All of life is social

Indirect genetic effects increase the heritable variation available to selection and are largest for behaviors: a meta-analysis

The evolutionary potential of traits is governed by the amount of heritable variation available to selection. While this is typically quantified based on genetic variation in a focal individual for its own traits (direct genetic effects, DGEs), when social interactions occur, genetic variation in interacting partners can influence a focal individual's traits (indirect genetic effects, IGEs). Theory and studies on domesticated species have suggested IGEs can greatly impact evolutionary trajectories, but whether this is true more broadly remains unclear. Here, we perform a systematic review and meta-analysis to quantify the amount of trait variance explained by IGEs and the contribution of IGEs to predictions of adaptive potential. We identified 180 effect sizes from 47 studies across 21 species and found that, on average, IGEs of a single social partner account for a small but statistically significant amount of phenotypic variation (0.03). As IGEs affect the trait values of each interacting group member and due to a typically positive-although statistically nonsignificant-correlation with DGEs (r DGE-IGE = 0.26), IGEs ultimately increase trait heritability substantially from 0.27 (narrow-sense heritability) to 0.45 (total heritable variance). This 66% average increase in heritability suggests IGEs can increase the amount of genetic variation available to selection. Furthermore, whilst showing considerable variation across studies, IGEs were most prominent for behaviors and, to a lesser extent, for reproduction and survival, in contrast to morphological, metabolic, physiological, and development traits. Our meta-analysis, therefore, shows that IGEs tend to enhance the evolutionary potential of traits, especially for those tightly related to interactions with other individuals, such as behavior and reproduction.

Plant metabolites modulate social networks and lifespan in a sawfly

Social interactions influence disease spread, information flow and resource allocation across species, yet heterogeneity in social interaction frequency and its fitness consequences are still poorly understood. Additionally, the role of exogenous chemicals, such as non-nutritive plant metabolites that are utilised by several animal species, in shaping social networks remains unclear. Here, we investigated how non-nutritive plant metabolites impact social interactions and the lifespan of the turnip sawfly, Athalia rosae. Adult sawflies acquire neo-clerodane diterpenoids ('clerodanoids') from non-food plants and this can serve as a defence against predation and increase mating success. We found intraspecific variation in clerodanoids in natural populations and laboratory-reared individuals. Clerodanoids could also be acquired from conspecifics that had prior access to the plant metabolites, which led to increased agonistic social interactions. Network analysis indicated increased social interactions in sawfly groups where some or all individuals had prior access to clerodanoids, while groups with no prior access had fewer interactions. The frequency of social interactions was influenced by the clerodanoid status of the focal individual and that of other conspecifics. Finally, we observed a shorter lifespan in adults with prior clerodanoid access when grouped with individuals without prior access, suggesting that social interactions to obtain clerodanoids have fitness costs. Our findings highlight the role of intraspecific variation in the acquisition of non-nutritional plant metabolites in shaping social networks. This variation influences individual fitness and social interactions, thereby shaping the individualised social niche.

The genetic identity of neighboring plants in intraspecific mixtures modulates disease susceptibility of both wheat and rice

Mixing crop cultivars has long been considered as a way to control epidemics at the field level and is experiencing a revival of interest in agriculture. Yet, the ability of mixing to control pests is highly variable and often unpredictable in the field. Beyond classical diversity effects such as dispersal barrier generated by genotypic diversity, several understudied processes are involved. Among them is the recently discovered neighbor-modulated susceptibility (NMS), which depicts the phenomenon that susceptibility in a given plant is affected by the presence of another healthy neighboring plant. Despite the putative tremendous importance of NMS for crop science, its occurrence and quantitative contribution to modulating susceptibility in cultivated species remains unknown. Here, in both rice and wheat inoculated in greenhouse conditions with foliar fungal pathogens considered as major threats, using more than 200 pairs of intraspecific genotype mixtures, we experimentally demonstrate the occurrence of NMS in 11% of the mixtures grown in experimental conditions that precluded any epidemics. Thus, the susceptibility of these 2 major crops results from indirect effects originating from neighboring plants. Quite remarkably, the levels of susceptibility modulated by plant-plant interactions can reach those conferred by intrinsic basal immunity. These findings open new avenues to develop more sustainable agricultural practices by engineering less susceptible crop mixtures thanks to emergent but now predictable properties of mixtures.

The importance of distinguishing individual differences in 'social impact' versus 'social responsiveness' when quantifying indirect genetic effects on the evolution of social plasticity

Social evolution and the dynamics of social interactions have previously been studied under the frameworks of quantitative genetics and behavioural ecology. In quantitative genetics, indirect genetic effects of social partners on the socially plastic phenotypes of focal individuals typically lack crucial detail already included in treatments of social plasticity in behavioural ecology. Specifically, whilst focal individuals (e.g. receivers) may show variation in their 'responsiveness' to the social environment, individual social partners (e.g. signallers) may have a differential 'impact' on focal phenotypes. Here we propose an integrative framework, that highlights the distinction between responsiveness versus impact in indirect genetic effects for a range of behavioural traits. We describe impact and responsiveness using a reaction norm approach and provide statistical models for the assessment of these effects of focal and social partner identity in different types of social interactions. By providing such a framework, we hope to stimulate future quantitative research investigating the causes and consequences of social interactions on phenotypic evolution.

Expanding the frame around social dynamics and glucocorticoids: From hierarchies within the nest to competitive interactions among species

The effect of the social environment on individual state or condition has largely focused on glucocorticoid levels (GCs). As metabolic hormones whose production can be influenced by nutritional, physical, or psychosocial stressors, GCs are a valuable (though singular) measure that may reflect the degree of "stress" experienced by an individual. Most work to date has focused on how social rank influences GCs in group-living species or how predation risk influences GCs in prey. This work has been revealing, but a more comprehensive assessment of the social environment is needed to fully understand how different features of the social environment influence GCs in both group living and non-group living species and across life history stages. Just as there can be intense within-group competition among adult conspecifics, it bears appreciating there can also be competition among siblings from the same brood, among adult conspecifics that do not live in groups, or among heterospecifics. In these situations, dominance hierarchies typically emerge, albeit, do dominants or subordinate individuals or species have higher GCs? We examine the degree of support for hypotheses derived from group-living species about whether differential GCs between dominants and subordinates reflect the "stress of subordination" or "costs of dominance" in these other social contexts. By doing so, we aim to test the generality of these two hypotheses and propose new research directions to broaden the lens that focuses on social hierarchies and GCs.

