Animal Social Structure Research Articles

Social responses to the natural loss of individuals in Barbary macaques

In recent years, there has been considerable interest in investigating how animal social structure is affected by the loss of individuals. This is often achieved using simulations that generate predictions regarding how the removal of ‘key’ individuals from a group affects network structure. However, little is known about the effects of such removals in wild and free-ranging populations, particularly the extent to which naturally occurring mortality events and the loss of a large proportion of individuals from a social group affects the overall structure of a social network. Here, we used data from a population of wild Barbary macaques (Macaca sylvanus) that was exposed to an exceptionally harsh winter, culminating in the death of 64% of the adults from two groups. We analysed how social interaction patterns among surviving individuals were affected by the natural loss of group members using social networks based on affiliative (i.e., grooming) and aggressive social interactions. We show that only the structure of the pre-decline grooming networks was conserved in the post-decline networks, suggesting that grooming, but not aggression networks are resilient against the loss of group members. Surviving group members were not significantly different from the non-survivors in terms of their affiliative and agonistic relationships, and did not form assorted communities in the pre-decline networks. Overall, our results suggest that in primates, patterns of affiliative interactions are more resilient to changes in group composition than aggressive interaction patterns, which tend to be used more flexibly in new conditions.

Modelling associations between animal social structure and demography

Successfully navigating a complex social environment can influence fitness (i.e. survival and reproductive success), which can cascade to outcomes in demography and population dynamics. Extensive research has focused on the mechanisms and drivers of fitness variation that result from differences in social structure and interactions, and separately, the effects of demography on population change. However, there have been few attempts to address the effects of social structure on population dynamics through demography. Here, we first review the effects of social structure and individual social position on fitness. We then address knowledge gaps, including the relationship between social structure and population dynamics, the carryover effects of social conditions, and the differential effects of social variables on specific demographic rates. We also review statistical tools and data requirements for the analysis of social networks and demography. We then propose that knowledge gaps could be filled by using joint modelling approaches. We used a simulation study to highlight the potential use of social networks to inform survival, a key demographic parameter. We developed a model that combines social network and survival (Cormack–Jolly–Seber) analyses and evaluated its performance to place inferences under different group structures and sampling scenarios using simulated data. Our results show that valid inferences on social and survival parameters and their connections can be achieved with realistic sample sizes, but precision is improved with more complete information (i.e. fewer missing individuals). Based on our review and simulation study, we suggest that further development of integrative modelling approaches can yield greater understanding and improved power to make predictions about the effects of social environments on populations and the feedback of population dynamics on social structure. • Social structure influences demography through fitness. • We conducted a simulation combining social network analysis and survival modelling. • Models showed minimal bias and good precision but incomplete data reduced precision. • We suggest further work to overcome limitations associated with data integration.

The important role of animal social status in vertebrate seed dispersal.

Seed dispersal directly affects plant establishment, gene flow and fitness. Understanding patterns in seed dispersal is, therefore, fundamental to understanding plant ecology and evolution, as well as addressing challenges of extinction and global change. Our ability to understand dispersal is limited because seeds may be dispersed by multiple agents, and the effectiveness of these agents can be highly variable both among and within species. We provide a novel framework that links seed dispersal to animal social status, a key component of behaviour. Because social status affects individual resource access and movement, it provides a critical link to two factors that determine seed dispersal: the quantity of seeds dispersed and the spatial patterns of dispersal. Social status may have unappreciated effects on post-dispersal seed survival and recruitment when social status affects individual habitat use. Hence, environmental changes, such as selective harvesting and urbanisation, that affect animal social structure may have unappreciated consequences for seed dispersal. This framework highlights these exciting new hypotheses linking environmental change, social structure and seed dispersal. By outlining experimental approaches to test these hypotheses, we hope to facilitate studies across a wide diversity of plant-animal networks, which may uncover emerging hotspots or significant declines in seed dispersal.

