Selection and evolution of causally covarying traits

Evolutionary-developmental (evo-devo) dynamics of hominin brain size

Brain size tripled in the human lineage over four million years, but why this occurred remains uncertain. Here, to study what caused this brain expansion, I mathematically model the evolutionary and developmental (evo-devo) dynamics of hominin brain size. The model recovers (1) the evolution of brain and body sizes of seven hominin species starting from brain and body sizes of the australopithecine scale, (2) the evolution of the hominin brain-body allometry and (3) major patterns of human development and evolution. I show that the brain expansion recovered is not caused by direct selection for brain size but by its genetic correlation with developmentally late preovulatory ovarian follicles. This correlation is generated over development if individuals experience a challenging ecology and seemingly cumulative culture, among other conditions. These findings show that the evolution of exceptionally adaptive traits may not be primarily caused by selection for them but by developmental constraints that divert selection.

The missing fraction problem as an episodes of selection problem

In evolutionary quantitative genetics, the missing fraction problem refers to a specific kind of bias in parameters estimated later in life that occurs when nonrandom subsets of phenotypes are missing from the population due to prior viability selection on correlated traits. The missing fraction problem thus arises when the following hold: (a) viability selection and (b) correlation between later-life traits and traits important for early-life survival. Although it is plausible that these conditions are widespread in wild populations, this problem has received little empirical attention. This may be natural: the problem could appear intractable, given that it is impossible to measure phenotypes of individuals that have previously died. However, it is not impossible to correctly measure lifetime selection, or correctly predict evolutionary trajectories, of later-life traits in the presence of the missing fraction. Two basic strategies are available. First, given phenotypic data on selected early life traits, well established but underused episodes of selection theory can yield correct values of evolutionary parameters throughout life. Second, when traits subjected to early-life viability selection are not known and/or measured, it is possible to use the genetic association of later-life traits with early-life viability to correctly infer important information about the consequences of prior viability selection for later-life traits. By carefully reviewing the basic nature of the missing fraction problem, and describing the tractable solutions to the problem, we hope that future studies will be able to be better designed to cope with the (likely pervasive) consequences of early-life viability selection.

A mathematical framework for evo-devo dynamics

Natural selection acts on phenotypes constructed over development, which raises the question of how development affects evolution. Classic evolutionary theory indicates that development affects evolution by modulating the genetic covariation upon which selection acts, thus affecting genetic constraints. However, whether genetic constraints are relative, thus diverting adaptation from the direction of steepest fitness ascent, or absolute, thus blocking adaptation in certain directions, remains uncertain. This limits understanding of long-term evolution of developmentally constructed phenotypes. Here we formulate a general, tractable mathematical framework that integrates age progression, explicit development (i.e., the construction of the phenotype across life subject to developmental constraints), and evolutionary dynamics, thus describing the evolutionary and developmental (evo-devo) dynamics. The framework yields simple equations that can be arranged in a layered structure that we call the evo-devo process, whereby five core elementary components generate all equations including those mechanistically describing genetic covariation and the evo-devo dynamics. The framework recovers evolutionary dynamic equations in gradient form and describes the evolution of genetic covariation from the evolution of genotype, phenotype, environment, and mutational covariation. This shows that genotypic and phenotypic evolution must be followed simultaneously to yield a dynamically sufficient description of long-term phenotypic evolution in gradient form, such that evolution described as the climbing of a fitness landscape occurs in "geno-phenotype" space. Genetic constraints in geno-phenotype space are necessarily absolute because the phenotype is related to the genotype by development. Thus, the long-term evolutionary dynamics of developed phenotypes is strongly non-standard: (1) evolutionary equilibria are either absent or infinite in number and depend on genetic covariation and hence on development; (2) developmental constraints determine the admissible evolutionary path and hence which evolutionary equilibria are admissible; and (3) evolutionary outcomes occur at admissible evolutionary equilibria, which do not generally occur at fitness landscape peaks in geno-phenotype space, but at peaks in the admissible evolutionary path where "total genotypic selection" vanishes if exogenous plastic response vanishes and mutational variation exists in all directions of genotype space. Hence, selection and development jointly define the evolutionary outcomes if absolute mutational constraints and exogenous plastic response are absent, rather than the outcomes being defined only by selection. Moreover, our framework provides formulas for the sensitivities of a recurrence and an alternative method to dynamic optimization (i.e., dynamic programming or optimal control) to identify evolutionary outcomes in models with developmentally dynamic traits. These results show that development has major evolutionary effects.