The social transmission of stress in animal collectives

The stress systems are powerful mediators between the organism's systemic dynamic equilibrium and changes in its environment beyond the level of anticipated fluctuations. Over- or under-activation of the stress systems' responses can impact an animal's health, survival and reproductive success. While physiological stress responses and their influence on behaviour and performance are well understood at the individual level, it remains largely unknown whether-and how-stressed individuals can affect the stress systems of other group members, and consequently their collective behaviour. Stressed individuals could directly signal the presence of a stressor (e.g. via an alarm call or pheromones), or an acute or chronic activation of the stress systems could be perceived by others (as an indirect cue) and spread via social contagion. Such social transmission of stress responses could then amplify the effects of stressors by impacting social interactions, social dynamics and the collective performance of groups. As the neuroendocrine pathways of the stress response are highly conserved among vertebrates, transmission of physiological stress states could be more widespread among non-human animals than previously thought. We therefore suggest that identifying the extent to which stress transmission modulates animal collectives represents an important research avenue.

Superinfection exclusion: A viral strategy with short-term benefits and long-term drawbacks

Viral superinfection occurs when multiple viral particles subsequently infect the same host. In nature, several viral species are found to have evolved diverse mechanisms to prevent superinfection (superinfection exclusion) but how this strategic choice impacts the fate of mutations in the viral population remains unclear. Using stochastic simulations, we find that genetic drift is suppressed when superinfection occurs, thus facilitating the fixation of beneficial mutations and the removal of deleterious ones. Interestingly, we also find that the competitive (dis)advantage associated with variations in life history parameters is not necessarily captured by the viral growth rate for either infection strategy. Putting these together, we then show that a mutant with superinfection exclusion will easily overtake a superinfecting population even if the latter has a much higher growth rate. Our findings suggest that while superinfection exclusion can negatively impact the long-term adaptation of a viral population, in the short-term it is ultimately a winning strategy.

Social animal models for quantifying plasticity, assortment, and selection on interacting phenotypes

Both assortment and plasticity can facilitate social evolution, as each may generate heritable associations between the phenotypes and fitness of individuals and their social partners. However, it currently remains difficult to empirically disentangle these distinct mechanisms in the wild, particularly for complex and environmentally responsive phenotypes subject to measurement error. To address this challenge, we extend the widely used animal model to facilitate unbiased estimation of plasticity, assortment and selection on social traits, for both phenotypic and quantitative genetic (QG) analysis. Our social animal models (SAMs) estimate key evolutionary parameters for the latent reaction norms underlying repeatable patterns of phenotypic interaction across social environments. As a consequence of this approach, SAMs avoid inferential biases caused by various forms of measurement error in the raw phenotypic associations between social partners. We conducted a simulation study to demonstrate the application of SAMs and investigate their performance for both phenotypic and QG analyses. With sufficient repeated measurements, we found desirably high power, low bias and low uncertainty across model parameters using modest sample and effect sizes, leading to robust predictions of selection and adaptation. Our results suggest that SAMs will readily enhance social evolutionary research on a variety of phenotypes in the wild. We provide detailed coding tutorials and worked examples for implementing SAMs in the Stan statistical programming language.

A Synthesis of Game Theory and Quantitative Genetic Models of Social Evolution

Two popular approaches for modeling social evolution, evolutionary game theory and quantitative genetics, ask complementary questions but are rarely integrated. Game theory focuses on evolutionary outcomes, with models solving for evolutionarily stable equilibria, whereas quantitative genetics provides insight into evolutionary processes, with models predicting short-term responses to selection. Here we draw parallels between evolutionary game theory and interacting phenotypes theory, which is a quantitative genetic framework for understanding social evolution. First, we show how any evolutionary game may be translated into two quantitative genetic selection gradients, nonsocial and social selection, which may be used to predict evolutionary change from a single round of the game. We show that synergistic fitness effects may alter predicted selection gradients, causing changes in magnitude and sign as the population mean evolves. Second, we show how evolutionary games involving plastic behavioral responses to partners can be modeled using indirect genetic effects, which describe how trait expression changes in response to genes in the social environment. We demonstrate that repeated social interactions in models of reciprocity generate indirect effects and conversely, that estimates of parameters from indirect genetic effect models may be used to predict the evolution of reciprocity. We argue that a pluralistic view incorporating both theoretical approaches will benefit empiricists and theorists studying social evolution. We advocate the measurement of social selection and indirect genetic effects in natural populations to test the predictions from game theory and, in turn, the use of game theory models to aid in the interpretation of quantitative genetic estimates.

Phenotypic Assortment Changes the Landscape of Selection

Social interactions with conspecifics can dramatically affect an individual's fitness. The positive or negative consequences of interacting with social partners typically depend on the value of traits that they express. These pathways of social selection connect the traits and genes expressed in some individuals to the fitness realized by others, thereby altering the total phenotypic selection on and evolutionary response of traits across the multivariate phenotype. The downstream effects of social selection are mediated by the patterns of phenotypic assortment between focal individuals and their social partners (the interactant covariance, Cij', or the multivariate form, CI). Depending on the sign and magnitude of the interactant covariance, the direction of social selection can be reinforced, reversed, or erased. We report estimates of Cij' from a variety of studies of forked fungus beetles to address the largely unexplored questions of consistency and plasticity of phenotypic assortment in natural populations. We found that phenotypic assortment of male beetles based on body size or horn length was highly variable among subpopulations, but that those differences also were broadly consistent from year to year. At the same time, the strength and direction of Cij' changed quickly in response to experimental changes in resource distribution and social properties of populations. Generally, interactant covariances were more negative in contexts in which the number of social interactions was greater in both field and experimental situations. These results suggest that patterns of phenotypic assortment could be important contributors to variability in multilevel selection through their mediation of social selection gradients.

