Collective signalling is shaped by feedbacks between signaller variation, receiver perception and acoustic environment in a simulated communication network.

Communication takes place within a network of multiple signallers and receivers. Social network analysis provides tools to quantify how an individual's social positioning affects group dynamics and the subsequent biological consequences. However, network analysis is rarely applied to animal communication, likely due to the logistical difficulties of monitoring natural communication networks. We generated a simulated communication network to investigate how variation in individual communication behaviours generates network effects, and how this communication network's structure feeds back to affect future signalling interactions. We simulated competitive acoustic signalling interactions among chorusing individuals and varied several parameters related to communication and chorus size to examine their effects on calling output and social connections. Larger choruses had higher noise levels, and this reduced network density and altered the relationships between individual traits and communication network position. Hearing sensitivity interacted with chorus size to affect both individuals' positions in the network and the acoustic output of the chorus. Physical proximity to competitors influenced signalling, but a distinctive communication network structure emerged when signal active space was limited. Our model raises novel predictions about communication networks that could be tested experimentally and identifies aspects of information processing in complex environments that remain to be investigated. This article is part of the theme issue 'The power of sound: unravelling how acoustic communication shapes group dynamics'.

Hierarchically embedded scales of movement shape the social networks of vampire bats.

Social structure can emerge from hierarchically embedded scales of movement, where movement at one scale is constrained within a larger scale (e.g. among branches, trees, forests). In most studies of animal social networks, some scales of movement are not observed, and the relative importance of the observed scales of movement is unclear. Here, we asked: how does individual variation in movement, at multiple nested spatial scales, influence each individual's social connectedness? Using existing data from common vampire bats (Desmodus rotundus), we created an agent-based model of how three nested scales of movement-among roosts, clusters and grooming partners-each influence a bat's grooming network centrality. In each of 10 simulations, virtual bats lacking social and spatial preferences moved at each scale at empirically derived rates that were either fixed or individually variable and either independent or correlated across scales. We found that numbers of partners groomed per bat were driven more by within-roost movements than by roost switching, highlighting that co-roosting networks do not fully capture bat social structure. Simulations revealed how individual variation in movement at nested spatial scales can cause false discovery and misidentification of preferred social relationships. Our model provides several insights into how nonsocial factors shape social networks.

Inferred Attractiveness: A generalized mechanism for sexual selection that can maintain variation in traits and preferences over time.

Sexual selection by mate choice is a powerful force that can lead to evolutionary change, and models of why females choose particular mates are central to understanding its effects. Predominant mate choice theories assume preferences are determined solely by genetic inheritance, an assumption still lacking widespread support. Moreover, preferences often vary among individuals or populations, fail to correspond with conspicuous male traits, or change with context, patterns not predicted by dominant models. Here, we propose a new model that explains this mate choice complexity with one general hypothesized mechanism, "Inferred Attractiveness." In this model, females acquire mating preferences by observing others' choices and use context-dependent information to infer which traits are attractive. They learn to prefer the feature of a chosen male that most distinguishes him from other available males. Over generations, this process produces repeated population-level switches in preference and maintains male trait variation. When viability selection is strong, Inferred Attractiveness produces population-wide adaptive preferences superficially resembling "good genes." However, it results in widespread preference variation or nonadaptive preferences under other predictable circumstances. By casting the female brain as the central selective agent, Inferred Attractiveness captures novel and dynamic aspects of sexual selection and reconciles inconsistencies between mate choice theory and observed behavior.

Individual identity information persists in learned calls of introduced parrot populations.

Animals can actively encode different types of identity information in learned communication signals, such as group membership or individual identity. The social environments in which animals interact may favor different types of information, but whether identity information conveyed in learned signals is robust or responsive to social disruption over short evolutionary timescales is not well understood. We inferred the type of identity information that was most salient in vocal signals by combining computational tools, including supervised machine learning, with a conceptual framework of "hierarchical mapping", or patterns of relative acoustic convergence across social scales. We used populations of a vocal learning species as a natural experiment to test whether the type of identity information emphasized in learned vocalizations changed in populations that experienced the social disruption of introduction into new parts of the world. We compared the social scales with the most salient identity information among native and introduced range monk parakeet (Myiopsitta monachus) calls recorded in Uruguay and the United States, respectively. We also evaluated whether the identity information emphasized in introduced range calls changed over time. To place our findings in an evolutionary context, we compared our results with another parrot species that exhibits well-established and distinctive regional vocal dialects that are consistent with signaling group identity. We found that both native and introduced range monk parakeet calls displayed the strongest convergence at the individual scale and minimal convergence within sites. We did not identify changes in the strength of acoustic convergence within sites over time in the introduced range calls. These results indicate that the individual identity information in learned vocalizations did not change over short evolutionary timescales in populations that experienced the social disruption of introduction. Our findings point to exciting new research directions about the robustness or responsiveness of communication systems over different evolutionary timescales.