Personality traits differentially affect components of reproductive success in a Neotropical poison frog

Individual reproductive success has several components, including the acquisition of mating partners, offspring production, and offspring survival until adulthood. While the effects of certain personality traits-such as boldness or aggressiveness-on single components of reproductive success are well studied, we know little about the composite and multifaceted effects behavioural traits can have on all the aspects of reproductive success. Behavioural traits positively linked to one component of reproductive success might not be beneficial for other components, and these effects may differ between sexes. We investigated the influence of boldness, aggressiveness, and exploration on the number of mating partners, mating events, and offspring surviving until adulthood in males and females of the Neotropical poison frog Allobates femoralis. Behavioural traits had different-even opposite-effects on distinct components of reproductive success in both males and females. For example, males who displayed high levels of aggressiveness and exploration (or low levels of aggressiveness and exploration) managed to attract high number of mating partners, while males with low levels of boldness, low levels of aggressiveness, and high levels of exploration had the most offspring surviving until adulthood. Our results therefore suggest correlational selection favouring particular combinations of behavioural traits.

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'.

How development affects evolution

Natural selection acts on developmentally constructed phenotypes, but how does development affect evolution? This question prompts a simultaneous consideration of development and evolution. However, there has been a lack of general mathematical frameworks mechanistically integrating the two, which may have inhibited progress on the question. Here, we use a new mathematical framework that mechanistically integrates development into evolution to analyse how development affects evolution. We show that, while selection pushes genotypic and phenotypic evolution up the fitness landscape, development determines the admissible evolutionary pathway, such that evolutionary outcomes occur at path peaks rather than landscape peaks. Changes in development can generate path peaks, triggering genotypic or phenotypic diversification, even on constant, single-peak landscapes. Phenotypic plasticity, niche construction, extra-genetic inheritance, and developmental bias alter the evolutionary path and hence the outcome. Thus, extra-genetic inheritance can have permanent evolutionary effects by changing the developmental constraints, even if extra-genetically acquired elements are not transmitted to future generations. Selective development, whereby phenotype construction points in the adaptive direction, may induce adaptive or maladaptive evolution depending on the developmental constraints. Moreover, developmental propagation of phenotypic effects over age enables the evolution of negative senescence. Overall, we find that development plays a major evolutionary role.

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.

Some complexities in interpreting apparent effects of hitchhiking: A commentary on Gompert et al. (2022)

We write to address recent claims by regarding the potentially important and underappreciated phenomena of "indirect selection," the observation that neutral regions may be affected by natural selection. We argue both that this phenomenon-generally known as genetic hitchhiking-is neither new nor poorly studied, and that the patterns described by the authors have multiple alternative explanations.

The evolution of mating preferences for genetic attractiveness and quality in the presence of sensory bias

The aesthetic preferences of potential mates have driven the evolution of a baffling diversity of elaborate ornaments. Which fitness benefit-if any-choosers gain from expressing such preferences is controversial, however. Here, we simulate the evolution of preferences for multiple ornament types (e.g., "Fisherian," "handicap," and "indicator" ornaments) that differ in their associations with genes for attractiveness and other components of fitness. We model the costs of preference expression in a biologically plausible way, which decouples costly mate search from cost-free preferences. Ornaments of all types evolved in our model, but their occurrence was far from random. Females typically preferred ornaments that carried information about a male's quality, defined here as his ability to acquire and metabolize resources. Highly salient ornaments, which key into preexisting perceptual biases, were also more likely to evolve. When males expressed quality-dependent ornaments, females invested readily in costly mate search to locate preferred males. In contrast, the genetic benefits associated with purely arbitrary ornaments were insufficient to sustain highly costly mate search. Arbitrary ornaments could nonetheless "piggyback" on mate-search effort favored by other, quality-dependent ornaments. We further show that the potential to produce attractive male offspring ("sexy sons") can be as important as producing offspring of high general quality ("good genes") in shaping female preferences, even when preferred ornaments are quality dependent. Our model highlights the importance of mate-search effort as a driver of aesthetic coevolution.