Group size and modularity interact to shape the spread of infection and information through animal societies

Social interactions between animals can provide many benefits, including the ability to gain useful environmental information through social learning. However, these social contacts can also facilitate the transmission of infectious diseases through a population. Animals engaging in social interactions therefore face a trade-off between the potential informational benefits and the risk of acquiring disease. Theoretical models have suggested that modular social networks, associated with the formation of groups or sub-groups, can slow spread of infection by trapping it within particular groups. However, these social structures will not necessarily impact the spread of information in the same way if its transmission follows a "complex contagion", e.g. through individuals disproportionally copying the majority (conformist learning). Here we use simulation models to demonstrate that modular networks can promote the spread of information relative to the spread of infection, but only when the network is fragmented and group sizes are small. We show that the difference in transmission between information and disease is maximised for more well-connected social networks when the likelihood of transmission is intermediate. Our results have important implications for understanding the selective pressures operating on the social structure of animal societies, revealing that highly fragmented networks such as those formed in fission-fusion social groups and multilevel societies can be effective in modulating the infection-information trade-off for individuals within them.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s00265-021-03102-4.

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.

Antagonistic interactions subdue inter-species green-beard cooperation in bacteria

Cooperation can be favoured through the green-beard mechanism, where a set of linked genes encodes both a cooperative trait and a phenotypic marker (green beard), which allows carriers of the trait to selectively direct cooperative acts to other carriers. In theory, the green-beard mechanism should favour cooperation even when interacting partners are totally unrelated at the genome level. Here, we explore such an extreme green-beard scenario between two unrelated bacterial species-Pseudomonas aeruginosa and Burkholderia cenocepacia, which share a cooperative locus encoding the public good pyochelin (an iron-scavenging siderophore) and its cognate receptor (green beard) required for iron-pyochelin uptake. We show that pyochelin, when provided in cell-free supernatants, can be mutually exchanged between species and provide fitness benefits under iron limitation. However, in co-culture we observed that these cooperative benefits vanished and communities were dominated by P. aeruginosa, regardless of strain background and species starting frequencies. Our results further suggest that P. aeruginosa engages in interference competition to suppress B. cenocepacia, indicating that inter-species conflict arising from dissimilarities at the genome level overrule the aligned cooperative interests at the pyochelin locus. Thus, green-beard cooperation is subdued by competition, indicating that interspecific siderophore cooperation is difficult to evolve and to be maintained.

The performance of permutations and exponential random graph models when analyzing animal networks

Social network analysis is a suite of approaches for exploring relational data. Two approaches commonly used to analyze animal social network data are permutation-based tests of significance and exponential random graph models. However, the performance of these approaches when analyzing different types of network data has not been simultaneously evaluated. Here we test both approaches to determine their performance when analyzing a range of biologically realistic simulated animal social networks. We examined the false positive and false negative error rate of an effect of a two-level explanatory variable (e.g., sex) on the number and combined strength of an individual’s network connections. We measured error rates for two types of simulated data collection methods in a range of network structures, and with/without a confounding effect and missing observations. Both methods performed consistently well in networks of dyadic interactions, and worse on networks constructed using observations of individuals in groups. Exponential random graph models had a marginally lower rate of false positives than permutations in most cases. Phenotypic assortativity had a large influence on the false positive rate, and a smaller effect on the false negative rate for both methods in all network types. Aspects of within- and between-group network structure influenced error rates, but not to the same extent. In "grouping event-based" networks, increased sampling effort marginally decreased rates of false negatives, but increased rates of false positives for both analysis methods. These results provide guidelines for biologists analyzing and interpreting their own network data using these methods.

Evolutionary dynamics drives role specialization in a community of players

The progression of game theory from classical to evolutionary and spatial games provided a powerful means to study cooperation, and enabled a better understanding of general cooperation-promoting mechanisms. However, current standard models assume that at any given point players must choose either cooperation or defection, meaning that regardless of the spatial structure in which they exist, they cannot differentiate between their neighbours and adjust their behaviour accordingly. This is at odds with interactions among organisms in nature who are well capable of behaving differently towards different members of their communities. We account for this natural fact by introducing a new type of player-dubbed link players-who can adjust their behaviour to each individual neighbour. This is in contrast to more common node players whose behaviour affects all neighbours in the same way. We proceed to study cooperation in pure and mixed populations, showing that cooperation peaks at moderately low densities of link players. In such conditions, players naturally specialize in different roles. Node players tend to be either cooperators or defectors, while link players form social insulation between cooperative and defecting clusters by acting both as cooperators and defectors. Such fairly complex processes emerging from a simple model reflect some of the complexities observed in experimental studies on social behaviour in microbes and pave a way for the development of richer game models.

Insights from the study of complex systems for the ecology and evolution of animal populations

Populations of animals comprise many individuals, interacting in multiple contexts, and displaying heterogeneous behaviors. The interactions among individuals can often create population dynamics that are fundamentally deterministic yet display unpredictable dynamics. Animal populations can, therefore, be thought of as complex systems. Complex systems display properties such as nonlinearity and uncertainty and show emergent properties that cannot be explained by a simple sum of the interacting components. Any system where entities compete, cooperate, or interfere with one another may possess such qualities, making animal populations similar on many levels to complex systems. Some fields are already embracing elements of complexity to help understand the dynamics of animal populations, but a wider application of complexity science in ecology and evolution has not occurred. We review here how approaches from complexity science could be applied to the study of the interactions and behavior of individuals within animal populations and highlight how this way of thinking can enhance our understanding of population dynamics in animals. We focus on 8 key characteristics of complex systems: hierarchy, heterogeneity, self-organization, openness, adaptation, memory, nonlinearity, and uncertainty. For each topic we discuss how concepts from complexity theory are applicable in animal populations and emphasize the unique insights they provide. We finish by outlining outstanding questions or predictions to be evaluated using behavioral and ecological data. Our goal throughout this article is to familiarize animal ecologists with the basics of each of these concepts and highlight the new perspectives that they could bring to variety of subfields.