Infected or informed? Social structure and the simultaneous transmission of information and infectious disease

Social interactions present opportunities for both information and infection to spread through populations. Social learning is often proposed as a key benefit of sociality, while infectious disease spread are proposed as a major cost. Multiple empirical and theoretical studies have demonstrated the importance of social structure for the transmission of either information or harmful pathogens and parasites, but rarely in combination. We provide an overview of relevant empirical studies, discuss differences in the transmission processes of infection and information, and review how these processes have been modelled. Finally, we highlight ways in which animal social network structure and dynamics might mediate the tradeoff between the sharing of information and infection. We reveal how modular social network structures can promote the spread of information and mitigate against the spread of infection relative to other network structures. We discuss how the maintenance of long‐term social bonds, clustering of social contacts in time, and adaptive plasticity in behavioural interactions, all play important roles in influencing the transmission of information and infection. We provide novel hypotheses and suggest new directions for research that quantifies the transmission of information and infection simultaneously across different network structures to help tease apart their influence on the evolution of social behaviour.

Ant colony nest networks adapt to resource disruption.

Animal social structure is shaped by environmental conditions, such as food availability. This is important as conditions are likely to change in the future and changes to social structure can have cascading ecological effects. Wood ants are a useful taxon for the study of the relationship between social structure and environmental conditions, as some populations form large nest networks and they are ecologically dominant in many northern hemisphere woodlands. Nest networks are formed when a colony inhabits more than one nest, known as polydomy. Polydomous colonies are composed of distinct sub-colonies that inhabit spatially distinct nests and that share resources with each other. In this study, we performed a controlled experiment on 10 polydomous wood ant (Formica lugubris) colonies to test how changing the resource environment affects the social structure of a polydomous colony. We took network maps of all colonies for 5years before the experiment to assess how the networks changes under natural conditions. After this period, we prevented ants from accessing an important food source for a year in five colonies and left the other five colonies undisturbed. We found that preventing access to an important food source causes polydomous wood ant colony networks to fragment into smaller components and begin foraging on previously unused food sources. These changes were not associated with a reduction in the growth of populations inhabiting individual nests (sub-colonies), foundation of new nests or survival, when compared with control colonies. Colony splitting likely occurred as the availability of food in each nest changed causing sub-colonies to change their inter-nest connections. Consequently, our results demonstrate that polydomous colonies can adjust to environmental changes by altering their social network.

Sociodemographic factors modulate the spatial response of brown bears to vacancies created by hunting.

There is a growing recognition of the importance of indirect effects from hunting on wildlife populations, e.g. social and behavioural changes due to harvest, which occur after the initial offtake. Nonetheless, little is known about how the removal of members of a population influences the spatial configuration of the survivors. We studied how surviving brown bears (Ursus arctos) used former home ranges that had belonged to casualties of the annual bear hunting season in southcentral Sweden (2007-2015). We used resource selection functions to explore the effects of the casualty's and survivor's sex, age and their pairwise genetic relatedness, population density and hunting intensity on survivors' spatial responses to vacated home ranges. We tested the competitive release hypothesis, whereby survivors that increase their use of a killed bear's home range are presumed to have been released from intraspecific competition. We found strong support for this hypothesis, as survivors of the same sex as the casualty consistently increased their use of its vacant home range. Patterns were less pronounced or absent when the survivor and casualty were of opposite sex. Genetic relatedness between the survivor and the casualty emerged as the most important factor explaining increased use of vacated male home ranges by males, with a stronger response from survivors of lower relatedness. Relatedness was also important for females, but it did not influence use following removal; female survivors used home ranges of higher related female casualties more, both before and after death. Spatial responses by survivors were further influenced by bear age, population density and hunting intensity. We have shown that survivors exhibit a spatial response to vacated home ranges caused by hunting casualties, even in nonterritorial species such as the brown bear. This spatial reorganization can have unintended consequences for population dynamics and interfere with management goals. Altogether, our results underscore the need to better understand the short- and long-term indirect effects of hunting on animal social structure and their resulting distribution in space.

