Pathways to social evolution and their evolutionary feedbacks

Social interactions generate complex selection patterns in virtual worlds

Understanding the influence of social interactions on individual fitness is key to improving our predictions of phenotypic evolution. However, we often overlook the different components of selection regimes arising from interactions among organisms, including social, correlational, and indirect selection. This is due to the challenging sampling efforts required in natural populations to measure phenotypes expressed during interactions and individual fitness. Furthermore, behaviours are crucial in mediating social interactions, yet few studies have explicitly quantified these selection components on behavioural traits. In this study, we capitalize on an online multiplayer video game as a source of extensive data recording direct social interactions among prey, where prey collaborate to escape a predator in realistic ecological settings. We estimate natural and social selection and their contribution to total selection on behavioural traits mediating competition, cooperation, and predator-prey interactions. Behaviours of other prey in a group impact an individual's survival, and thus are under social selection. Depending on whether selection pressures on behaviours are synergistic or conflicting, social interactions enhance or mitigate the strength of natural selection, although natural selection remains the main driving force. Indirect selection through correlations among traits also contributed to the total selection. Thus, failing to account for the effects of social interactions and indirect selection would lead to a misestimation of the total selection acting on traits. Dissecting the contribution of each component to the total selection differential allowed us to investigate the causal mechanisms relating behaviour to fitness and quantify the importance of the behaviours of conspecifics as agents of selection. Our study emphasizes that social interactions generate complex selective regimes even in a relatively simple ecological environment.

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Evolutionary rescue from climate change: male indirect genetic effects on lay-dates and their consequences for population persistence

Changes in avian breeding phenology are among the most apparent responses to climate change in free-ranging populations. A key question is whether populations will be able to keep up with the expected rates of environmental change. There is a large body of research on the mechanisms by which avian lay-dates track temperature change and the consequences of (mal)adaptation on population persistence. Often overlooked is the role of males, which can influence the lay-date of their mate through their effect on the prelaying environment. We explore how social plasticity causing male indirect genetic effects can help or hinder population persistence when female genes underpinning lay-date and male genes influencing female's timing of reproduction both respond to climate-mediated selection. We extend quantitative genetic moving optimum models to predict the consequences of social plasticity on the maximum sustainable rate of temperature change, and evaluate our model using a combination of simulated data and empirical estimates from the literature. Our results suggest that predictions for population persistence may be biased if indirect genetic effects and cross-sex genetic correlations are not considered and that the extent of this bias depends on sex differences in how environmental change affects the optimal timing of reproduction. Our model highlights that more empirical work is needed to understand sex-specific effects of environmental change on phenology and the fitness consequences for population dynamics. While we discuss our results exclusively in the context of avian breeding phenology, the approach we take here can be generalized to many different contexts and types of social interaction.

Evolutionary game theory of continuous traits from a causal perspective

Modern evolutionary game theory typically deals with the evolution of continuous, quantitative traits under weak selection, allowing the incorporation of rich biological detail and complicated nonlinear interactions. While these models are commonly used to find candidates for evolutionary endpoints and to approximate evolutionary trajectories, a less appreciated property is their potential to expose and clarify the causal structure of evolutionary processes. The mathematical step of differentiation breaks a nonlinear model into additive components which are more intuitive to interpret, and when combined with a proper causal hypothesis, partial derivatives in such models have a causal meaning. Such an approach has been used in the causal analysis of game-theoretical models in an informal manner. Here we formalize this approach by linking evolutionary game theory to concepts developed in causal modelling over the past century, from path coefficients to the recently proposed causal derivative. There is a direct correspondence between the causal derivative and the derivative used in evolutionary game theory. Some game theoretical models (e.g. kin selection) consist of multiple causal derivatives. Components of these derivatives correspond to components of the causal derivative, to path coefficients, and to edges on a causal graph, formally linking evolutionary game theory to causal modelling. This article is part of the theme issue 'Half a century of evolutionary games: a synthesis of theory, application and future directions'.