Personality variation improves collective decision-making in cockroaches

Many animals live in groups and engage in collective actions which can enhance their fitness. One common example is collective decision-making, which mainly arises from social interactions that modify the individual behaviour. Despite the widespread interest in animal personalities on the one hand and in social effects (such as social organisation, social learning or anti-predator behaviour) on the other, the question of how the amount of among-individual differences, coupled with social interactions, influence group cohesion has rarely been addressed. For this purpose, I used a modelling approach based on aggregation behaviour of cockroaches to explore the mechanisms underlying such context-dependent behaviour. The results of simulations considering different degrees (none, medium, high) of personality variation in a non-social and social context were compared to experimental patterns of aggregation dynamics in cockroaches. The comparison between the simulated and experimental data show that only a model that considers differences in individuals was able to reproduce the experimental patterns of individuals and groups. In addition, the comparison between models suggest that some individuals may play a keystone role during aggregation dynamics, influencing the behaviour of others and facilitating the collective decision. Finally, I show that personality variation amplifies the effects of social inter-attractions, thus increasing the speed of aggregation, shedding light on the mechanisms underpinning social modification of individual behaviour.

Deconstructing Evolutionary Game Theory: Coevolution of Social Behaviors with Their Evolutionary Setting

Evolution of social behaviors is one of the most fascinating and active fields of evolutionary biology. During the past half century, social evolution theory developed into a mature field with powerful tools to understand the dynamics of social traits such as cooperation under a wide range of conditions. In this article, I argue that the next stage in the development of social evolution theory should consider the evolution of the setting in which social behaviors evolve. To that end, I propose a conceptual map of the components that make up the evolutionary setting of social behaviors, review existing work that considers the evolution of each component, and discuss potential future directions. The theoretical work reviewed here illustrates how unexpected dynamics can happen when the setting of social evolution itself is evolving, such as cooperation sometimes being self-limiting. I argue that a theory of how the setting of social evolution itself evolves will lead to a deeper understanding of when cooperation and other social behaviors evolve and diversify.

Assessing the repeatability, robustness to disturbance, and parent-offspring colony resemblance of collective behavior

Groups of animals possess phenotypes such as collective behaviour, which may determine the fitness of group members. However, the stability and robustness to perturbations of collective phenotypes in natural conditions is not established. Furthermore, whether group phenotypes are transmitted from parent to offspring groups with fidelity is required for understanding how selection on group phenotypes contributes to evolution, but parent-offspring resemblance at the group level is rarely estimated. We evaluated the repeatability, robustness to perturbation and parent-offspring resemblance of collective foraging aggressiveness in colonies of the social spider Anelosimus eximius. Among-colony differences in foraging aggressiveness were consistent over time but changed if the colony was perturbed through the removal of individuals or via individuals' removal and subsequent return. Offspring and parent colony behaviour were correlated at the phenotypic level, but only once the offspring colony had settled after being translocated, and the correlation overlapped with zero at the among-colony level. The parent-offspring resemblance was not driven by a shared elevation but could be due to other environmental factors. The behaviour of offspring colonies in a common garden laboratory setting was not correlated with the behaviour of the parent colony nor with the same colony's behaviour once it was returned to the field. The phenotypes of groups represent a potentially important tier of biological organization, and assessing the stability and heritability of such phenotypes helps us better understand their role in evolution.

Transcriptomic basis and evolution of the ant nurse-larval social interactome

Development is often strongly regulated by interactions among close relatives, but the underlying molecular mechanisms are largely unknown. In eusocial insects, interactions between caregiving worker nurses and larvae regulate larval development and resultant adult phenotypes. Here, we begin to characterize the social interactome regulating ant larval development by collecting and sequencing the transcriptomes of interacting nurses and larvae across time. We find that the majority of nurse and larval transcriptomes exhibit parallel expression dynamics across larval development. We leverage this widespread nurse-larva gene co-expression to infer putative social gene regulatory networks acting between nurses and larvae. Genes with the strongest inferred social effects tend to be peripheral elements of within-tissue regulatory networks and are often known to encode secreted proteins. This includes interesting candidates such as the nurse-expressed giant-lens, which may influence larval epidermal growth factor signaling, a pathway known to influence various aspects of insect development. Finally, we find that genes with the strongest signatures of social regulation tend to experience relaxed selective constraint and are evolutionarily young. Overall, our study provides a first glimpse into the molecular and evolutionary features of the social mechanisms that regulate all aspects of social life.

Transcriptomic basis and evolution of the ant nurse-larval social interactome

Development is often strongly regulated by interactions among close relatives, but the underlying molecular mechanisms are largely unknown. In eusocial insects, interactions between caregiving worker nurses and larvae regulate larval development and resultant adult phenotypes. Here, we begin to characterize the social interactome regulating ant larval development by collecting and sequencing the transcriptomes of interacting nurses and larvae across time. We find that the majority of nurse and larval transcriptomes exhibit parallel expression dynamics across larval development. We leverage this widespread nurse-larva gene co-expression to infer putative social gene regulatory networks acting between nurses and larvae. Genes with the strongest inferred social effects tend to be peripheral elements of within-tissue regulatory networks and are often known to encode secreted proteins. This includes interesting candidates such as the nurse-expressed giant-lens, which may influence larval epidermal growth factor signaling, a pathway known to influence various aspects of insect development. Finally, we find that genes with the strongest signatures of social regulation tend to experience relaxed selective constraint and are evolutionarily young. Overall, our study provides a first glimpse into the molecular and evolutionary features of the social mechanisms that regulate all aspects of social life.

