understanding of the proximate mechanisms that drive variation in EPP within populations in socially monogamous species, and might ultimately provide insights into the evolution and maintenance of mating systems.