Lanza V, Rodríguez-Beltrán J, Galán JC, San Millán A, Cantón R, Coque TM. Evolutionary Pathways and Trajectories in Antibiotic Resistance

Evolution is the hallmark of life. Descriptions of the evolution of microorganisms have provided a wealth of information, but knowledge regarding "what happened" has precluded a deeper understanding of "how" evolution has proceeded, as in the case of antimicrobial resistance. The difficulty in answering the "how" question lies in the multihierarchical dimensions of evolutionary processes, nested in complex networks, encompassing all units of selection, from genes to communities and ecosystems. At the simplest ontological level (as resistance genes), evolution proceeds by random (mutation and drift) and directional (natural selection) processes; however, sequential pathways of adaptive variation can occasionally be observed, and under fixed circumstances (particular fitness landscapes), evolution is predictable. At the highest level (such as that of plasmids, clones, species, microbiotas), the systems' degrees of freedom increase dramatically, related to the variable dispersal, fragmentation, relatedness, or coalescence of bacterial populations, depending on heterogeneous and changing niches and selective gradients in complex environments. Evolutionary trajectories of antibiotic resistance find their way in these changing landscapes subjected to random variations, becoming highly entropic and therefore unpredictable. However, experimental, phylogenetic, and ecogenetic analyses reveal preferential frequented paths (highways) where antibiotic resistance flows and propagates, allowing some understanding of evolutionary dynamics, modeling and designing interventions. Studies on antibiotic resistance have an applied aspect in improving individual health, One Health, and Global Health, as well as an academic value for understanding evolution. Most importantly, they have a heuristic significance as a model to reduce the negative influence of anthropogenic effects on the environment.

Detecting patterns of correlational selection with sampling error: A simulation study

The adoption of a multivariate perspective of selection implies the existence of multivariate adaptive peaks and pervasive correlational selection that promotes co-adaptation between traits. However, to test for the ubiquity of correlational selection in nature, we must first have a sense of how well can we estimate multivariate nonlinear selection (i.e., the γ-matrix) in the face of sampling error. To explore the sampling properties of estimated γ-matrices, we simulated inidividual traits and fitness under a wide range of sample sizes, using different strengths of correlational selection and of stabilizing selection, combined with different number of traits under selection, different amounts of residual variance in fitness, and distinct patterns of selection. We then ran nonlinear regressions with these simulated datasets to simulate γ-matrices after adding random error to individual fitness. To test how well could we detect the imposed pattern of correlational selection at different sample sizes, we measured the similarity between simulated and imposed γ-matrices. We show that detection of the pattern of correlational selection is highly dependent on the total strength of selection on traits and on the amount of residual variance in fitness. Minimum sample size needs to be at least 500 to precisely estimate the pattern of correlational selection. Furthermore, a pattern of selection in which different sets of traits contribute to different functions is the easiest to diagnose, even when using a large number of traits (10 traits), but with sample sizes in the order of 1000 individuals. Consequently, we recommend working with sets of traits from distinct functional complexes and fitness proxies less prone to effects of environmental and demographic stochasticity to test for correlational selection with lower sample sizes.

Evolvability: A Quantitative-Genetics Perspective

The concept of evolvability emerged in the early 1990s and soon became fashionable as a label for different streams of research in evolutionary biology. In evolutionary quantitative genetics, evolvability is defined as the ability of a population to respond to directional selection. This differs from other fields by treating evolvability as a property of populations rather than organisms or lineages and in being focused on quantification and short-term prediction rather than on macroevolution. While the term evolvability is new to quantitative genetics, many of the associated ideas and research questions have been with the field from its inception as biometry. Recent research on evolvability is more than a relabeling of old questions, however. New operational measures of evolvability have opened possibilities for understanding adaptation to rapid environmental change, assessing genetic constraints, and linking micro- and macroevolution.

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.

Predicting evolutionary change at the DNA level in a natural Mimulus population

Evolution by natural selection occurs when the frequencies of genetic variants change because individuals differ in Darwinian fitness components such as survival or reproductive success. Differential fitness has been demonstrated in field studies of many organisms, but it remains unclear how well we can quantitatively predict allele frequency changes from fitness measurements. Here, we characterize natural selection on millions of Single Nucleotide Polymorphisms (SNPs) across the genome of the annual plant Mimulus guttatus. We use fitness estimates to calibrate population genetic models that effectively predict allele frequency changes into the next generation. Hundreds of SNPs experienced "male selection" in 2013 with one allele at each SNP elevated in frequency among successful male gametes relative to the entire population of adults. In the following generation, allele frequencies at these SNPs consistently shifted in the predicted direction. A second year of study revealed that SNPs had effects on both viability and reproductive success with pervasive trade-offs between fitness components. SNPs favored by male selection were, on average, detrimental to survival. These trade-offs (antagonistic pleiotropy and temporal fluctuations in fitness) may be essential to the long-term maintenance of alleles. Despite the challenges of measuring selection in the wild, the strong correlation between predicted and observed allele frequency changes suggests that population genetic models have a much greater role to play in forward-time prediction of evolutionary change.

