Interacting Phenotypes and the Evolutionary Process. II. Selection Resulting from Social Interactions

Genetic Variation in Male Aggression Is Influenced by Genotype of Prior Social Partners in Drosophila melanogaster

AbstractSocial behaviors can be influenced by the genotypes of interacting individuals through indirect genetic effects (IGEs) and can also display developmental plasticity. We investigated how developmental IGEs, which describe the effects of a prior social partner's genotype on later behavior, can influence aggression in male Drosophila melanogaster. We predicted that developmental IGEs cannot be estimated by simply extending the effects of contextual IGEs over time and instead have their own unique effects on behavior. On day 1 of the experiment, we measured aggressive behavior in 15 genotypic pairings (n = 600 males). On day 2, each of the males was paired with a new opponent, and aggressive behavior was again measured. We found contextual IGEs on day 1 of the experiment and developmental IGEs on day 2 of the experiment: the influence of the day 1 partner's genotype on the focal individual's day 2 behavior depended on the genotypic identity of both the day 1 partner and the focal male. Importantly, the developmental IGEs in our system produced fundamentally different dynamics than the contextual IGEs, as the presence of IGEs was altered over time. These findings represent some of the first empirical evidence demonstrating developmental IGEs, a first step toward incorporating developmental IGEs into our understanding of behavioral evolution.

Indirect genetic effects should make group size more evolvable than expected

Group size is an important trait for many ecological and evolutionary processes. However, it is not a trait possessed by individuals but by social groups, and as many genomes contribute to group size understanding its genetic underpinnings and so predicting its evolution is a conceptual challenge. Here I suggest how group size can be modelled as a joint phenotype of multiple individuals, and so how models for evolution accounting for indirect genetic effects are essential for understanding the genetic variance of group size. This approach makes it clear that (a) group size should have a larger genetic variance than initially expected as indirect genetic effects always contribute exactly as much as direct genetic effects and (b) the response to selection of group size should be faster than expected based on direct genetic variance alone as the correlation between direct and indirect effects is always at the maximum positive limit of 1. Group size should therefore show relatively rapid evolved increases and decreases, the consequences of which and evidence for I discuss.

Metabolic scaling as an emergent outcome of variation in metabolic rate

The allometric scaling of metabolic rate and what drives it are major questions in biology with a long history. Since the metabolic rate at any level of biological organization is an emergent property of its lower-level constituents, it is an outcome of the intrinsic heterogeneity among these units and the interactions among them. However, the influence of lower-level heterogeneity on system-level metabolic rate is difficult to investigate, given the tightly integrated body plan of unitary organisms. In this context, social insects such as honeybees can serve as important model systems because unlike unitary organisms, these superorganisms can be taken apart and reassembled in different configurations to study metabolic rate and its various drivers at different levels of organization. This commentary discusses the background of such an approach and how combining it with artificial selection to generate heterogeneity in metabolic rate with an analytical framework to parse out the different mechanisms that contribute to the effects of heterogeneity can contribute to the various models of metabolic scaling. Finally, the absence of the typical allometric scaling relationship among different species of honeybees is discussed as an important prospect for deciphering the role of top-down ecological factors on metabolic scaling. This article is part of the theme issue 'The evolutionary significance of variation in metabolic rates'.

Dolphin social phenotypes vary in response to food availability but not the North Atlantic Oscillation index

Social behaviours can allow individuals to flexibly respond to environmental change, potentially buffering adverse effects. However, individuals may respond differently to the same environmental stimulus, complicating predictions for population-level response to environmental change. Here, we show that bottlenose dolphins (Tursiops truncatus) alter their social behaviour at yearly and monthly scales in response to a proxy for food availability (salmon abundance) but do not respond to variation in a proxy for climate (the North Atlantic Oscillation index). There was also individual variation in plasticity for gregariousness and connectedness to distant parts of the social network, although these traits showed limited repeatability. By contrast, individuals showed consistent differences in clustering with their immediate social environment at the yearly scale but no individual variation in plasticity for this trait at either timescale. These results indicate that social behaviour in free-ranging cetaceans can be highly resource dependent with individuals increasing their connectedness over short timescales but possibly reducing their wider range of connection at longer timescales. Some social traits showed more individual variation in plasticity or mean behaviour than others, highlighting how predictions for the responses of populations to environmental variation must consider the type of individual variation present in the population.

Fission-fusion dynamics in the social networks of a North American pitviper

Many animal species exist in fission-fusion societies, where the size and composition of conspecific groups change spatially and temporally. To help investigate such phenomena, social network analysis (SNA) has emerged as a powerful conceptual and analytical framework for assessing patterns of interconnectedness and quantifying group-level interactions. We leveraged behavioral observations via radiotelemetry and genotypic data from a long-term (>10 years) study on the pitviper Crotalus atrox (western diamondback rattlesnake) and used SNA to quantify the first robust demonstration of social network structures for any free-living snake. Group-level interactions among adults in this population resulted in structurally modular networks (i.e., distinct clusters of interacting individuals) for fidelis use of communal winter dens (denning network), mating behaviors (pairing network), and offspring production (parentage network). Although the structure of each network was similar, the size and composition of groups varied among them. Specifically, adults associated with moderately sized social groups at winter dens but often engaged in reproductive behaviors-both at and away from dens-with different and fewer partners. Additionally, modules formed by individuals in the pairing network were frequently different from those in the parentage network, likely due to multiple mating, long-term sperm storage by females, and resultant multiple paternity. Further evidence for fission-fusion dynamics exhibited by this population-interactions were rare when snakes were dispersing to and traversing their spring-summer home ranges (to which individuals show high fidelity), despite ample opportunities to associate with numerous conspecifics that had highly overlapping ranges. Taken together, we show that long-term datasets incorporating SNA with spatial and genetic information provide robust and unique insights to understanding the social structure of cryptic taxa that are understudied.