Inferring the decision rules that drive co-foraging affiliations in wild mixed-species parrot groups.

Animals gathered around a specific location or resource may represent mixed-species aggregations or mixed-species groups. Patterns of individuals choosing to join these groups can provide insight into the information processing underlying these decisions. However, we still have little understanding of how much information these decisions are based upon. We used data on 12 parrot species to test what kind of information each species may use about others to make decisions about which mixed-species aggregations to participate in. We used co-presence and joining patterns with categorization and model fitting methods to test how these species could be making grouping decisions. Species generally used a simpler lower-category method to choose which other individuals to associate with, rather than basing these decisions on species-level information. We also found that the best-fit models for decision-making differed across the 12 species and included different kinds of information. We found that not only does this approach provide a framework to test hypotheses about why individuals join or leave mixed-species aggregations, it also provides insight into what features each parrot could have been using to make their decisions. While not exhaustive, this approach provides a novel examination of the potential features that species could use to make grouping decisions and could provide a link to the perceptive and cognitive abilities of the animals making these minute-by-minute decisions. This article is part of the theme issue 'Mixed-species groups and aggregations: shaping ecological and behavioural patterns and processes'.

The centennial of the pecking order: current state and future prospects for the study of dominance hierarchies.

A century ago, foundational work by Thorleif Schjelderup-Ebbe described a 'pecking order' in chicken societies, where individuals could be ordered according to their ability to exert their influence over their group-mates. Now known as dominance hierarchies, these structures have been shown to influence a plethora of individual characteristics and outcomes, situating dominance research as a pillar of the study of modern social ecology and evolution. Here, we first review some of the major questions that have been answered about dominance hierarchies in the last 100 years. Next, we introduce the contributions to this theme issue and summarize how they provide ongoing insight in the epistemology, physiology and neurobiology, hierarchical structure, and dynamics of dominance. These contributions employ the full range of research approaches available to modern biologists. Cross-cutting themes emerging from these contributions include a focus on cognitive underpinnings of dominance, the application of network-analytical approaches, and the utility of experimental rank manipulations for revealing causal relationships. Reflection on the last 100 years of dominance research reveals how Schjelderup-Ebbe's early ideas and the subsequent research helped drive a shift from an essentialist view of species characteristics to the modern recognition of rich inter-individual variation in social, behavioural and physiological phenotypes. This article is part of the theme issue 'The centennial of the pecking order: current state and future prospects for the study of dominance hierarchies'.

Quantifying the dynamics of nearly 100 years of dominance hierarchy research.

Dominance hierarchies have been studied for almost 100 years. The science of science approach used here provides high-level insight into how the dynamics of dominance hierarchy research have shifted over this long timescale. To summarize these patterns, I extracted publication metadata using a Google Scholar search for the phrase 'dominance hierarchy', resulting in over 26 000 publications. I used text mining approaches to assess patterns in three areas: (1) general patterns in publication frequency and rate, (2) dynamics of term usage and (3) term co-occurrence in publications across the history of the field. While the overall number of publications per decade continues to rise, the percent growth rate has fallen in recent years, demonstrating that although there is sustained interest in dominance hierarchies, the field is no longer experiencing the explosive growth it showed in earlier decades. Results from title term co-occurrence networks and community structure show that the different subfields of dominance hierarchy research were most strongly separated early in the field's history while modern research shows more evidence for cohesion and a lack of distinct term community boundaries. These methods provide a general view of the history of research on dominance hierarchies and can be applied to other fields or search terms to gain broad synthetic insight into patterns of interest, especially in fields with large bodies of literature. This article is part of the theme issue 'The centennial of the pecking order: current state and future prospects for the study of dominance hierarchies'.

DomArchive: a century of published dominance data.

Dominance behaviours have been collected for many groups of animals since 1922 and serve as a foundation for research on social behaviour and social structure. Despite a wealth of data from the last century of research on dominance hierarchies, these data are only rarely used for comparative insight. Here, we aim to facilitate comparative studies of the structure and function of dominance hierarchies by compiling published dominance interaction datasets from the last 100 years of work. This compiled archive includes 436 datasets from 190 studies of 367 unique groups (mean group size 13.8, s.d. = 13.4) of 135 different species, totalling over 243 000 interactions. These data are presented in an R package alongside relevant metadata and a tool for subsetting the archive based on biological or methodological criteria. In this paper, we explain how to use the archive, discuss potential limitations of the data, and reflect on best practices in publishing dominance data based on our experience in assembling this dataset. This archive will serve as an important resource for future comparative studies and will promote the development of general unifying theories of dominance in behavioural ecology that can be grounded in testing with empirical data. This article is part of the theme issue 'The centennial of the pecking order: current state and future prospects for the study of dominance hierarchies'.