Offspring genetic effects on maternal care

Parental care is found widely across animal taxa and is manifest in a range of behaviours from basic provisioning in cockroaches to highly complex behaviours seen in mammals. The evolution of parental care is viewed as the outcome of an evolutionary cost/benefit trade-off between investing in current and future offspring, leading to the selection of traits in offspring that influence parental behaviour. Thus, level and quality of parental care are affected by both parental and offspring genetic differences that directly and indirectly influence parental care behaviour. While significant research effort has gone into understanding how parental genomes affect parental, and mostly maternal, behaviour, few studies have investigated how offspring genomes affect parental care. In this review, we bring together recent findings across different fields focussing on the mechanism and genetics of offspring effects on maternal care in mammals.

Multiple infection of cells changes the dynamics of basic viral evolutionary processes

The infection of cells by multiple copies of a given virus can impact viral evolution in a variety of ways, yet some of the most basic evolutionary dynamics remain underexplored. Using computational models, we investigate how infection multiplicity affects the fixation probability of mutants, the rate of mutant generation, and the timing of mutant invasion. An important insight from these models is that for neutral and disadvantageous phenotypes, rare mutants initially enjoy a fitness advantage in the presence of multiple infection of cells. This arises because multiple infection allows the rare mutant to enter more target cells and to spread faster, while it does not accelerate the spread of the resident wild-type virus. The rare mutant population can increase by entry into both uninfected and wild-type-infected cells, while the established wild-type population can initially only grow through entry into uninfected cells. Following this initial advantageous phase, the dynamics are governed by drift or negative selection, respectively, and a higher multiplicity reduces the chances that mutants fix in the population. Hence, while increased infection multiplicity promotes the presence of neutral and disadvantageous mutants in the short-term, it makes it less likely in the longer term. We show how these theoretical insights can be useful for the interpretation of experimental data on virus evolution at low and high multiplicities. The dynamics explored here provide a basis for the investigation of more complex viral evolutionary processes, including recombination, reassortment, as well as complementary/inhibitory interactions.

Modelling the co-evolution of indirect genetic effects and inherited variability

When individuals interact, their phenotypes may be affected not only by their own genes but also by genes in their social partners. This phenomenon is known as Indirect Genetic Effects (IGEs). In aquaculture species and some plants, however, competition not only affects trait levels of individuals, but also inflates variability of trait values among individuals. In the field of quantitative genetics, the variability of trait values has been studied as a quantitative trait in itself, and is often referred to as inherited variability. Such studies, however, consider only the genetic effect of the focal individual on trait variability and do not make a connection to competition. Although the observed phenotypic relationship between competition and variability suggests an underlying genetic relationship, the current quantitative genetic models of IGE and inherited variability do not allow for such a relationship. The lack of quantitative genetic models that connect IGEs to inherited variability limits our understanding of the potential of variability to respond to selection, both in nature and agriculture. Models of trait levels, for example, show that IGEs may considerably change heritable variation in trait values. Currently, we lack the tools to investigate whether this result extends to variability of trait values. Here we present a model that integrates IGEs and inherited variability. In this model, the target phenotype, say growth rate, is a function of the genetic and environmental effects of the focal individual and of the difference in trait value between the social partner and the focal individual, multiplied by a regression coefficient. The regression coefficient is a genetic trait, which is a measure of cooperation; a negative value indicates competition, a positive value cooperation, and an increasing value due to selection indicates the evolution of cooperation. In contrast to the existing quantitative genetic models, our model allows for co-evolution of IGEs and variability, as the regression coefficient can respond to selection. Our simulations show that the model results in increased variability of body weight with increasing competition. When competition decreases, i.e., cooperation evolves, variability becomes significantly smaller. Hence, our model facilitates quantitative genetic studies on the relationship between IGEs and inherited variability. Moreover, our findings suggest that we may have been overlooking an entire level of genetic variation in variability, the one due to IGEs.

The early-life environment of a pig shapes the phenotypes of its social partners in adulthood

Social interactions among individuals are abundant, both in natural and domestic populations, and may affect phenotypes of individuals. Recent research has demonstrated that the social effect of an individual on the phenotype of its social partners may have a genetic component, known as an indirect genetic effect (IGE). Little is known, however, of nongenetic factors underlying such social effects. Early-life environments often have large effects on phenotypes of the individuals themselves later in life. Offspring development in many mammalian species, for example, depends on interactions with the mother and siblings. In domestic pigs, individuals sharing the same juvenile environment develop similar body weight later in life. We, therefore, hypothesized that offspring originating from the same early-life environment also develop common social skills that generate early-life social effects (ELSEs) that affect the phenotypes of their social partners later in life. We, therefore, quantified IGEs and ELSEs on growth in domestic pigs. Results show that individuals from the same early-life environment express similar social effects on the growth of their social partners, and that such ELSEs shape the growth rate of social partners more than IGEs. Thus, the social skills that individuals develop in early life have a long-lasting impact on the phenotypes of social partners. Early-life and genetic social effects were independent of the corresponding direct effects of offspring on their own growth, indicating that individuals may enhance the growth of their social partners without a personal cost. Our findings also illustrate how research devoted to quantifying IGEs may miss nongenetic and potentially confounded social mechanisms which may bias the estimates of IGEs.

Social Interactions and Indirect Genetic Effects on Complex Juvenile and Adult Traits

Most animal species are social in one form or another, yet many studies in rodent model systems use either individually housed animals or ignore potential confounds caused by group housing. While such social interaction effects on developmental and behavioral traits are well established, the genetic basis of social interactions has not been researched in as much detail. Specifically, the effects of genetic variation in social partners on the phenotype of a focal individual have mostly been studied at the phenotypic level. Such indirect genetic effects (IGEs), where the genotype of one individual influences the phenotype of a second individual, can have important evolutionary and medically relevant consequences. In this chapter, we give a brief outline of social interaction effects, and how systems genetics approaches using recombinant inbred populations can be used to investigate indirect genetic effects specifically, including maternal genetic effects. We discuss experimental designs for the study of IGEs and show how indirect genetic loci can be identified that underlie social interaction effects, their mechanisms, and consequences for trait variation in focal individuals.