Indirect genetic effects for social network structure in Drosophila melanogaster

The position an individual holds in a social network is dependent on both its direct and indirect social interactions. Because social network position is dependent on the actions and interactions of conspecifics, it is likely that the genotypic composition of individuals within a social group impacts individuals' network positions. However, we know very little about whether social network positions have a genetic basis, and even less about how the genotypic makeup of a social group impacts network positions and structure. With ample evidence indicating that network positions influence various fitness metrics, studying how direct and indirect genetic effects shape network positions is crucial for furthering our understanding of how the social environment can respond to selection and evolve. Using replicate genotypes of Drosophila melanogaster fruit flies, we created social groups that varied in their genotypic makeup. Social groups were videoed, and networks were generated using motion-tracking software. We found that both an individual's own genotype and the genotypes of conspecifics in its social group affect its position within a social network. These findings provide an early example of how indirect genetic effects and social network theory can be linked, and shed new light on how quantitative genetic variation shapes the structure of social groups. This article is part of a discussion meeting issue 'Collective behaviour through time'.

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.

Direct and indirect phenotypic effects on sociability indicate potential to evolve

The decision to leave or join a group is important as group size influences many aspects of organisms' lives and their fitness. This tendency to socialise with others, sociability, should be influenced by genes carried by focal individuals (direct genetic effects) and by genes in partner individuals (indirect genetic effects), indicating the trait's evolution could be slower or faster than expected. However, estimating these genetic parameters is difficult. Here, in a laboratory population of the cockroach Blaptica dubia, I estimate phenotypic parameters for sociability: repeatability (R) and repeatable influence (RI), that indicate whether direct and indirect genetic effects respectively are likely. I also estimate the interaction coefficient (Ψ), which quantifies how strongly a partner's trait influences the phenotype of the focal individual and is key in models for the evolution of interacting phenotypes. Focal individuals were somewhat repeatable for sociability across a 3-week period (R = 0.080), and partners also had marginally consistent effects on focal sociability (RI = 0.053). The interaction coefficient was non-zero, although in opposite sign for the sexes; males preferred to associate with larger individuals (Ψ_male  = -0.129), while females preferred to associate with smaller individuals (Ψ_female  = 0.071). Individual sociability was consistent between dyadic trials and in social networks of groups. These results provide phenotypic evidence that direct and indirect genetic effects have limited influence on sociability, with perhaps most evolutionary potential stemming from heritable effects of the body mass of partners. Sex-specific interaction coefficients may produce sexual conflict and the evolution of sexual dimorphism in social behaviour.

The social evolution of individual differences: Future directions for a comparative science of personality in social behavior

Personality is essential for understanding the evolution of cooperation and conflict in behavior. However, personality science remains disconnected from the field of social evolution, limiting our ability to explain how personality and plasticity shape phenotypic adaptation in social behavior. Researchers also lack an integrative framework for comparing personality in the contextualized and multifaceted behaviors central to social interactions among humans and other animals. Here we address these challenges by developing a social evolutionary approach to personality, synthesizing theory, methods, and organizing questions in the study of individuality and sociality in behavior. We critically review current measurement practices and introduce social reaction norm models for comparative research on the evolution of personality in social environments. These models demonstrate that social plasticity affects the heritable variance of personality, and that individual differences in social plasticity can further modify the rate and direction of adaptive social evolution. Future empirical studies of frequency- and density-dependent social selection on personality are crucial for further developing this framework and testing adaptive theory of social niche specialization.

Maternal effects do not resolve the paradox of stasis in birth weight in a wild red deer populaton

In natural populations, quantitative traits seldom show short-term evolution at the rate predicted by evolutionary models. Resolving this "paradox of stasis" is a key goal in evolutionary biology, as it directly challenges our capacity to predict evolutionary change. One particularly promising hypothesis to explain the lack of evolutionary responses in a key offspring trait, body weight, is that positive selection on juveniles is counterbalanced by selection against maternal investment in offspring growth, given that reproduction is costly for the mothers. Here, we used data from one of the longest individual-based studies of a wild mammal population to test this hypothesis. We first showed that despite positive directional selection on birth weight, and heritable variation for this trait, no genetic change has been observed for birth weight over the past 47 years in the study population. Contrarily to our expectation, we found no evidence of selection against maternal investment in birth weight-if anything, selection favors mothers that produce large calves. Accordingly, we show that genetic change in birth weight over the study period is actually lower than that predicted from models including selection on maternal performance; ultimately our analysis here only deepens rather than resolves the paradox of stasis.

Linking quantitative genetics with community-level performance: Are there operational models for plant breeding?

Plant breeding is focused on the genotype and population levels while targeting effects at higher levels of biodiversity, from crop covers to agroecosystems. Making predictions across nested levels of biodiversity is therefore a major challenge for the development of intercropping practices. New prediction tools and concepts are required to design breeding strategies with desirable outcomes at the crop community level. We reviewed theoretical advances in the field of evolutionary ecology to identify potentially operational ways of predicting the effects of artificial selection on community-level performances. We identified three main types of approaches differing in the way they model interspecific indirect genetic effects (IIGEs) at the community level: (1) The community heritability approach estimates the variance for IIGE induced by a focal species at the community level; (2) the joint phenotype approach quantifies genetic constraints between direct genetic effects and IIGE for a set of interacting species; (3) the community-trait genetic gradient approach decomposes the IIGE for a focal species across a multivariate set of its functional traits. We discuss the potential operational capacities of these approaches and stress that each is a special case of a general multitrait and multispecies selection index. Choosing one therefore involves assumptions and goals regarding the breeding target and strategy. Obtaining reliable quantitative, community-level predictions at the genetic level is constrained by the size and complexity of the experimental designs usually required. Breeding strategies should instead be compared using theoretically informed qualitative predictions. The need to estimate genetic covariances between traits measured both within and among species (for IIGE) is another obstacle, as the two are not determined by the exact same biological processes. We suggest future research directions and strategies to overcome these limits. Our synthesis offers an integrative theoretical framework for breeders interested in the genetic improvement of crop communities but also for scientists interested in the genetic bases of plant community functioning.