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'.

A generalised approach to the study and understanding of adaptive evolution

Evolutionary theory has made large impacts on our understanding and management of the world, in part because it has been able to incorporate new data and new insights successfully. Nonetheless, there is currently a tension between certain biological phenomena and mainstream evolutionary theory. For example, how does the inheritance of molecular epigenetic changes fit into mainstream evolutionary theory? Is niche construction an evolutionary process? Is local adaptation via habitat choice also adaptive evolution? These examples suggest there is scope (and perhaps even a need) to broaden our views on evolution. We identify three aspects whose incorporation into a single framework would enable a more generalised approach to the understanding and study of adaptive evolution: (i) a broadened view of extended phenotypes; (ii) that traits can respond to each other; and (iii) that inheritance can be non-genetic. We use causal modelling to integrate these three aspects with established views on the variables and mechanisms that drive and allow for adaptive evolution. Our causal model identifies natural selection and non-genetic inheritance of adaptive parental responses as two complementary yet distinct and independent drivers of adaptive evolution. Both drivers are compatible with the Price equation; specifically, non-genetic inheritance of parental responses is captured by an often-neglected component of the Price equation. Our causal model is general and simplified, but can be adjusted flexibly in terms of variables and causal connections, depending on the research question and/or biological system. By revisiting the three examples given above, we show how to use it as a heuristic tool to clarify conceptual issues and to help design empirical research. In contrast to a gene-centric view defining evolution only in terms of genetic change, our generalised approach allows us to see evolution as a change in the whole causal structure, consisting not just of genetic but also of phenotypic and environmental variables.

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.

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.

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.

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.

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.

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.

Sociality and parasite transmission

Parasites and their social hosts form many different relationships. But what kind of selection regimes are important? A look at the parameters that determine fitness of the two parties suggests that social hosts differ from solitary ones primarily in the structure of transmission pathways. Because transmission is, both, the physical encounter of a new host and infecting it, several different elements determine parasite transmission success. These include spatial distance, genetic distance, or the temporal and ecological niche overlaps. Combing these elements into a ‘generalized transmission distance’ that determines parasite fitness aids in the identification of the critical steps. For example, short-distance transmission to genetically similar hosts within the social group is the most frequent process under sociality. Therefore, spatio-genetical distances are the main driver of parasite fitness. Vice versa, the generalized distance identifies the critical host defences. In this case, host defences should be primarily selected to defend against the within-group spread of an infection, especially among closely related group members.

Genetic Consequences of Biologically Altered Environments

Evolvable traits of organisms can alter the environment those organisms experience. While it is well appreciated that those modified environments can influence natural selection to which organisms are exposed, they can also influence the expression of genetic variances and covariances of traits under selection. When genetic variance and covariance change in response to changes in the evolving, modified environment, rates and outcomes of evolution also change. Here we discuss the basic mechanisms whereby organisms modify their environments, review how those modified environments have been shown to alter genetic variance and covariance, and discuss potential evolutionary consequences of such dynamics. With these dynamics, responses to selection can be more rapid and sustained, leading to more extreme phenotypes, or they can be slower and truncated, leading to more conserved phenotypes. Patterns of correlated selection can also change, leading to greater or less evolutionary independence of traits, or even causing convergence or divergence of traits, even when selection on them is consistent across environments. Developing evolutionary models that incorporate changes in genetic variances and covariances when environments themselves evolve requires developing methods to predict how genetic parameters respond to environments-frequently multifactorial environments. It also requires a population-level analysis of how traits of collections of individuals modify environments for themselves and/or others in a population, possibly in spatially explicit ways. Despite the challenges of elucidating the mechanisms and nuances of these processes, even qualitative predictions of how environment-modifying traits alter evolutionary potential are likely to improve projections of evolutionary outcomes.

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 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.