Indirect genetic effects for growth rate in domestic pigs alter aggressive and manipulative biting behaviour

Indirect genetic effects (IGEs) are heritable effects of an individual on phenotypic values of others, and may result from social interactions. We determined the behavioural consequences of selection for IGEs for growth (IGEg) in pigs in a G × E treatment design. Pigs (n = 480) were selected for high versus low IGEg with a contrast of 14 g average daily gain and were housed in either barren or straw-enriched pens (n = 80). High IGEg pigs showed from 8 to 23 weeks age 40 % less aggressive biting (P = 0.006), 27 % less ear biting (P = 0.03), and 40 % less biting on enrichment material (P = 0.005). High IGEg pigs had a lower tail damage score (high 2.0; low 2.2; P = 0.004), and consumed 30 % less jute sacks (P = 0.002). Selection on high IGEg reduced biting behaviours additive to the, generally much larger, effects of straw-bedding (P < 0.01), with no G × E interactions. These results show opportunities to reduce harmful biting behaviours in pigs.

Indirect genetic effects from competition in the clonal herb Sedum album (Crassulaceae)

Recent years have seen increasing interest in indirect genetic effects, i.e. influences on the phenotype that depend on the genotype of other conspecific individuals; however, the empirical evidence for such effects is still limited, especially in wild plant species. The present study of the clonal herb Sedum album assessed direct and indirect genetic effects on performance-related traits in a 4-year experiment with clonally replicated genotypes, grown in pairs and differing in anthocyanin pigmentation to allow separation of individuals during data collection. In agreement with the existence of indirect genetic effects, the experimentally-paired plants not only expressed their own genotype but were also affected by the genotype of their pair mate. The effect of neighbour genotype explained up to one-fourth of the variation in performance and most likely resulted from competition, imposed by the close physical contact between paired individuals and the limiting conditions used in the garden environment. Indirect genetic effects from competition have the potential to enhance the efficacy of group-level selection relative to individual selection, given the nutrient-poor and spatially-confined substrate available to plants of S. album in the natural habitat.

Indirect genetic effects contribute substantially to heritable variation in aggression-related traits in group-housed mink (Neovison vison)

BACKGROUND

Since the recommendations on group housing of mink (Neovison vison) were adopted by the Council of Europe in 1999, it has become common in mink production in Europe. Group housing is advantageous from a production perspective, but can lead to aggression between animals and thus raises a welfare issue. Bite marks on the animals are an indicator of this aggressive behaviour and thus selection against frequency of bite marks should reduce aggression and improve animal welfare. Bite marks on one individual reflect the aggression of its group members, which means that the number of bite marks carried by one individual depends on the behaviour of other individuals and that it may have a genetic basis. Thus, for a successful breeding strategy it could be crucial to consider both direct (DGE) and indirect (IGE) genetic effects on this trait. However, to date no study has investigated the genetic basis of bite marks in mink.

RESULT AND DISCUSSION

A model that included DGE and IGE fitted the data significantly better than a model with DGE only, and IGE contributed a substantial proportion of the heritable variation available for response to selection. In the model with IGE, the total heritable variation expressed as the proportion of phenotypic variance (T2) was six times greater than classical heritability (h2). For instance, for total bite marks, T2 was equal to 0.61, while h2 was equal to 0.10. The genetic correlation between direct and indirect effects ranged from 0.55 for neck bite marks to 0.99 for tail bite marks. This positive correlation suggests that mink have a tendency to fight in a reciprocal way (giving and receiving bites) and thus, a genotype that confers a tendency to bite other individuals can also cause its bearer to receive more bites.

CONCLUSION

Both direct and indirect genetic effects contribute to variation in number of bite marks in group-housed mink. Thus, a genetic selection design that includes both direct genetic and indirect genetic effects could reduce the frequency of bite marks and probably aggression behaviour in group-housed mink.

Indirect genetic effects and kin recognition: estimating IGEs when interactions differ between kin and strangers

Social interactions among individuals are widespread, both in natural and domestic populations. As a result, trait values of individuals may be affected by genes in other individuals, a phenomenon known as indirect genetic effects (IGEs). IGEs can be estimated using linear mixed models. The traditional IGE model assumes that an individual interacts equally with all its partners, whether kin or strangers. There is abundant evidence, however, that individuals behave differently towards kin as compared with strangers, which agrees with predictions from kin-selection theory. With a mix of kin and strangers, therefore, IGEs estimated from a traditional model may be incorrect, and selection based on those estimates will be suboptimal. Here we investigate whether genetic parameters for IGEs are statistically identifiable in group-structured populations when IGEs differ between kin and strangers, and develop models to estimate such parameters. First, we extend the definition of total breeding value and total heritable variance to cases where IGEs depend on relatedness. Next, we show that the full set of genetic parameters is not identifiable when IGEs differ between kin and strangers. Subsequently, we present a reduced model that yields estimates of the total heritable effects on kin, on non-kin and on all social partners of an individual, as well as the total heritable variance for response to selection. Finally we discuss the consequences of analysing data in which IGEs depend on relatedness using a traditional IGE model, and investigate group structures that may allow estimation of the full set of genetic parameters when IGEs depend on kin.

The quantitative genetics of indirect genetic effects: a selective review of modelling issues

Indirect genetic effects (IGE) occur when the genotype of an individual affects the phenotypic trait value of another conspecific individual. IGEs can have profound effects on both the magnitude and the direction of response to selection. Models of inheritance and response to selection in traits subject to IGEs have been developed within two frameworks; a trait-based framework in which IGEs are specified as a direct consequence of individual trait values, and a variance-component framework in which phenotypic variance is decomposed into a direct and an indirect additive genetic component. This work is a selective review of the quantitative genetics of traits affected by IGEs, with a focus on modelling, estimation and interpretation issues. It includes a discussion on variance-component vs trait-based models of IGEs, a review of issues related to the estimation of IGEs from field data, including the estimation of the interaction coefficient Ψ (psi), and a discussion on the relevance of IGEs for response to selection in cases where the strength of interaction varies among pairs of individuals. An investigation of the trait-based model shows that the interaction coefficient Ψ may deviate considerably from the corresponding regression coefficient when feedback occurs. The increasing research effort devoted to IGEs suggests that they are a widespread phenomenon, probably particularly in natural populations and plants. Further work in this field should considerably broaden our understanding of the quantitative genetics of inheritance and response to selection in relation to the social organisation of populations.