Where do we stand with the covariation framework in primate societies?

Comparative study of the social systems of macaques has revealed correlated variations between species in multiple social traits such as the asymmetry of dominance relationships, preferential treatment of kin, patterns of aggression and reconciliation, modes of socialization, and access to food resources. Macaques can be classified on a scale of four categories of social styles, ranging from the least to the most tolerant species. This led to the development of the covariation framework, which addresses the constraints responsible for the linkages between social traits, and their consequences on the evolution of primate social systems. Decades of research have provided a wealth of information that supports, complements, expands, or challenges the covariation framework. In this article, I review this body of knowledge and consider covariation in its two aspects, that is, as a pattern and as a hypothesis. I first consider the extent to which social styles can be invariant, the strength of correlations between traits, and the possible extension of the framework to nonhuman primates other than macaques. I then discuss how to formulate hypotheses, identify sources of linkage between traits, make predictions about the effects of social constraints, assess the tolerance dimension of social styles, and consider the breaking of linkages between traits. Whereas socioecological studies aim to understand how adaptation to the ecological environment determines the shape of social systems, the covariation framework is a complementary research program that seeks to unravel the internal processes that restrict or channel change in social behavior.

Niche construction in quantitative traits: heritability and response to selection

A central tenet of niche construction (NC) theory is that organisms can alter their environments in heritable and evolutionarily important ways, often altering selection pressures. We suggest that the physical changes niche constructors make to their environments may also alter trait heritability and the response of phenotypes to selection. This effect might change evolution, over and above the effect of NC acting via selection alone. We develop models of trait evolution that allow us to partition the effects of NC on trait heritability from those on selection to better investigate their distinct effects. We show that the response of a phenotype to selection and so the pace of phenotypic change can be considerably altered in the presence of NC and that this effect is compounded when trans-generational interactions are included. We argue that novel mathematical approaches are needed to describe the simultaneous effects of NC on trait evolution via selection and heritability. Just as indirect genetic effects have been shown to significantly increase trait heritability, the effects of NC on heritability in our model suggest a need for further theoretical development of the concept of heritability.

The ecology of wealth inequality in animal societies

Individuals vary in their access to resources, social connections and phenotypic traits, and a central goal of evolutionary biology is to understand how this variation arises and influences fitness. Parallel research on humans has focused on the causes and consequences of variation in material possessions, opportunity and health. Central to both fields of study is that unequal distribution of wealth is an important component of social structure that drives variation in relevant outcomes. Here, we advance a research framework and agenda for studying wealth inequality within an ecological and evolutionary context. This ecology of inequality approach presents the opportunity to reintegrate key evolutionary concepts as different dimensions of the link between wealth and fitness by (i) developing measures of wealth and inequality as taxonomically broad features of societies, (ii) considering how feedback loops link inequality to individual and societal outcomes, (iii) exploring the ecological and evolutionary underpinnings of what makes some societies more unequal than others, and (iv) studying the long-term dynamics of inequality as a central component of social evolution. We hope that this framework will facilitate a cohesive understanding of inequality as a widespread biological phenomenon and clarify the role of social systems as central to evolutionary biology.

Quantifying within-group variation in sociality—covariation among metrics and patterns across primate groups and species

Abstract

It has long been recognized that the patterning of social interactions within a group can give rise to a social structure that holds very different places for different individuals. Such within-group variation in sociality correlates with fitness proxies in fish, birds, and mammals. Broader integration of this research has been hampered by the lack of agreement on how to integrate information from a plethora of dyadic interactions into individual-level metrics. As a step towards standardization, we collected comparative data on affinitive and affiliative interactions from multiple groups each of five species of primates to assess whether the same aspects of sociality are measured by different metrics and indices. We calculated 16 different sociality metrics used in previous research and thought to represent three different sociality concepts. We assessed covariation of metrics within groups and then summarized covariation patterns across all 15 study groups, which varied in size from 5 to 41 adults. With some methodological and conceptual caveats, we found that the number of weak ties individuals formed within their groups represented a dimension of sociality that was largely independent from the overall number of ties as well as from the number and strength of the strong ties they formed. Metrics quantifying indirect connectedness exhibited strong covariation with strong tie metrics and thus failed to capture a third aspect of sociality. Future research linking affiliation and affinity to fitness or other individual level outcomes should quantify inter-individual variation in three aspects: the overall number of ties, the number of weak ties, and the number or strength of strong ties individuals form, after taking into account effects of social network density.

Significance statement

In recent years, long-term studies of individually known animals have revealed strong correlations between individual social bonds and social integration, on the one hand, and reproductive success and survival on the other hand, suggesting strong natural selection on affiliative and affinitive behavior within groups. It proved difficult to generalize from these studies because they all measured sociality in slightly different ways. Analyzing covariation between 16 previously used metrics identified only three rather independent dimensions of variation. Thus, different studies have tapped into the same biological phenomenon. How individuals are weakly connected within their group needs further attention.

A variance partitioning perspective of assortative mating: Proximate mechanisms and evolutionary implications

Assortative mating occurs when paired individuals of the same population are more similar than expected by chance. This form of non-random assortment has long been predicted to play a role in many evolutionary processes because assortatively mated individuals are assumed to be genetically similar. However, this assumption may always hold for labile traits, or traits that are measured with error. For such traits, there is a variety of proximate mechanisms that can drive phenotypic resemblance between mated partners that, notably, have very different evolutionary repercussions. Bettering our understanding of the role of assortative mating in evolution will thus require insight into its proximate causes. To date, empirical research remains sparse, especially when for labile traits. This special issue aims to stimulate such research while promoting the usage and development of statistical approaches allowing the quantification of the relative roles of alternative proximate mechanisms causing assortative mating. To this end, we first describe how the phenotypic covariance between mated partners can be usefully partitioned into components that capture one or several of five distinct mechanisms. We then demonstrate why the importance of mechanisms causing genetic covariance between the traits of partners may often be overestimated. Finally, we detail how the evolutionary causes and consequences of the diverse mechanisms may be identified.