Using ecological context to interpret spatiotemporal variation in natural selection

Spatiotemporal variation in natural selection is expected, but difficult to estimate. Pollinator-mediated selection on floral traits provides a good system for understanding and linking variation in selection to differences in ecological context. We studied pollinator-mediated selection in five populations of Dalechampia scandens (Euphorbiaceae) in Costa Rica and Mexico. Using a nonlinear path-analytical approach, we assessed several functional components of selection, and linked variation in pollinator-mediated selection across time and space to variation in pollinator assemblages. After correcting for estimation error, we detected moderate variation in net selection on two out of four blossom traits. Both the opportunity for selection and the mean strength of selection decreased with increasing reliability of cross-pollination. Selection for pollinator attraction was consistently positive and stronger on advertisement than reward traits. Selection on traits affecting pollen transfer from the pollinator to the stigmas was strong only when cross-pollination was unreliable and there was a mismatch between pollinator and blossom size. These results illustrate how consideration of trait function and ecological context can facilitate both the detection and the causal understanding of spatiotemporal variation in natural selection.

How general is cognitive ability in non-human animals? A meta-analytical and multi-level reanalysis approach

General intelligence has been a topic of high interest for over a century. Traditionally, research on general intelligence was based on principal component analyses and other dimensionality reduction approaches. The advent of high-speed computing has provided alternative statistical tools that have been used to test predictions of human general intelligence. In comparison, research on general intelligence in non-human animals is in its infancy and still relies mostly on factor-analytical procedures. Here, we argue that dimensionality reduction, when incorrectly applied, can lead to spurious results and limit our understanding of ecological and evolutionary causes of variation in animal cognition. Using a meta-analytical approach, we show, based on 555 bivariate correlations, that the average correlation among cognitive abilities is low (r = 0.185; 95% CI: 0.087-0.287), suggesting relatively weak support for general intelligence in animals. We then use a case study with relatedness (genetic) data to demonstrate how analysing traits using mixed models, without dimensionality reduction, provides new insights into the structure of phenotypic variance among cognitive traits, and uncovers genetic associations that would be hidden otherwise. We hope this article will stimulate the use of alternative tools in the study of cognition and its evolution in animals.

Analogues of the fundamental and secondary theorems of selection, assuming a log-normal distribution of expected fitness

It is increasingly common for studies of evolution in natural populations to infer the quantitative genetic basis of fitness (e.g., the additive genetic variance for relative fitness), and of relationships between traits and fitness (e.g., the additive genetic covariance of traits with relative fitness). There is a certain amount of tension between the theory that justifies estimating these quantities, and methodological considerations relevant to their empirical estimation. In particular, the additive genetic variances and covariances involving relative fitness are justified by the fundamental and secondary theorems of selection, which pertain to relative fitness on the scale that it is expressed. However, naturally-occurring fitness distributions lend themselves to analysis with generalized linear mixed models (GLMMs), which conduct analysis on a different scale, typically on the scale of the logarithm of expected values, from which fitness is expressed. This note presents relations between evolutionary change in traits, and the rate of adaptation in fitness, and log quantitative genetic parameters of fitness, potentially reducing the discord between theoretical and methodological considerations to the operationalization of the secondary and fundamental theorems of selection.

Quantification and decomposition of environment-selection relationships

In nature, selection varies across time in most environments, but we lack an understanding of how specific ecological changes drive this variation. Ecological factors can alter phenotypic selection coefficients through changes in trait distributions or individual mean fitness, even when the trait-absolute fitness relationship remains constant. We apply and extend a regression-based approach in a population of Soay sheep (Ovis aries) and suggest metrics of environment-selection relationships that can be compared across studies. We then introduce a novel method that constructs an environmentally structured fitness function. This allows calculation of full (as in existing approaches) and partial (acting separately through the absolute fitness function slope, mean fitness, and phenotype distribution) sensitivities of selection to an ecological variable. Both approaches show positive overall effects of density on viability selection of lamb mass. However, the second approach demonstrates that this relationship is largely driven by effects of density on mean fitness, rather than on the trait-fitness relationship slope. If such mechanisms of environmental dependence of selection are common, this could have important implications regarding the frequency of fluctuating selection, and how previous selection inferences relate to longer term evolutionary dynamics.