Diffusive dispersal in a growing ungulate population: guanaco expansion beyond the limits of protected areas

Growth of wild ungulate populations within protected areas can cause an expansion towards surrounding non-protected areas and lead to conflicts with human activities. The spatial and demographic structure of colonizing populations inform about their state and potential trends, since the initial colonization by dispersing individuals precedes the establishment of a population with potential for further growth and expansion. Once colonization has succeeded, the spatial pattern of animal abundance is associated with intra- and interspecific interactions and environmental factors (e.g., habitat and food availability) and the population shows similar demographic features throughout the whole occupation area, which has been called a diffusive dispersal pattern. Here, we analyze the current status of colonization by a guanaco population of ranches surrounding a protected area in Chilean Patagonia with data gathered along three consecutive years. We thus compared animal abundance and social structure between the protected and unprotected areas and evaluated throughout the whole area the effect of environmental factors on guanaco abundance, proportion of family groups, and reproductive success. Guanaco abundance significantly declined with increasing distance from the center of the local distribution and marginally with predation risk. Moreover, social structure showed only minor differences between areas, pointing to a diffusive dispersal pattern. These results suggest that the population is already well established and has the potential to grow and continue its expansion. The case exemplifies a challenging outcome of successful animal conservation, and it presents a useful approach to evaluate the state of wild ungulate populations colonizing new areas.

Understanding animal social structure: exponential random graph models in animal behaviour research

The social environment is a pervasive influence on the ecological and evolutionary dynamics of animal populations. Recently, social network analysis has provided an increasingly powerful and diverse toolset to enable animal behaviour researchers to quantify the social environment of animals and the impact that it has on ecological and evolutionary processes. However, there is considerable scope for improving these methods further. We outline an approach specifically designed to model the formation of network links, exponential random graph models (ERGMs), which have great potential for modelling animal social structure. ERGMs are generative models that treat network topology as a response variable. This makes them ideal for answering questions related directly to how and why social associations or interactions occur, from the modelling of population level transmission, through within-group behavioural dynamics to social evolutionary processes. We discuss how ERGMs have been used to study animal behaviour previously, and how recent developments in the ERGM framework can increase the scope of their use further. We also highlight the strengths and weaknesses of this approach relative to more conventional methods, and provide some guidance on the situations and research areas in which they can be used appropriately. ERGMs have the potential to be an important part of an animal behaviour researcher's toolkit and fully integrating them into the field should enhance our ability to understand what shapes animal social interactions, and identify the underlying processes that lead to the social structure of animal populations.

Automating mouse weighing in group homecages with Raspberry Pi micro-computers

Operant training systems make use of water or food restriction and make it necessary to weigh animals to ensure compliance with experimental endpoints. In other applications periodic weighing is necessary to assess drug side-effects, or as an endpoint in feeding experiments. Periodic weighing while essential can disrupt animal circadian rhythms and social structure. Automatic weighing system within paired mouse homecages. Up to 10 mice freely move between two cages (28×18×9cm) which were connected by a weighing chamber mounted on a load cell. Each mouse was identified using an RFID tag placed under the skin of the neck. A single-board computer (Raspberry Pi; RPi) controls the task, logging RFID tag, load cell weights, and time stamps from each RFID detection until the animal leaves the chamber. Collected data were statistically analyzed to estimate mouse weights. We anticipate integration with tasks where automated imaging or behaviour is assessed in homecages. Mice frequently move between the two cages, an average of 42+-16 times/day/mouse at which time we obtained weights. We report accurate determination of mouse weight and long term monitoring over 53days. Comparison with existing methods Although commercial systems are available for automatically weighing rodents, they only work with single animals, or are not open source nor cost effective for specific custom application. This automated system permits automated weighing of mice ∼40 times per day. The system employs inexpensive hardware and open-source Python code.

Personality and Social Networks: A Generative Model Approach.

Social network analysis has produced important insights regarding the causes and consequences of animal social structure. Social structure has been shown to impact longevity, reproductive success, transmission of pathogens and information, and also play important role in the evolution of cooperation. Studies of the determinants of social structure have identified environmental, genetic, and structural factors in a variety of species. At the same time, most studies in the field have been descriptive in approach, statistically identifying patterns in social networks constructed from observed interactions. We argue that there is a need for predictive theory to complement descriptive studies, moving the field from pattern to process. As an example, we provide a simple model of the effect of personality on social network structure and social role differentiation. Our model suggests that variation in behavioral types can result in variation in individual social network traits, and that some patterns found in animal networks in the wild, such as assortativity with respect to personality, may be outcomes of social inheritance and individual variation in it. Our approach and results exemplify the potential of generative models to connect individual-level processes to emergent patterns and advance our understanding of social complexity in nature.