Interacting phenotypes and the coevolutionary process: Interspecific indirect genetic effects alter coevolutionary dynamics

Coevolution occurs when species interact to influence one another's fitness, resulting in reciprocal evolutionary change. In many coevolving lineages, trait expression in one species is modified by the genotypes and phenotypes of the other, forming feedback loops reminiscent of models of intraspecific social evolution. Here, we adapt the theory of within-species social evolution, characterized by indirect genetic effects and social selection imposed by interacting individuals, to the case of interspecific interactions. In a trait-based model, we derive general expressions for multivariate evolutionary change in two species and the expected between-species covariance in evolutionary change when selection varies across space. We show that reciprocal interspecific indirect genetic effects can dominate the coevolutionary process and drive patterns of correlated evolution beyond what is expected from direct selection alone. In extreme cases, interspecific indirect genetic effects can lead to coevolution when selection does not covary between species or even when one species lacks genetic variance. Moreover, our model indicates that interspecific indirect genetic effects may interact in complex ways with cross-species selection to determine the course of coevolution. Importantly, our model makes empirically testable predictions for how different forms of reciprocal interactions contribute to the coevolutionary process.

Similarity in Temporal Movement Patterns in Laying Hens Increases with Time and Social Association

We explored the relationship between social associations and individual activity patterns in domestic hens. Out of 1420 laying hens, 421 hens were equipped with RFID tags attached to RFID-specific leg bands (leg bands from Company Roxan, Selkirk, Scotland) to continuously track their change in location across four different areas (one indoor and three outdoor areas). Using a combination of social network analysis for quantifying social relationships and dynamic time warping for characterizing the movement patterns of hens, we found that hens were consistent in their individual variation in temporal activity and maintained stable social relationships in terms of preferred association partners. In addition to being consistent, social associations correlated with movement patterns and this correlation strengthened over the period of observation, suggesting that the animals aligned their activity patterns with those of their social affiliates. These results demonstrate the importance of social relationships when considering the expression of individual behaviour. Notably, differences in temporal patterns emerge despite rather homogeneous rearing conditions, same environment, and low genetic diversity. Thus, while variation in behavioural phenotypes can be observed across isolated individuals, this study shows that the social environment within a group can shape and enhance variation in general movement patterns of individual animals.

The Indirect Genetic Effect Interaction Coefficient ψ: Theoretically Essential and Empirically Neglected

The interaction effect coefficient ψ has been a much-discussed, fundamental parameter of indirect genetic effect (IGE) models since its formal mathematical description in 1997. The coefficient simultaneously describes the form of changes in trait expression caused by genes in the social environment and predicts the evolutionary consequences of those IGEs. Here, we report a striking mismatch between theoretical emphasis on ψ and its usage in empirical studies. Surveying all IGE research, we find that the coefficient ψ has not been equivalently conceptualized across studies. Several issues related to its proper empirical measurement have recently been raised, and these may severely distort interpretations about the evolutionary consequences of IGEs. We provide practical advice on avoiding such pitfalls. The majority of empirical IGE studies use an alternative variance-partitioning approach rooted in well-established statistical quantitative genetics, but several hundred estimates of ψ (from 15 studies) have been published. A significant majority are positive. In addition, IGEs with feedback, that is, involving the same trait in both interacting partners, are far more likely to be positive and of greater magnitude. Although potentially challenging to measure without bias, ψ has critically-developed theoretical underpinnings that provide unique advantages for empirical work. We advocate for a shift in perspective for empirical work, from ψ as a description of IGEs, to ψ as a robust predictor of evolutionary change. Approaches that "run evolution forward" can take advantage of ψ to provide falsifiable predictions about specific trait interactions, providing much-needed insight into the evolutionary consequences of IGEs.

Indirect Genetic Effects: A Cross-disciplinary Perspective on Empirical Studies

Indirect genetic effects (IGE) occur when an individual's phenotype is influenced by genetic variation in conspecifics. Opportunities for IGE are ubiquitous, and, when present, IGE have profound implications for behavioral, evolutionary, agricultural, and biomedical genetics. Despite their importance, the empirical study of IGE lags behind the development of theory. In large part, this lag can be attributed to the fact that measuring IGE, and deconvoluting them from the direct genetic effects of an individual's own genotype, is subject to many potential pitfalls. In this Perspective, we describe current challenges that empiricists across all disciplines will encounter in measuring and understanding IGE. Using ideas and examples spanning evolutionary, agricultural, and biomedical genetics, we also describe potential solutions to these challenges, focusing on opportunities provided by recent advances in genomic, monitoring, and phenotyping technologies. We hope that this cross-disciplinary assessment will advance the goal of understanding the pervasive effects of conspecific interactions in biology.

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.

Identifying Causes of Social Evolution: Contextual Analysis, the Price Approach, and Multilevel Selection

Kin selection theory and multilevel selection theory are distinct approaches to explaining the evolution of social traits. The latter claims that it is useful to regard selection as a process that can occur on multiple levels of organisation such as the level of individuals and the level of groups. This is reflected in a decomposition of fitness into an individual component and a group component. This multilevel view is central to understanding and characterising evolutionary transitions in individuality, e.g., from unicellular life to multicellular organisms, but currently suffers from the lack of a consistent, quantifiable measure. Specifically, the two major statistical tools to determine the coefficients of such a decomposition, the multilevel Price equation and contextual analysis, are inconsistent and may disagree on whether group selection is present. Here we show that the reason for the discrepancies is that underlying the multilevel Price equation and contextual analysis are two non-equivalent causal models for the generation of individual fitness effects (thus leaving different “remainders” explained by group effects). While the multilevel Price equation assumes that the individual effect of a trait determines an individual's relative success within a group, contextual analysis posits that the individual effect is context-independent. Since these different assumptions reflect claims about the causal structure of the system, the correct approach cannot be determined on general theoretical or statistical grounds but must be identified by experimental intervention. We outline interventions that reveal the underlying causal structure and thus facilitate choosing the appropriate approach. We note that kin selection theory with its focus on the individual is immune to such inconsistency because it does not address causal structure with respect to levels of organisation. In contrast, our analysis of the two approaches to measuring group selection demonstrates that multilevel selection theory adds meaningful (falsifiable) causal structure to explain the sources of individual fitness and thereby constitutes a proper refinement of kin selection theory. Taking such refined causal structure into account seems indispensable for studying evolutionary transitions in individuality because these transitions are characterised by changes in the selection pressures that act on the respective levels.