Life-history evolution under fluctuating density-dependent selection and the adaptive alignment of pace-of-life syndromes

We present a novel perspective on life-history evolution that combines recent theoretical advances in fluctuating density-dependent selection with the notion of pace-of-life syndromes (POLSs) in behavioural ecology. These ideas posit phenotypic co-variation in life-history, physiological, morphological and behavioural traits as a continuum from the highly fecund, short-lived, bold, aggressive and highly dispersive 'fast' types at one end of the POLS to the less fecund, long-lived, cautious, shy, plastic and socially responsive 'slow' types at the other. We propose that such variation in life histories and the associated individual differences in behaviour can be explained through their eco-evolutionary dynamics with population density - a single and ubiquitous selective factor that is present in all biological systems. Contrasting regimes of environmental stochasticity are expected to affect population density in time and space and create differing patterns of fluctuating density-dependent selection, which generates variation in fast versus slow life histories within and among populations. We therefore predict that a major axis of phenotypic co-variation in life-history, physiological, morphological and behavioural traits (i.e. the POLS) should align with these stochastic fluctuations in the multivariate fitness landscape created by variation in density-dependent selection. Phenotypic plasticity and/or genetic (co-)variation oriented along this major POLS axis are thus expected to facilitate rapid and adaptively integrated changes in various aspects of life histories within and among populations and/or species. The fluctuating density-dependent selection POLS framework presented here therefore provides a series of clear testable predictions, the investigation of which should further our fundamental understanding of life-history evolution and thus our ability to predict natural population dynamics.

A guide to using a multiple-matrix animal model to disentangle genetic and nongenetic causes of phenotypic variance

Non-genetic influences on phenotypic traits can affect our interpretation of genetic variance and the evolutionary potential of populations to respond to selection, with consequences for our ability to predict the outcomes of selection. Long-term population surveys and experiments have shown that quantitative genetic estimates are influenced by nongenetic effects, including shared environmental effects, epigenetic effects, and social interactions. Recent developments to the "animal model" of quantitative genetics can now allow us to calculate precise individual-based measures of non-genetic phenotypic variance. These models can be applied to a much broader range of contexts and data types than used previously, with the potential to greatly expand our understanding of nongenetic effects on evolutionary potential. Here, we provide the first practical guide for researchers interested in distinguishing between genetic and nongenetic causes of phenotypic variation in the animal model. The methods use matrices describing individual similarity in nongenetic effects, analogous to the additive genetic relatedness matrix. In a simulation of various phenotypic traits, accounting for environmental, epigenetic, or cultural resemblance between individuals reduced estimates of additive genetic variance, changing the interpretation of evolutionary potential. These variances were estimable for both direct and parental nongenetic variances. Our tutorial outlines an easy way to account for these effects in both wild and experimental populations. These models have the potential to add to our understanding of the effects of genetic and nongenetic effects on evolutionary potential. This should be of interest both to those studying heritability, and those who wish to understand nongenetic variance.

Natural selection for body shape in resource polymorphic Icelandic Arctic charr

Resource polymorphisms exhibit remarkable intraspecific diversity and in many cases are expected to be maintained by diversifying selection. Phenotypic trade-offs can constrain morphologically intermediate individuals from effectively exploiting both alternate resources, resulting in ecological barriers to gene flow. Determining if and how phenotypic trade-offs cause fitness variation in the wild is challenging because of phenotypic and environmental correlations associated with alternative resource strategies. We investigated multiple pathways through which morphology could affect organismal performance, as measured by growth rate, and whether these effects generate diversifying selection in polymorphic Icelandic Arctic charr (Salvelinus alpinus) populations. We considered direct effects of morphology on growth and indirect effects via trophic resource use, estimated by stable isotopic signatures, and via parasitism associated with trophic resources. We sampled over 3 years in (lakes) Thingvallavatn and Vatnshlíðarvatn using the extended selection gradient path analytical approach and estimating size-dependent mortality. We found evidence for diversifying selection only in Thingvallavatn: more streamlined and terminally mouthed planktivore charr experienced greater growth, with the opposite pattern in small benthic charr. However, this effect was mediated by parasitism and nontrophic pathways, rather than trophic performance as often expected. Detection of between-morph differences in the presence (Vatnshlíðarvatn) and direction (Thingvallavatn) of size-dependent mortality, together with nontrophic effects of shape, suggests that a morphological trophic performance explanation for polymorphism is insufficient. This rare insight into selection during early diversification suggests that a complex of interacting local factors must be considered to understand how phenotype influences fitness, despite morphological variation reflecting intuitive trade-off explanations.