Expanding the landscape of opportunity: Professional societies support early-career researchers through community programming and peer coaching.

Weaving the future of the field of comparative psychology is dependent on the career advancement of early-career scientists. Despite concerted efforts to increase diversity in science, technology, engineering, and mathematics, scholars from marginalized groups are disproportionately underrepresented in the field-especially at advanced career stages. New approaches to sponsorship, mentoring, and community building are necessary to retain talent from marginalized communities and to create a culture and a system where all individuals can thrive. We describe the unique and supportive role of senior women scientists united through a professional society in initiating peer coaching circles to facilitate the success of a diverse cohort of early-career women scientists. We offer our experiences with the Weaving the Future of Animal Behavior program as a case study that illustrates the cascading impacts of professional societies investing in the success and career development of marginalized scholars. We focus on our peer coaching circle experience and share the products and outcomes after 2 years of meeting. Peer coaching transformed us from a group of loosely organized, anxious individuals into a collective of empowered agents of change with an enhanced sense of belonging. We end by presenting recommendations to institutions seeking to expand the landscape of opportunities to other marginalized scholars. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Anticipated effects of abiotic environmental change on intraspecific social interactions.

Social interactions are ubiquitous across the animal kingdom. A variety of ecological and evolutionary processes are dependent on social interactions, such as movement, disease spread, information transmission, and density-dependent reproduction and survival. Social interactions, like any behaviour, are context dependent, varying with environmental conditions. Currently, environments are changing rapidly across multiple dimensions, becoming warmer and more variable, while habitats are increasingly fragmented and contaminated with pollutants. Social interactions are expected to change in response to these stressors and to continue to change into the future. However, a comprehensive understanding of the form and magnitude of the effects of these environmental changes on social interactions is currently lacking. Focusing on four major forms of rapid environmental change currently occurring, we review how these changing environmental gradients are expected to have immediate effects on social interactions such as communication, agonistic behaviours, and group formation, which will thereby induce changes in social organisation including mating systems, dominance hierarchies, and collective behaviour. Our review covers intraspecific variation in social interactions across environments, including studies in both the wild and in laboratory settings, and across a range of taxa. The expected responses of social behaviour to environmental change are diverse, but we identify several general themes. First, very dry, variable, fragmented, or polluted environments are likely to destabilise existing social systems. This occurs as these conditions limit the energy available for complex social interactions and affect dissimilar phenotypes differently. Second, a given environmental change can lead to opposite responses in social behaviour, and the direction of the response often hinges on the natural history of the organism in question. Third, our review highlights the fact that changes in environmental factors are not occurring in isolation: multiple factors are changing simultaneously, which may have antagonistic or synergistic effects, and more work should be done to understand these combined effects. We close by identifying methodological and analytical techniques that might help to study the response of social interactions to changing environments, highlight consistent patterns among taxa, and predict subsequent evolutionary change. We expect that the changes in social interactions that we document here will have consequences for individuals, groups, and for the ecology and evolution of populations, and therefore warrant a central place in the study of animal populations, particularly in an era of rapid environmental change.

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

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

Aggression heuristics underlie animal dominance hierarchies and provide evidence of group-level social information.

Members of a social species need to make appropriate decisions about who, how, and when to interact with others in their group. However, it has been difficult for researchers to detect the inputs to these decisions and, in particular, how much information individuals actually have about their social context. We present a method that can serve as a social assay to quantify how patterns of aggression depend upon information about the ranks of individuals within social dominance hierarchies. Applied to existing data on aggression in 172 social groups across 85 species in 23 orders, it reveals three main patterns of rank-dependent social dominance: the downward heuristic (aggress uniformly against lower-ranked opponents), close competitors (aggress against opponents ranked slightly below self), and bullying (aggress against opponents ranked much lower than self). The majority of the groups (133 groups, 77%) follow a downward heuristic, but a significant minority (38 groups, 22%) show more complex social dominance patterns (close competitors or bullying) consistent with higher levels of social information use. These patterns are not phylogenetically constrained and different groups within the same species can use different patterns, suggesting that heuristic use may depend on context and the structuring of aggression by social information should not be considered a fixed characteristic of a species. Our approach provides opportunities to study the use of social information within and across species and the evolution of social complexity and cognition.

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.

Differences in social information are critical to understanding aggressive behavior in animal dominance hierarchies.