Frequency dependence and the predictability of evolution in a changing environment

Frequency‐dependent (FD) selection, whereby fitness and selection depend on the genetic or phenotypic composition of the population, arises in numerous ecological contexts (competition, mate choice, crypsis, mimicry, etc.) and can strongly impact evolutionary dynamics. In particular, negative frequency‐dependent selection (NFDS) is well known for its ability to potentially maintain stable polymorphisms, but it has also been invoked as a source of persistent, predictable frequency fluctuations. However, the conditions under which such fluctuations persist are not entirely clear. In particular, previous work rarely considered that FD is unlikely to be the sole driver of evolutionary dynamics when it occurs, because most environments are not static but instead change dynamically over time. Here, we investigate how FD interacts with a temporally fluctuating environment to shape the dynamics of population genetic change. We show that a simple metric introduced by Lewontin, the slope of frequency change against frequency near equilibrium, works as a key criterion for distinguishing microevolutionary outcomes, even in a changing environment. When this slope D is between 0 and –2 (consistent with the empirical examples we review), substantial fluctuations would not persist on their own in a large population occupying a constant environment, but they can still be maintained indefinitely as quasi‐cycles fueled by environmental noise or genetic drift. However, such moderate NFDS buffers and temporally shifts evolutionary responses to periodic environments (e.g., seasonality). Stronger FD, with slope D < –2, can produce self‐sustained cycles that may overwhelm responses to a changing environment, or even chaos that fundamentally limits predictability. This diversity of expected outcomes, together with the empirical evidence for both FD and environment‐dependent selection, suggests that the interplay of internal dynamics with external forcing should be investigated more systematically to reach a better understanding and prediction of evolution.

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.

Social Selection and the Evolution of Maladaptation

Evolution by natural selection is often viewed as a process that inevitably leads to adaptation or an increase in population fitness over time. However, maladaptation, an evolved decrease in fitness, may also occur in response to natural selection under some conditions. Social selection, which arises from the effects of social partners on fitness, has been identified as a potential cause of maladaptation, but we lack a general rule identifying when social selection should lead to a decrease in population mean fitness. Here we use a quantitative genetic model to develop such a rule. We show that maladaptation is most likely to occur when social selection is strong relative to nonsocial selection and acts in an opposing direction. In this scenario, the evolution of traits that impose fitness costs on others may outweigh evolved gains in fitness for the individual, leading to a net decrease in population mean fitness. Furthermore, we find that maladaptation may also sometimes occur when phenotypes of interacting individuals negatively covary. We outline the biological situations where maladaptation in response to social selection can be expected, provide both quantitative genetic and phenotypic versions of our derived result, and suggest what empirical work would be needed to test it. We also consider the effect of social selection on inclusive fitness and support previous work showing that inclusive fitness cannot suffer an evolutionary decrease. Taken together, our results show that social selection may decrease population mean fitness when it opposes individual-level selection, even as inclusive fitness increases.

Runaway evolution from male-male competition

Wondrously elaborate weapons and displays that appear to be counter to ecological optima are widespread features of male contests for mates across the animal kingdom. To understand how such diverse traits evolve, here we develop a quantitative genetic model of sexual selection for a male signaling trait that mediates aggression in male‐male contests and show that an honest indicator of aggression can generate selection on itself by altering the social environment. This can cause selection to accelerate as the trait is elaborated, leading to runaway evolution. Thus, an evolving source of selection provided by the social environment is the fundamental unifying feature of runaway sexual selection driven by either male‐male competition or female mate choice. However, a key difference is that runaway driven by male‐male competition requires signal honesty. Our model identifies simple conditions that provide clear, testable predictions for empirical studies using standard quantitative genetic methods.

A scaling law of multilevel evolution: how the balance between within- and among-collective evolution is determined

Numerous living systems are hierarchically organised, whereby replicating components are grouped into reproducing collectives-e.g., organelles are grouped into cells, and cells are grouped into multicellular organisms. In such systems, evolution can operate at two levels: evolution among collectives, which tends to promote selfless cooperation among components within collectives (called altruism), and evolution within collectives, which tends to promote cheating among components within collectives. The balance between within- and among-collective evolution thus exerts profound impacts on the fitness of these systems. Here, we investigate how this balance depends on the size of a collective (denoted by N) and the mutation rate of components (m) through mathematical analyses and computer simulations of multiple population genetics models. We first confirm a previous result that increasing N or m accelerates within-collective evolution relative to among-collective evolution, thus promoting the evolution of cheating. Moreover, we show that when within- and among-collective evolution exactly balance each other out, the following scaling relation generally holds: Nmα is a constant, where scaling exponent α depends on multiple parameters, such as the strength of selection and whether altruism is a binary or quantitative trait. This relation indicates that although N and m have quantitatively distinct impacts on the balance between within- and among-collective evolution, their impacts become identical if m is scaled with a proper exponent. Our results thus provide a novel insight into conditions under which cheating or altruism evolves in hierarchically-organised replicating systems.