Can survival analyses detect hunting pressure in a highly connected species? Lessons from straw-coloured fruit bats

Animal behaviour, social structure and population dynamics affect community structure, interspecific interactions, and a species' resilience to harvesting. Building on new life history information for the straw-coloured fruit bat (Eidolon helvum) from multiple localities across Africa, we used survival analyses based on tooth-cementum annuli data to test alternative hypotheses relating to hunting pressure, demography and population connectivity. The estimated annual survival probability across Africa was high (≥ 0.64), but was greatest in colonies with the highest proportion of males. This difference in sex survival, along with age and sex capture biases and out-of-phase breeding across the species' distribution, leads us to hypothesize that E. helvum has a complex social structure. We found no evidence for additive mortality in heavily hunted populations, with most colonies having high survival with constant risk of mortality despite different hunting pressure. Given E. helvum's slow life history strategy, similar survival patterns and rate among colonies suggest that local movement and regional migration may compensate for local excess hunting, but these were also not clearly detected. Our study suggests that spatio-temporal data are necessary to appropriately assess the population dynamics and conservation status of this and other species with similar traits.

The response of a sleepy lizard social network to altered ecological conditions

The use of social networks to describe animal social structure is increasing, yet our understanding of how social networks respond to changing ecological conditions remains limited. Animal behaviour is often constrained by temporal or spatial variation in ecological conditions; how do behaviour and social organization respond to changing ecological conditions? We used a social network approach to ask this question in the pair-living sleepy lizard, Tiliqua rugosa. We attached GPS data loggers to lizards to record their movement, activity and social interactions during their activity period (October–December) in 2008–2010. The years varied substantially in ecological conditions, from hot and dry in 2008 to cool and wet in 2010. Our aim was not to suggest how individual climatic or ecological factors influence social organization, but to explore the stability of social structure over varying conditions. Lizards spent less time active and overlapped in home range area more with conspecifics in the driest year of the study (2008) than in subsequent years. Despite this variation in behaviour, the number and strength of connections in the social network were stable across years. Intrasexual associations were similar across years, but there was a lower incidence of intersexual associations in 2008 than in the other 2 years. Among male–female dyads, pairing intensity was lower in 2008, while for males, extrapair strength was higher in 2008. These results suggest that although the overall social network is tolerant to changes in ecological conditions, the nature of contacts within the network shifts in response to ecological variation.

Structural balance in the social networks of a wild mammal

The social structure of a population is based on individual social associations, which can be described using network patterns (motifs). Our understanding of the forces stabilizing specific social structures in animals is limited. Structural balance theory was proposed for exploring social alliances and suggested that some network motifs are more stable than others in a society. The theory models the presence of specific triads in the network and their effect on the global population structure, based on the differential stability of specific triad configurations. While structural balance was shown in human social networks, the theory has never been tested in animal societies. Here we use empirical data from an animal social network to determine whether or not structural balance is present in a population of wild rock hyraxes, Procavia capensis. We confirm its presence and show the ability of structural balance to predict social changes resulting from local instability. We present evidence that new individuals entering the population introduce social instability, which counters the tendency of social relationships to seek balanced structures. Our findings imply that structural balance has a role in the evolution of animal social structure.

Heavy Metal Pollutants and Chemical Ecology: Exploring New Frontiers

Heavy metals are an important class of pollutants with both lethal and sublethal effects on organisms. The latter are receiving increased attention, as these may have harmful ecological outcomes. For example, recent explorations of heavy metals in freshwater habitats reveal that they can modify chemical communication between individuals, resulting in "info-disruption" that can impact ecological relationships within and between species. Info-disruption can affect animal behavior and social structure, which in turn can modify both intraspecies and interspecies interactions. In terrestrial habitats, info-disruption by metals is not well studied, but recent demonstrations of chemical signaling between plants via both roots and volatile organic molecules provide potential opportunities for info-disruption. Metals in terrestrial habitats also can form elemental plant defenses, in which they can defend a plant against natural enemies. For example, hyperaccumulation of metals by terrestrial plants has been shown to provide defensive benefits, although in almost all known cases the metals are not anthropogenic pollutants but are naturally present in soils inhabited by these plants. Info-disruption among microbes is another arena in which metal pollutants may have ecological effects, as recent discoveries regarding quorum sensing in bacteria provide an avenue for metals to affect interactions among bacteria or between bacteria and other organisms. Metal pollutants also may influence immune responses of organisms, and thus affect pathogen/host relationships. Immunomodulation (modification of immune system function) has been tied to some metal pollutants, although specific metals may boost or reduce immune system function depending on dose. Finally, the study of metal pollutants is complicated by their frequent occurrence as mixtures, either with other metals or with organic pollutants. Most studies of metal pollutants focus on single metals and therefore oversimplify complex field conditions. Study of pollutant impacts on chemical ecology also are difficult due to the necessity of studying effects at varying ecological scales: "dynamic scaling" of chemical ecology studies is rarely done completely. It is clear that much remains to be learned about how heavy metal pollution impacts organisms, and that exciting new research frontiers are available for experimental exploration.