Genetic control of interactions among individuals: contrasting outcomes of indirect genetic effects arising from neighbour disease infection and competition in a forest tree

Indirect genetic effects (IGEs) are heritable effects of individuals on trait values of their conspecifics. IGEs may substantially affect response to selection, but empirical studies on IGEs are sparse and their magnitude and correlation with direct genetic effects are largely unknown in plants. Here we used linear mixed models to estimate genetic (co)variances attributable to direct and indirect effects for growth and foliar disease damage in a large pedigreed population of Eucalyptus globulus. We found significant IGEs for growth and disease damage, which increased with age for growth. The correlation between direct and indirect genetic effects was highly negative for growth, but highly positive for disease damage, consistent with neighbour competition and infection, respectively. IGEs increased heritable variation by 71% for disease damage, but reduced heritable variation by 85% for growth, leaving nonsignificant heritable variation for later age growth. Thus, IGEs are likely to prevent response to selection in growth, despite a considerable ordinary heritability. IGEs change our perspective on the genetic architecture and potential response to selection. Depending on the correlation between direct and indirect genetic effects, IGEs may enhance or diminish the response to natural or artificial selection compared with that predicted from ordinary heritability.

Indirect genetic effects for survival in domestic chickens (Gallus gallus) are magnified in crossbred genotypes and show a parent-of-origin effect

Through social interactions, individuals can affect one another's phenotype. The heritable effect of an individual on the phenotype of a conspecific is known as an indirect genetic effect (IGE). Although IGEs can have a substantial impact on heritable variation and response to selection, little is known about the genetic architecture of traits affected by IGEs. We studied IGEs for survival in domestic chickens (Gallus gallus), using data on two purebred lines and their reciprocal cross. Birds were kept in groups of four. Feather pecking and cannibalism caused mortality, as beaks were kept intact. Survival time was shorter in crossbreds than in purebreds, indicating outbreeding depression and the presence of nonadditive genetic effects. IGEs contributed the majority of heritable variation in crossbreds (87 and 72%) and around half of heritable variation in purebreds (65 and 44%). There was no evidence of dominance variance, neither direct nor indirect. Absence of dominance variance in combination with considerable outbreeding depression suggests that survival is affected by many loci. Direct-indirect genetic correlations were moderately to highly negative in crossbreds (-0.37 ± 0.17 and -0.83 ± 0.10), but low and not significantly different from zero in purebreds (0.20 ± 0.21 and -0.28 ± 0.18). Consequently, unlike purebreds, crossbreds would fail to respond positively to mass selection. The direct genetic correlation between both crosses was high (0.95 ± 0.23), whereas the indirect genetic correlation was moderate (0.41 ± 0.26). Thus, for IGEs, it mattered which parental line provided the sire and which provided the dam. This indirect parent-of-origin effect appeared to be paternally transmitted and is probably Z chromosome linked.

[Bacterial quorum sensing in an evolutionary perspective]

In contrast to the individual and nonsocial organism view of bacteria, recent discoveries show that bacteria can communicate and exhibit population behaviour via a system known as quorum sensing. Some bacterial behaviour can only be initiated when the cell number reaches a certain level (Quorum sensing, QS). It is generally believed that quorum sensing is used to coordinate cooperative behaviours at the population level; however, many issues exist regarding the evolution or development of such a system. In the present paper, the evolutionary process of bacterial quorum-sensing systems is discussed based on recent events and progresses in this field. As quorum sensing systems are often affected by environ-mental factors, such as temperature, pH, and nutrient levels, it is hence proposed that the evolution of bacterial cooperation, such as the quorum sensing, is rather a dynamic and ever-changing process which is radically affected by environmental conditions, genetic exchanges, as well as by changes in microbial community. The dynamic transformation suggests the advantages of cheaters of the system might have been short-lasted and confined in certain conditions and diminish over a long run.

A general definition of the heritable variation that determines the potential of a population to respond to selection

Genetic selection is a major force shaping life on earth. In classical genetic theory, response to selection is the product of the strength of selection and the additive genetic variance in a trait. The additive genetic variance reflects a population's intrinsic potential to respond to selection. The ordinary additive genetic variance, however, ignores the social organization of life. With social interactions among individuals, individual trait values may depend on genes in others, a phenomenon known as indirect genetic effects. Models accounting for indirect genetic effects, however, lack a general definition of heritable variation. Here I propose a general definition of the heritable variation that determines the potential of a population to respond to selection. This generalizes the concept of heritable variance to any inheritance model and level of organization. The result shows that heritable variance determining potential response to selection is the variance among individuals in the heritable quantity that determines the population mean trait value, rather than the usual additive genetic component of phenotypic variance. It follows, therefore, that heritable variance may exceed phenotypic variance among individuals, which is impossible in classical theory. This work also provides a measure of the utilization of heritable variation for response to selection and integrates two well-known models of maternal genetic effects. The result shows that relatedness between the focal individual and the individuals affecting its fitness is a key determinant of the utilization of heritable variance for response to selection.

Fitness consequences of social network position in a wild population of forked fungus beetles (Bolitotherus cornutus)

Social networks describe the pattern of intraspecific interactions within a population. An individual's position in a social network often is expected to influence its fitness, but only a few studies have examined this relationship in natural populations. We investigated the fitness consequences of network position in a wild beetle population. Copulation success of male beetles positively covaried with strength (a measure of network centrality) and negatively covaried with clustering coefficient (CC) (a measure of cliquishness). Further analysis using mediation path models suggested that the activity level of individuals drove the relationships between strength and fitness almost entirely. In contrast, selection on CC was not explained by individual behaviours. Although our data suggest that social network position can experience strong sexual selection, it is also clear that the relationships between fitness and some network metrics merely reflect variation in individual-level behaviours.