Social Effects on Annual Fitness in Red Squirrels

When resources are limited, mean fitness is constrained and competition can cause genes and phenotypes to enhance an individual's own fitness while reducing the fitness of their competitors. Negative social effects on fitness have the potential to constrain adaptation, but the interplay between ecological opportunity and social constraints on adaptation remains poorly studied in nature. Here, we tested for evidence of phenotypic social effects on annual fitness (survival and reproductive success) in a long-term study of wild North American red squirrels (Tamiasciurus hudsonicus) under conditions of both resource limitation and super-abundant food resources. When resources were limited, populations remained stable or declined, and there were strong negative social effects on annual survival and reproductive success. That is, mean fitness was constrained and individuals had lower fitness when other nearby individuals had higher fitness. In contrast, when food resources were super-abundant, populations grew and social constraints on reproductive success were greatly reduced or eliminated. Unlike reproductive success, social constraints on survival were not significantly reduced when food resources were super-abundant. These findings suggest resource-dependent social constraints on a component of fitness, which have important potential implications for evolution and adaptation.

Strong phenotypic trait correlations between mating partners do not result from assortative mating in wild great tits (Parus major)

There is considerable debate about the occurrence of assortative mating between phenotypic traits measured within natural populations. Meta-analyses have implied that assortative mating occurs generally in natural populations, but recent work indicates these conclusions largely result from biased data. Specifically, estimates of phenotypic correlations between mating partners do not solely result from nonrandom associations between individual-level traits of partners but also from other biological processes (joint phenotypic plasticity, indirect genetic effects), methodological practices (observer bias) and other unexplained residual correlations (e.g. correlated measurement error). This paper puts this critique to test. First, we estimated the overall phenotypic correlation between phenotypic traits of mating partners for a wild population of great tits. Second, we estimated various key variance components to reveal the extent to which phenotypic correlations between partners resulted from assortative mating, reversible plasticity, social partner effects and methodological practices. We performed our analyses for a range of phenotypic traits (body mass, breathing rate, exploration behaviour, wing and tarsus length) to derive general conclusions not hinging on the specifics of the traits involved. Our analyses support the conclusion that patterns of assortative mating exist at first glance but occur because of the biasing effects of correlated residuals likely caused by a combination of phenotypic responses to unknown environmental factors or measurement error-not because of intrinsic patterns of assortative mating.

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.

Social selection is density dependent but makes little contribution to total selection in New Zealand giraffe weevils

Social selection occurs when traits of interaction partners influence an individual's fitness and can alter total selection strength. However, we have little idea of what factors influence social selection's strength. Further, social selection only contributes to overall selection when there is phenotypic assortment, but simultaneous estimates of social selection and phenotypic assortment are rare. Here, we estimated social selection on body size in a wild population of New Zealand giraffe weevils (Lasiorhynchus barbicornis). We measured phenotypic assortment by body size and tested whether social selection varied with sex ratio, density and interacted with the body size of the focal individual. Social selection was limited and unaffected by sex ratio or the size of the focal individual. However, at high densities social selection was negative for both sexes, consistent with size-based competitive interactions for access to mates. Phenotypic assortment was always close to zero, indicating negative social selection at high densities will not impede the evolution of larger body sizes. Despite its predicted importance, social selection may only influence evolutionary change in specific contexts, leaving direct selection to drive evolutionary change.

Who listens to mother? A whole-family perspective on the evolution of maternal hormone allocation

Maternal effects, or the influence of maternal environment and phenotype on offspring phenotype, may allow mothers to fine-tune their offspring's developmental trajectory and resulting phenotype sometimes long after the offspring has reached independence. However, maternal effects on offspring phenotype do not evolve in isolation, but rather within the context of a family unit, where the separate and often conflicting evolutionary interests of mothers, fathers and offspring are all at play. While intrafamilial conflicts are routinely invoked to explain other components of reproductive strategy, remarkably little is known about how intrafamilial conflicts influence maternal effects. We argue that much of the considerable variation in the relationship between maternally derived hormones, nutrients and other compounds and the resulting offspring phenotype might be explained by the presence of conflicting selection pressures on different family members. In this review, we examine the existing literature on maternal hormone allocation as a case study for maternal effects more broadly, and explore new hypotheses that arise when we consider current findings within a framework that explicitly incorporates the different evolutionary interests of the mother, her offspring and other family members. Specifically, we hypothesise that the relationship between maternal hormone allocation and offspring phenotype depends on a mother's ability to manipulate the signals she sends to offspring, the ability of family members to be plastic in their response to those signals and the capacity for the phenotypes and strategies of various family members to interact and influence one another on both behavioural and evolutionary timescales. We also provide suggestions for experimental, comparative and theoretical work that may be instrumental in testing these hypotheses. In particular, we highlight that manipulating the level of information available to different family members may reveal important insights into when and to what extent maternal hormones influence offspring development. We conclude that the evolution of maternal hormone allocation is likely to be shaped by the conflicting fitness optima of mothers, fathers and offspring, and that the outcome of this conflict depends on the relative balance of power between family members. Extending our hypotheses to incorporate interactions between family members, as well as more complex social groups and a wider range of taxa, may provide exciting new developments in the fields of endocrinology and maternal effects.

Indirect genetic and environmental effects on behaviors, morphology, and life-history traits in a wild Eastern chipmunk population

Additive genetic variance in a trait reflects its potential to respond to selection, which is key for adaptive evolution in the wild. Social interactions contribute to this genetic variation through indirect genetic effects-the effect of an individual's genotype on the expression of a trait in a conspecific. However, our understanding of the evolutionary importance of indirect genetic effects in the wild and of their strength relative to direct genetic effects is limited. In this study, we assessed how indirect genetic effects contribute to genetic variation of behavioral, morphological, and life-history traits in a wild Eastern chipmunk population. We also compared the contribution of direct and indirect genetic effects to traits evolvabilities and related these effects to selection strength across traits. We implemented a novel approach integrating the spatial structure of social interactions in quantitative genetic analyses, and supported the reliability of our results with power analyses. We found indirect genetic effects for trappability and relative fecundity, little direct genetic effects in all traits and a large role for direct and indirect permanent environmental effects. Our study highlights the potential evolutionary role of social permanent environmental effects in shaping phenotypes of conspecifics through adaptive phenotypic plasticity.