How to quantify (the response to) sexual selection on traits

Natural selection operates via fitness components like mating success, fecundity, and longevity, which can be understood as intermediaries in the causal process linking traits to fitness. In particular, sexual selection occurs when traits influence mating or fertilization success, which, in turn, influences fitness. We show how to quantify both these steps in a single path analysis, leading to better estimates of the strength of sexual selection. Our model controls for confounding variables, such as body size or condition, when estimating the relationship between mating and reproductive success. Correspondingly, we define the Bateman gradient and the Jones index using partial rather than simple regressions, which better captures how they are commonly interpreted. The model can be applied both to purely phenotypic data and to quantitative genetic parameters estimated using information on relatedness. The phenotypic approach breaks down selection differentials into a sexually selected and a "remainder" component. The quantitative genetic approach decomposes the estimated evolutionary response to selection analogously. We apply our method to analyze sexual selection in male dusky pipefish, Syngnathus floridae, and in two simulated datasets. We highlight conceptual and statistical limitations of previous path-based approaches, which can lead to substantial misestimation of sexual selection.

Behavioural mediators of genetic life-history trade-offs: a test of the pace-of-life syndrome hypothesis in field crickets

The pace-of-life syndrome (POLS) hypothesis predicts associations between life history and 'risky' behaviours. Individuals with 'fast' lifestyles should develop faster, reproduce earlier, exhibit more risk-prone behaviours, and die sooner than those with 'slow' lifestyles. While support for POLS has been equivocal to date, studies have relied on individual-level (phenotypic) patterns in which genetic trade-offs may be masked by environmental effects on phenotypes. We estimated genetic correlations between life history (development, lifespan, size) and risky behaviours (exploration, aggression) in a pedigreed population of Mediterranean field crickets (Gryllus bimaculatus). Path analyses showed that behaviours mediated some genetic relationships between life history traits, though not those involved in trade-offs. Thus, while specific predictions of POLS theory were not supported, genetic integration of behaviour and life history was present. This implies a major role for risky behaviours in life history evolution.

Quantitative genetic methods depending on the nature of the phenotypic trait

A consequence of the assumptions of the infinitesimal model, one of the most important theoretical foundations of quantitative genetics, is that phenotypic traits are predicted to be most often normally distributed (so-called Gaussian traits). But phenotypic traits, especially those interesting for evolutionary biology, might be shaped according to very diverse distributions. Here, I show how quantitative genetics tools have been extended to account for a wider diversity of phenotypic traits using first the threshold model and then more recently using generalized linear mixed models. I explore the assumptions behind these models and how they can be used to study the genetics of non-Gaussian complex traits. I also comment on three recent methodological advances in quantitative genetics that widen our ability to study new kinds of traits: the use of "modular" hierarchical modeling (e.g., to study survival in the context of capture-recapture approaches for wild populations); the use of aster models to study a set of traits with conditional relationships (e.g., life-history traits); and, finally, the study of high-dimensional traits, such as gene expression.

Sexual selection on male body size, genital length and heterozygosity: Consistency across habitats and social settings

Spatial and temporal variation in environmental factors and the social setting can help to maintain genetic variation in sexually selected traits if it affects the strength of directional selection. A key social parameter which affects the intensity of, and sometimes predicts the response to, mating competition is the operational sex ratio (OSR; ratio of receptive males to females). How the OSR affects selection for specific male traits is poorly understood. It is also unclear how sexual selection is affected by interactions between the OSR and environmental factors, such as habitat complexity, that alter key male-female interactions such as mate encounter rates. Here, we experimentally manipulated the OSR and habitat complexity and quantified sexual selection on male mosquitofish (Gambusia holbrooki) by directly measuring male reproductive success (i.e. paternity). We show that despite a more equitable sharing of paternity (i.e. higher levels of multiple paternity) under a male-biased OSR, selection on focal male traits was unaffected by the OSR or habitat complexity. Instead, sexual selection consistently, and significantly, favoured smaller bodied males, males with higher genome wide heterozygosity (based on >3,000 SNP markers) and males with a relatively long gonopodium (intromittent organ). Our results show that sexual selection on male body size, relative genital size and heterozygosity in this system is consistent across environments that vary in ecological parameters that are expected to influence mate encounter rates.