Sociality often involves conflict as individuals compete with group members for resources. In many species, including humans, individuals assort into dominance hierarchies. Individuals with more social information may be able to better optimize which individuals they challenge and in doing so, improve their overall rank in the hierarchy. Understanding how information is perceived, processed, and used by individuals in hierarchical systems is critical to understanding how animals make aggression decisions because different types of information can underlie different kinds of aggression strategies. This review summarizes recent research on the effect of five information types on animal conflict: Firstly, individual experience; secondly, recognition abilities; thirdly, social context; fourthly, transitive inference; and finally, network or global inference. This increased understanding of the information underlying social interactions can begin to provide new insight into structured conflict and could be useful to better understand strategic decision-making, social plasticity, and the cognitive load of sociality across species, including humans.

Theory Meets Empiry: A Citation Network Analysis.

According to a recent survey, ecologists and evolutionary biologists feel that theoretical and empirical research should coexist in a tight feedback loop but believe that the two domains actually interact very little. We evaluate this perception using a citation network analysis for two data sets, representing the literature on sexual selection and speciation. Overall, 54%-60% of citations come from a paper's own category, whereas 17%-23% are citations across categories. These cross-citations tend to focus on highly cited papers, and we observe a positive correlation between the numbers of citations a study receives within and across categories. We find evidence that reviews can function as integrators between the two literatures, argue that theoretical models are analogous to specific empirical study systems, and complement our analyses by studying a cocitation network. We conclude that theoretical and empirical research are more tightly connected than generally thought but that avenues exist to further increase this integration.

Social tipping points in animal societies.

Animal social groups are complex systems that are likely to exhibit tipping points-which are defined as drastic shifts in the dynamics of systems that arise from small changes in environmental conditions-yet this concept has not been carefully applied to these systems. Here, we summarize the concepts behind tipping points and describe instances in which they are likely to occur in animal societies. We also offer ways in which the study of social tipping points can open up new lines of inquiry in behavioural ecology and generate novel questions, methods, and approaches in animal behaviour and other fields, including community and ecosystem ecology. While some behaviours of living systems are hard to predict, we argue that probing tipping points across animal societies and across tiers of biological organization-populations, communities, ecosystems-may help to reveal principles that transcend traditional disciplinary boundaries.

History of nonnative Monk Parakeets in Mexico.

Nonnative Monk Parakeets have been reported in increasing numbers across many cities in Mexico, and were formally classified as an invasive species in Mexico in late 2016. However, there has not been a large-scale attempt to determine how international pet trade and national and international governmental regulations have played a part in colonization, and when the species appeared in different areas. We describe the changes in regulations that led the international pet trade market to shift to Mexico, then used international trade data to determine how many parakeets were commercially imported each year and where those individuals originated. We also quantified the recent increases in Monk Parakeet (Myiopsitta monachus) sightings in Mexico in both the scientific literature and in citizen science reports. We describe the timeline of increased reports to understand the history of nonnative Monk Parakeets in Mexico. As in other areas where the species has colonized, the main mode of transport is through the international pet trade. Over half a million Monk Parakeets were commercially imported to Mexico during 2000-2015, with the majority of importation (90%) occurring in 2008-2014, and almost all (98%) were imported from Uruguay. The earliest record of a free-flying Monk Parakeet was observed during 1994-1995 in Mexico City, but sightings of the parakeets did not become geographically widespread in either the scientific literature or citizen science databases until 2012-2015. By 2015, parakeets had been reported in 97 cities in Mexico. Mexico City has consistently seen steep increases in reporting since this species was first reported in Mexico. Here we find that both national and international legal regulations and health concerns drove a rise and fall in Monk Parakeet pet trade importations, shortly followed by widespread sightings of feral parakeets across Mexico. Further monitoring of introduced Monk Parakeet populations in Mexico is needed to understand the establishment, growth and spread of introduced populations.

Social Feedback and the Emergence of Rank in Animal Society.

Dominance hierarchies are group-level properties that emerge from the aggression of individuals. Although individuals can gain critical benefits from their position in a hierarchy, we do not understand how real-world hierarchies form. Nor do we understand what signals and decision-rules individuals use to construct and maintain hierarchies in the absence of simple cues such as size or spatial location. A study of conflict in two groups of captive monk parakeets (Myiopsitta monachus) found that a transition to large-scale order in aggression occurred in newly-formed groups after one week, with individuals thereafter preferring to direct aggression more frequently against those nearby in rank. We consider two cognitive mechanisms underlying the emergence of this order: inference based on overall levels of aggression, or on subsets of the aggression network. Both mechanisms were predictive of individual decisions to aggress, but observed patterns were better explained by rank inference through subsets of the aggression network. Based on these results, we present a new theory, of a feedback loop between knowledge of rank and consequent behavior. This loop explains the transition to strategic aggression and the formation and persistence of dominance hierarchies in groups capable of both social memory and inference.