Variation in personality can substitute for social feedback in coordinated animal movements

Collective movements are essential for the effective function of animal societies, but are complicated by the need for consensus among group members. Consensus is typically assumed to arise via feedback mechanisms, but this ignores inter-individual variation in behavioural tendency ('personality'), which is known to underpin the successful function of many complex societies. In this study, we use a theoretical approach to examine the relative importance of personality and feedback in the emergence of collective movement decisions in animal groups. Our results show that variation in personality dramatically influences collective decisions and can partially or completely replace feedback depending on the directionality of relationships among individuals. The influence of personality increases with the exaggeration of differences among individuals. While it is likely that both feedback and personality interact in nature, our findings highlight the potential importance of personality in driving collective processes.

Task syndromes: linking personality and task allocation in social animal groups

Studies of eusocial insects have extensively investigated two components of task allocation: how individuals distribute themselves among different tasks in a colony and how the distribution of labor changes to meet fluctuating task demand. While discrete age- and morphologically-based task allocation systems explain much of the social order in these colonies, the basis for task allocation in non-eusocial organisms and within eusocial castes remains unknown. Building from recent advances in the study of among-individual variation in behavior (i.e., animal personalities), we explore a potential mechanism by which individuality in behaviors unrelated to tasks can guide the developmental trajectories that lead to task specialization. We refer to the task-based behavioral syndrome that results from the correlation between the antecedent behavioral tendencies and task participation as a task syndrome. In this review, we present a framework that integrates concepts from a long history of task allocation research in eusocial organisms with recent findings from animal personality research to elucidate how task syndromes and resulting task allocation might manifest in animal groups. By drawing upon an extensive and diverse literature to evaluate the hypothesized framework, this review identifies future areas for study at the intersection of social behavior and animal personality.

Social groups with diverse personalities mitigate physiological stress in a songbird

Social groups often consist of diverse phenotypes, including personality types, and this diversity is known to affect the functioning of the group as a whole. Social selection theory proposes that group composition (i.e. social environment) also influences the performance of individual group members. However, the effect of group behavioural composition on group members remains largely unexplored, and it is still contentious whether individuals benefit more in a social environment with homogeneous or diverse behavioural composition. We experimentally formed groups of house sparrows Passer domesticus with high and low diversity of personality (exploratory behaviour), and found that their physiological state (body condition, physiological stress and oxidative damage) improved with increasing group-level diversity of personality. These findings demonstrate that group personality composition affects the condition of group members and individuals benefit from social heterosis (i.e. associating with a diverse set of behavioural types). This aspect of the social life can play a key role in affiliation rules of social animals and might explain the evolutionary coexistence of different personalities in nature.

The diversity of maternal-age effects upon pre-adult survival across animal species

Maternal senescence is the detrimental effect of increased maternal age on offspring performance. Despite much recent interest given to describing this phenomenon, its distribution across animal species is poorly understood. A review of the published literature finds that maternal age affects pre-adult survival in 252 of 272 populations (93%) representing 97 animal species. Age effects tended to be deleterious in invertebrates and mammals, including humans, confirming the presence of senescence. However, bird species were a conspicuous exception, as pre-adult survival tended to increase with maternal age in surveyed populations. In all groups, maternal-age effects became more negative in older mothers. Invertebrates senesced faster than vertebrates, and humans aged faster than non-human mammals. Within invertebrates, lepidopterans demonstrated the most extreme rates of maternal-effect senescence. Among the surveyed studies, phylogeny, life history and environment (e.g. laboratory versus wild populations) were tightly associated; this made it difficult to make confident inferences regarding the causes of diversity for the phenomenon. However, we provide some testable suggestions, and we observe that some differences appear to be consistent with predictions from evolutionary theory. We discuss how future work may help clarify ultimate and proximate causes for this diversity.

Condition-Dependent Mutual Mate Preference and Intersexual Genetic Correlations for Mating Activity

Although mating represents a mutual interaction, the study of mate preferences has long focused on choice in one sex and preferred traits in the other. This has certainly been the case in the study of the costs and condition-dependent expression of mating preferences, with the majority of studies concerning female preference. The condition dependence and genetic architecture of mutual mate preferences remain largely unstudied, despite their likely relevance for the evolution of preferences and of mating behavior more generally. Here we measured (a) male and female mate preferences and (b) intersexual genetic correlations for the mating activity in pedigreed populations of southern field crickets (Gryllus bimaculatus) raised on a favorable (free-choice) or a stressful (protein-deprived) diet. In the favorable dietary environment, mutual mate preferences were strong, and the intersexual genetic covariance for mating activity was not different from one. However, in the stressful dietary environment, mutual mate preferences were weak, and the intersexual genetic covariance for mating activity was significantly smaller than one. Altogether, our results show that diet environments affect the expression of genetic variation in mating behaviors: when the environment is stressful, both (a) the strength of mutual mate preference and (b) intersexual genetic covariance for mating activity tend to be weaker. This implies that mating dynamics strongly vary across environments.

Phenotypic Plasticity Provides a Bioinspiration Framework for Minimal Field Swarm Robotics

The real world is highly variable and unpredictable, and so fine-tuned robot controllers that successfully result in group-level "emergence" of swarm capabilities indoors may quickly become inadequate outside. One response to unpredictability could be greater robot complexity and cost, but this seems counter to the "swarm philosophy" of deploying (very) large numbers of simple agents. Instead, here I argue that bioinspiration in swarm robotics has considerable untapped potential in relation to the phenomenon of phenotypic plasticity: when a genotype can produce a range of distinctive changes in organismal behavior, physiology and morphology in response to different environments. This commonly arises following a natural history of variable conditions; implying the need for more diverse and hazardous simulated environments in offline, pre-deployment optimization of swarms. This will generate-indicate the need for-plasticity. Biological plasticity is sometimes irreversible; yet this characteristic remains relevant in the context of minimal swarms, where robots may become mass-producible. Plasticity can be introduced through the greater use of adaptive threshold-based behaviors; more fundamentally, it can link to emerging technologies such as smart materials, which can adapt form and function to environmental conditions. Moreover, in social animals, individual heterogeneity is increasingly recognized as functional for the group. Phenotypic plasticity can provide meaningful diversity "for free" based on early, local sensory experience, contributing toward better collective decision-making and resistance against adversarial agents, for example. Nature has already solved the challenge of resilient self-organisation in the physical realm through phenotypic plasticity: swarm engineers can follow this lead.

