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.

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.

Maternal-zygotic co-evolution is one of the most common examples of indirect genetic effects. I investigate how maternal-zygotic gene interactions affect rates of evolution and adaptation. Using comparably parameterized population genetic models, I compare evolution to an abiotic environment with genotype-by-environment interaction (G × E) to evolution to a maternal environment with offspring genotype-by-maternal environment interaction (G × Gmaternal). There are strong parallels between the 2 models in the components of fitness variance but they differ in their rates of evolution measured in terms of ∆p, gene frequency change, or of ∆W, change in mean fitness. The Price Equation is used to partition ∆W into 2 components, one owing to the genetic variance in fitness by natural selection and a second owing to change in environment. Adaptive evolution is faster in the 2-locus model with G × Gmaternal with free recombination, than it is in the 1-locus model with G × E, because in the former the maternal genetic environment coevolves with the zygotic phenotype adapting to it. I discuss the relevance of these findings for the evolution of genes with indirect genetic effects.

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.

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.

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.

We use population genetics to model the evolution of a gene with an indirect effect owing to paternal care and with a second pleiotropic, direct effect on offspring viability. We use the model to illustrate how the common empirical practice of considering offspring viability as a component of parent fitness can confound a gene's direct and indirect fitness effects. We investigate when this confounding results in a distorted picture of overall evolution and when it does not. We find that the practice has no effect on mean fitness, W, but it does have an effect on the dynamics of gene frequency change, ∆q. We also find that, for some regions of parameter space associated with fitness trade-offs, the distortion is not only quantitative but also qualitative, obscuring the direction of gene frequency change. Because it affects the evolutionary dynamics, it also affects the expected amount of genetic variation at mutation-selection balance, an important consideration in molecular evolution. We discuss empirical techniques for separating direct from indirect effects and how field studies measuring the value of male paternal care might be improved by using them.

Mitochondria evolved from a union of microbial cells belonging to distinct lineages that were likely anaerobic. The evolution of eukaryotes required a massive reorganization of the 2 genomes and eventual adaptation to aerobic environments. The nutrients and oxygen that sustain eukaryotic metabolism today are processed in mitochondria through coordinated expression of 37 mitochondrial genes and over 1000 nuclear genes. This puts mitochondria at the nexus of gene-by-gene (G×G) and gene-by-environment (G×E) interactions that sustain life. Here we use a Drosophila model of mitonuclear genetic interactions to explore the notion that mitochondria are environments for the nuclear genome, and vice versa. We construct factorial combinations of mtDNA and nuclear chromosomes to test for epistatic interactions (G×G), and expose these mitonuclear genotypes to altered dietary environments to examine G×E interactions. We use development time and genome-wide RNAseq analyses to assess the relative contributions of mtDNA, nuclear chromosomes, and environmental effects on these traits (mitonuclear G×G×E). We show that the nuclear transcriptional response to alternative mitochondrial "environments" (G×G) has significant overlap with the transcriptional response of mitonuclear genotypes to altered dietary environments. These analyses point to specific transcription factors (e.g., giant) that mediated these interactions, and identified coexpressed modules of genes that may account for the overlap in differentially expressed genes. Roughly 20% of the transcriptome includes G×G genes that are concordant with G×E genes, suggesting that mitonuclear interactions are part of an organism's environment.

Recently, researchers have documented variation between groups in collective behavior. However, how genetic variation within and between groups contributes to population-level variation for collective behavior remains unclear. Understanding how genetic variation of group members relates to group-level phenotypes is evolutionarily important because there is increasing evidence that group-level behavioral variation influences fitness and that the genetic architecture of group-level traits can affect the evolutionary dynamics of traits. Social insects are ideal for studying the complex relationship between individual and group-level variation because they exhibit behavioral variation at multiple scales of organization. To explore how the genetic composition of groups affects collective behavior, we constructed groups of pharaoh ants (Monomorium pharaonis) from 33 genetically distinct colonies of known pedigree. The groups consisted of either all workers from the same single colony or workers from two genetically different colonies, and we assayed the exploration and aggression of the groups. We found that collective exploration, but not aggression, depended on the specific genotypic combination of group members, i.e., we found evidence for genotype-by-genotype epistasis for exploration. Group collective behavior did not depend on the pedigree relatedness between genotypes within groups. Overall, this study highlights that specific combinations of genotypes influence group-level phenotypes, emphasizing the importance of considering nonadditive effects of genotypic interactions between group members.

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.

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.

Mixed-species groups describe active associations among individuals of 2 or more species at the same trophic level. Mixed-species groups are important to key ecological and evolutionary processes such as competition and predation, and research that ignores the presence of other species risks ignoring a key aspect of the environment in which social behavior is expressed and selected. Despite the defining emphasis of active formation for mixed-species groups, surprisingly little is known about the mechanisms by which mixed-species groups form. Furthermore, insects have been almost completely ignored in the study of mixed-species groups, despite their taxonomic importance and relative prominence in the study of single-species groups. Here, we measured group formation processes in Drosophila melanogaster and its sister species, Drosophila simulans. Each species was studied alone, and together, and one population of D. melanogaster was also studied both alone and with another, phenotypically distinct D. melanogaster population, in a nested-factorial design. This approach differs from typical methods of studying mixed-species groups in that we could quantitatively compare group formation between single-population, mixed-population, and mixed-species treatments. Surprisingly, we found no differences between treatments in the number, size, or composition of groups that formed, suggesting that single- and mixed-species groups form through similar mechanisms of active attraction. However, we found that mixed-species groups showed elevated interspecies male-male interactions, relative to interpopulation or intergenotype interactions in single-species groups. Our findings expand the conceptual and taxonomic study of mixed-species groups while raising new questions about the mechanisms of group formation broadly.