Quantitative Genetic Variation in, and Environmental Effects on, Pathogen Resistance and Temperature-Dependent Disease Severity in a Wild Trout

Health after pathogen contact varies among individuals because of differences in pathogen load (which is limited by resistance) and disease severity in response to pathogen load (which is limited by tolerance). To understand pathogen-induced host evolution, it is critical to know not only the relative contributions of nongenetic and genetic variation to resistance and tolerance but also how they change environmentally. We quantified nongenetic and genetic variation in parasite load and the associated temperature-dependent disease among trout siblings from two rivers. We detected a genetic variance for parasite load 6.6 times as large in the colder river. By contrast, genetic variance for disease traits tended to be larger in the warmer river, where the disease was manifested more severely. The relationships between disease severity and pathogen load (tolerance) exhibited plateaus at low pathogen load and stronger steepening slopes at high pathogen load in the warmer river. Our study demonstrates the environmental influence on disease severity, nongenetic and genetic variance for health-damage-limiting host abilities, and the shape of tolerance curves. Environmental variability is predicted to govern the presence and intensity of selection, change the relative contributions of nongenetic and genetic variance, and therefore hamper evolution toward more resistant and tolerant hosts.

Subtle but ubiquitous selection on body size in a natural population of collared flycatchers over 33 years

Understanding the magnitude and long-term patterns of selection in natural populations is of importance, for example, when analysing the evolutionary impact of climate change. We estimated univariate and multivariate directional, quadratic and correlational selection on four morphological traits (adult wing, tarsus and tail length, body mass) over a time period of 33 years (≈ 19 000 observations) in a nest-box breeding population of collared flycatchers (Ficedula albicollis). In general, selection was weak in both males and females over the years regardless of fitness measure (fledged young, recruits and survival) with only few cases with statistically significant selection. When data were analysed in a multivariate context and as time series, a number of patterns emerged; there was a consistent, but weak, selection for longer wings in both sexes, selection was stronger on females when the number of fledged young was used as a fitness measure, there were no indications of sexually antagonistic selection, and we found a negative correlation between selection on tarsus and wing length in both sexes but using different fitness measures. Uni- and multivariate selection gradients were correlated only for wing length and mass. Multivariate selection gradient vectors were longer than corresponding vector of univariate gradients and had more constrained direction. Correlational selection had little importance. Overall, the fitness surface was more or less flat with few cases of significant curvature, indicating that the adaptive peak with regard to body size in this species is broader than the phenotypic distribution, which has resulted in weak estimates of selection.

Bigger Is Fitter? Quantitative Genetic Decomposition of Selection Reveals an Adaptive Evolutionary Decline of Body Mass in a Wild Rodent Population

In natural populations, quantitative trait dynamics often do not appear to follow evolutionary predictions. Despite abundant examples of natural selection acting on heritable traits, conclusive evidence for contemporary adaptive evolution remains rare for wild vertebrate populations, and phenotypic stasis seems to be the norm. This so-called “stasis paradox” highlights our inability to predict evolutionary change, which is especially concerning within the context of rapid anthropogenic environmental change. While the causes underlying the stasis paradox are hotly debated, comprehensive attempts aiming at a resolution are lacking. Here, we apply a quantitative genetic framework to individual-based long-term data for a wild rodent population and show that despite a positive association between body mass and fitness, there has been a genetic change towards lower body mass. The latter represents an adaptive response to viability selection favouring juveniles growing up to become relatively small adults, i.e., with a low potential adult mass, which presumably complete their development earlier. This selection is particularly strong towards the end of the snow-free season, and it has intensified in recent years, coinciding which a change in snowfall patterns. Importantly, neither the negative evolutionary change, nor the selective pressures that drive it, are apparent on the phenotypic level, where they are masked by phenotypic plasticity and a non causal (i.e., non genetic) positive association between body mass and fitness, respectively. Estimating selection at the genetic level enabled us to uncover adaptive evolution in action and to identify the corresponding phenotypic selective pressure. We thereby demonstrate that natural populations can show a rapid and adaptive evolutionary response to a novel selective pressure, and that explicitly (quantitative) genetic models are able to provide us with an understanding of the causes and consequences of selection that is superior to purely phenotypic estimates of selection and evolutionary change.