A complex social structure with fission–fusion properties can emerge from a simple foraging model

Precisely how ecological factors influence animal social structure is far from clear. We explore this question using an agent-based model inspired by the fission–fusion society of spider monkeys (Ateles spp). Our model introduces a realistic, complex foraging environment composed of many resource patches with size varying as an inverse power law frequency distribution with exponent β. Foragers do not interact among them and start from random initial locations. They have either a complete or a partial knowledge of the environment and maximize the ratio between the size of the next visited patch and the distance traveled to it, ignoring previously visited patches. At intermediate values of β, when large patches are neither too scarce nor too abundant, foragers form groups (coincide at the same patch) with a similar size frequency distribution as the spider monkey’s subgroups. Fission–fusion events create a network of associations that contains weak bonds among foragers that meet only rarely and strong bonds among those that repeat associations more frequently than would be expected by chance. The latter form subnetworks with the highest number of bonds and a high clustering coefficient at intermediate values of β. The weak bonds enable the whole social network to percolate. Some of our results are similar to those found in long-term field studies of spider monkeys and other fission–fusion species. We conclude that hypotheses about the ecological causes of fission–fusion and the origin of complex social structures should consider the heterogeneity and complexity of the environment in which social animals live.

Testing association patterns: issues arising and extensions

A reasonable necessary condition for a population to be socially structured is that individuals associate in a nonrandom fashion. Thus, testing for preferred or avoided companions is a fundamental step in analyses of social structure (Whitehead & Dufault 1999). Cluster analyses, sociograms and their ilk (e.g. Morgan et al. 1976) all assume nonrandom associations, and if associations are random, none of these mean anything. Unfortunately testing nonrandom association on real data is not simple. A suitable test statistic is the standard deviation of the association indexes, which will be higher than expected if individuals have preferred or avoided associates. But what is ‘expected’ in the case of no preference or avoidance? The distributions of the standard deviation of association indexes, or any other suitable test statistic, are not analytically tractable under the null hypothesis. A solution is to use permutation tests in which the association data are randomized many times subject to certain constraints, each time calculating the test statistic (Manly 1997). The mean of these randomized test statistics can be considered its ‘expected value’, and a P value is then calculated as the proportion of times that the permuted statistics are more extreme than the real test statistic. A number of analyses of animal social structure have taken this approach (e.g. Whitehead et al., 1982, Smolker et al., 1992, Slooten et al., 1993 and Pepper et al., 1999). However, it was not easy to design an efficient computational routine that randomly permutes the records of which individuals were found in which groups in such a way that the number of individuals in each group and the number of groups containing each individual are both held constant. There are conceptual difficulties with such tests (Manly 1997).

Analysing animal social structure

Abstract This paper presents a framework for analysing the social structure of populations in which interactions between some identified individuals can be observed. Statistics describing the nature, quality and temporal patterning of one or more interaction measures are used to define relationships between pairs of individuals or classes of individual. Multivariate techniques can then be used to display the social structure of the population. These displays indicate the social complexity of the population and can be used to classify relationships and examine patterns of relationship between classes of animal. They can also be used to define and delineate groups. This framework and these techniques should be particularly useful when analysing complex fission–fusion societies, as are found among the primates and cetaceans. 1997 The Association for the Study of Animal Behaviour

Ethical Similarities in Human and Animal Social Structure

Ethical Similarities in Human and Animal Social Structure