The gene's eye view, the Gouldian knot, Fisherian swords and the causes of selection

The biological units-of-selection debate has centred on questions of which units experience selection and adaptation. Here, I use a causal framework and the Price equation to develop the gene's eye perspective. Genes are causally special in being both replicators and interactors. Gene effects are tied together in a complex Gouldian knot of interactions, but Fisher deployed three swords to try to cut the knot. The first, Fisher's average excess, is non-causal, so not fully satisfactory in that respect. The Price equation highlights Fisher's other two swords, choosing to model only selection, and only the part that is transmissible across generations. The models developed here show that many causes of organismal fitness do not cause Gouldian complications. Only two kinds of elements must be added to the focal gene for a causal explanation of its selective change: co-replicators that are associated with the focal gene and co-interactors that interact non-additively with the focal gene. Identical equations for co-replication and co-interaction describe interactions between gene copies at a single locus or at separate loci, and also for genes situated within the same individual or in different individuals. These results resolve some of the objections to the gene's eye view. This article is part of the theme issue 'Fifty years of the Price equation'.

Analysis of direct and indirect genetic effects in fighting sea anemones

Theoretical models of animal contests such as the Hawk-Dove game predict that variation in fighting behavior will persist due to mixed evolutionarily stable strategies (ESS) under certain conditions. However, the genetic basis for this variation is poorly understood and a mixed ESS for fighting can be interpreted in more than one way. Specifically, we do not know whether variation in aggression within a population arises from among-individual differences in fixed strategy (determined by an individual's genotype-direct genetic effects [DGEs]), or from within-individual variation in strategy across contests. Furthermore, as suggested by developments of the original Hawk-Dove model, within-individual variation in strategy may be dependent on the phenotype and thus genotype of the opponent (indirect genetic effects-IGEs). Here we test for the effect of DGEs and IGEs during fights in the beadlet sea anemone Actinia equina. By exploiting the unusual reproductive system of sea anemones, combined with new molecular data, we investigate the role of both additive (DGE + IGE) and non-additive (DGE × IGE) genetic effects on fighting parameters, the latter of which have been hypothesized but never tested for explicitly. We find evidence for heritable variation in fighting ability and that fight duration increases with relatedness. Fighting success is influenced additively by DGEs and IGEs but we found no evidence for non-additive IGEs. These results indicate that variation in fighting behavior is driven by additive indirect genetic effects (DGE + IGE), and support a core assumption of contest theory that strategies are fixed by DGEs.

Gazing into the anthosphere: considering how microbes influence floral evolution

The flower is the hallmark of angiosperms and its evolution is key to their diversification. As knowledge of ecological interactions between flowers and their microbial communities (the anthosphere) expands, it becomes increasingly important to consider the evolutionary impacts of these associations and their potential eco-evolutionary dynamics. In this Viewpoint we synthesize current knowledge of the anthosphere within a multilevel selection framework and illustrate the potential for the extended floral phenotype (the phenotype expressed from the genes of the plant and its associated flower microbes) to evolve. We argue that flower microbes are an important, but understudied, axis of variation that shape floral trait evolution and angiosperm reproductive ecology. We highlight knowledge gaps and discuss approaches that are critical for gaining a deeper understanding of the role microbes play in mediating plant reproduction, ecology, and evolution.

Partner’s age, not social environment, predicts extrapair paternity in wild great tits (Parus major)

An individual’s fitness is not only influenced by its own phenotype, but by the phenotypes of interacting conspecifics. This is likely to be particularly true when considering fitness gains and losses caused by extrapair matings, as they depend directly on the social environment. While previous work has explored effects of dyadic interactions, limited understanding exists regarding how group-level characteristics of the social environment affect extrapair paternity (EPP) and cuckoldry. We use a wild population of great tits (Parus major) to examine how, in addition to the phenotypes of focal parents, two neighborhood-level traits—age and personality composition—predict EPP and cuckoldry. We used the well-studied trait “exploration behavior” as a measure of the reactive-proactive personality axis. Because breeding pairs inhabit a continuous “social landscape,” we first established an ecologically relevant definition of a breeding “neighborhood” through genotyping parents and nestlings in a 51-ha patch of woodland and assessing the spatial predictors of EPP events. Using the observed decline in likelihood of EPP with increasing spatial separation between nests, we determined the relevant neighborhood boundaries, and thus the group phenotypic composition of an individual’s neighborhood, by calculating the point at which the likelihood of EPP became negligible. We found no evidence that “social environment” effects (i.e., neighborhood age or personality composition) influenced EPP or cuckoldry. We did, however, find that a female’s own age influenced the EPP of her social mate, with males paired to older females gaining more EPP, even when controlling for the social environment. These findings suggest that partner characteristics, rather than group phenotypic composition, influence mating activity patterns at the individual level.

Green beards in the light of indirect genetic effects

The green-beard effect is one proposed mechanism predicted to underpin the evolution of altruistic behavior. It relies on the recognition and the selective help of altruists to each other in order to promote and sustain altruistic behavior. However, this mechanism has often been dismissed as unlikely or uncommon, as it is assumed that both the signaling trait and altruistic trait need to be encoded by the same gene or through tightly linked genes. Here, we use models of indirect genetic effects (IGEs) to find the minimum correlation between the signaling and altruistic trait required for the evolution of the latter. We show that this correlation threshold depends on the strength of the interaction (influence of the green beard on the expression of the altruistic trait), as well as the costs and benefits of the altruistic behavior. We further show that this correlation does not necessarily have to be high and support our analytical results by simulations.