Interacting phenotypes and the evolutionary process. III. Social evolution

Interactions among conspecifics influence social evolution through two distinct but intimately related paths. First, they provide the opportunity for indirect genetic effects (IGEs), where genes expressed in one individual influence the expression of traits in others. Second, interactions can generate social selection when traits expressed in one individual influence the fitness of others. Here, we present a quantitative genetic model of multivariate trait evolution that integrates the effects of both IGEs and social selection, which have previously been modeled independently. We show that social selection affects evolutionary change whenever the breeding value of one individual covaries with the phenotype of its social partners. This covariance can be created by both relatedness and IGEs, which are shown to have parallel roles in determining evolutionary response. We show that social selection is central to the estimation of inclusive fitness and derive a version of Hamilton's rule showing the symmetrical effects of relatedness and IGEs on the evolution of altruism. We illustrate the utility of our approach using altruism, greenbeards, aggression, and weapons as examples. Our model provides a general predictive equation for the evolution of social phenotypes that encompasses specific cases such as kin selection and reciprocity. The parameters can be measured empirically, and we emphasize the importance of considering both IGEs and social selection, in addition to relatedness, when testing hypotheses about social evolution.

Social aggregation in the pelagic zone with special reference to fish and invertebrates

Aggregations of organisms, ranging from zooplankton to whales, are an extremely common phenomenon in the pelagic zone; perhaps the best known are fish schools. Social aggregation is a special category that refers to groups that self-organize and maintain cohesion to exploit benefits such as protection from predators, and location and capture of resources more effectively and with greater energy efficiency than could a solitary individual. In this review we explore general aggregation principles, with specific reference to pelagic organisms; describe a range of new technologies either designed for studying aggregations or that could potentially be exploited for this purpose; report on the insights gained from theoretical modelling; discuss the relationship between social aggregation and ocean management; and speculate on the impact of climate change. Examples of aggregation occur in all animal phyla. Among pelagic organisms, it is possible that repeated co-occurrence of stable pairs of individuals, which has been established for some schooling fish, is the likely precursor leading to networks of social interaction and more complex social behaviour. Social network analysis has added new insights into social behaviour and allows us to dissect aggregations and to examine how the constituent individuals interact with each other. This type of analysis is well advanced in pinnipeds and cetaceans, and work on fish is progressing. Detailed three-dimensional analysis of schools has proved to be difficult, especially at sea, but there has been some progress recently. The technological aids for studying social aggregation include video and acoustics, and have benefited from advances in digitization, miniaturization, motion analysis and computing power. New techniques permit three-dimensional tracking of thousands of individual animals within a single group which has allowed novel insights to within-group interactions. Approaches using theoretical modelling of aggregations have a long history but only recently have hypotheses been tested empirically. The lack of synchrony between models and empirical data, and lack of a common framework to schooling models have hitherto hampered progress; however, recent developments in this field offer considerable promise. Further, we speculate that climate change, already having effects on ecosystems, could have dramatic effects on aggregations through its influence on species composition by altering distribution ranges, migration patterns, vertical migration, and oceanic acidity. Because most major commercial fishing targets schooling species, these changes could have important consequences for the dependent businesses.

Multilevel selection 4: modeling the relationship of indirect genetic effects and group size

Indirect genetic effects (IGE) occur when individual trait values depend on genes in others. With IGEs, heritable variance and response to selection depend on the relationship of IGEs and group size. Here I propose a model for this relationship, which can be implemented in standard restricted maximum likelihood software.

What the hyena's laugh tells: sex, age, dominance and individual signature in the giggling call of Crocuta crocuta

BACKGROUND

Among mammals living in social groups, individuals form communication networks where they signal their identity and social status, facilitating social interaction. In spite of its importance for understanding of mammalian societies, the coding of individual-related information in the vocal signals of non-primate mammals has been relatively neglected. The present study focuses on the spotted hyena Crocuta crocuta, a social carnivore known for its complex female-dominated society. We investigate if and how the well-known hyena's laugh, also known as the giggle call, encodes information about the emitter.

RESULTS

By analyzing acoustic structure in both temporal and frequency domains, we show that the hyena's laugh can encode information about age, individual identity and dominant/subordinate status, providing cues to receivers that could enable assessment of the social position of an emitting individual.

CONCLUSIONS

The range of messages encoded in the hyena's laugh is likely to play a role during social interactions. This call, together with other vocalizations and other sensory channels, should ensure an array of communication signals that support the complex social system of the spotted hyena. Experimental studies are now needed to decipher precisely the communication network of this species.

Reproductive conflict delays the recovery of an endangered social species

1. Evolutionary theory predicts that individuals, in order to increase their relative fitness, can evolve behaviours that are detrimental for the group or population. This mismatch is particularly visible in social organisms. Despite its potential to affect the population dynamics of social animals, this principle has not yet been applied to real-life conservation. 2. Social group structure has been argued to stabilize population dynamics due to the buffering effects of nonreproducing subordinates. However, competition for breeding positions in such species can also interfere with the reproduction of breeding pairs. 3. Seychelles magpie robins, Copsychus sechellarum, live in social groups where subordinate individuals do not breed. Analysis of long-term individual-based data and short-term behavioural observations show that subordinates increase the territorial takeover frequency of established breeders. Such takeovers delay offspring production and decrease territory productivity. 4. Individual-based simulations of the Seychelles magpie robin population parameterized with the long-term data show that this process has significantly postponed the recovery of the species from the Critically Endangered status. 5. Social conflict thus can extend the period of high extinction risk, which we show to have population consequences that should be taken into account in management programmes. This is the first quantitative assessment of the effects of social conflict on conservation.