A population of snow voles provides a rare example of contemporary adaptive evolution in the wild, but without a quantitative genetic perspective this genetic change, and the selective pressure that underlies it, would have gone undetected.

Biologists struggle to demonstrate adaptive evolution in wild populations: while they routinely observe natural selection on heritable traits, in only a handful of cases could they demonstrate an evolutionary response. Although various explanations for this paradox have been proposed, comprehensive empirical tests are lacking. Over the past years, we have therefore studied an alpine population of snow voles. Following all individuals throughout their lives, we found that body mass is heritable and that heavy voles have a higher fitness. Nevertheless, mean body mass did not increase. To resolve this, we disentangled the role of genes and the environment in shaping body mass. This revealed that the population did evolve, but that this was masked by environmental variation. Furthermore, although the genetic change was adaptive, it was opposite to our initial expectation: the population evolved to become lighter, not heavier. This was because although heavy voles have the highest fitness, their mass does not cause high fitness. Instead, it is the voles with the genes for being light that do best, especially when the first winter snow arrives early. This shows that populations can evolve rapidly, but that without a genetic perspective, this, and its underlying mechanism, may go undetected.

Discovering phenotypic causal structure from nonexperimental data

The evolutionary potential of organisms depends on how their parts are structured into a cohesive whole. A major obstacle for empirical studies of phenotypic organization is that observed associations among characters usually confound different causal pathways such as pleiotropic modules, interphenotypic causal relationships and environmental effects. The present article proposes causal search algorithms as a new tool to distinguish these different modes of phenotypic integration. Without assuming an a priori structure, the algorithms seek a class of causal hypotheses consistent with independence relationships holding in observational data. The technique can be applied to discover causal relationships among a set of measured traits and to distinguish genuine selection from spurious correlations. The former application is illustrated with a biological data set of rat morphological measurements previously analysed by Cheverud et al. (Evolution 1983, 37, 895).

Evolutionary quantitative genetics of nonlinear developmental systems

In quantitative genetics, the effects of developmental relationships among traits on microevolution are generally represented by the contribution of pleiotropy to additive genetic covariances. Pleiotropic additive genetic covariances arise only from the average effects of alleles on multiple traits, and therefore the evolutionary importance of nonlinearities in development is generally neglected in quantitative genetic views on evolution. However, nonlinearities in relationships among traits at the level of whole organisms are undeniably important to biology in general, and therefore critical to understanding evolution. I outline a system for characterizing key quantitative parameters in nonlinear developmental systems, which yields expressions for quantities such as trait means and phenotypic and genetic covariance matrices. I then develop a system for quantitative prediction of evolution in nonlinear developmental systems. I apply the system to generating a new hypothesis for why direct stabilizing selection is rarely observed. Other uses will include separation of purely correlative from direct and indirect causal effects in studying mechanisms of selection, generation of predictions of medium-term evolutionary trajectories rather than immediate predictions of evolutionary change over single generation time-steps, and the development of efficient and biologically motivated models for separating additive from epistatic genetic variances and covariances.

Natural selection for earlier male arrival to breeding grounds through direct and indirect effects in a migratory songbird

For migratory birds, the earlier arrival of males to breeding grounds is often expected to have fitness benefits. However, the selection differential on male arrival time has rarely been decomposed into the direct effect of male arrival and potential indirect effects through female traits. We measured the directional selection differential on male arrival time in the pied flycatcher (Ficedula hypoleuca) using data from 6 years and annual number of fledglings as the fitness proxy. Using structural equation modeling, we were able to take into account the temporal structure of the breeding cycle and the hierarchy between the examined traits. We found directional selection differentials for earlier male arrival date and earlier female laying date, as well as strong selection differential for larger clutch size. These selection differentials were due to direct selection only as indirect selection for these traits was nonsignificant. When decomposing the direct selection for earlier male arrival into direct and indirect effects, we discovered that it was almost exclusively due to the direct effect of male arrival date on fitness and not due to its indirect effects via female traits. In other words, we showed for the first time that there is a direct effect of male arrival date on fitness while accounting for those effects that are mediated by effects of the social partner. Our study thus indicates that natural selection directly favored earlier male arrival in this flycatcher population.

A multivariate analysis of genetic constraints to life history evolution in a wild population of red deer

Evolutionary theory predicts that genetic constraints should be widespread, but empirical support for their existence is surprisingly rare. Commonly applied univariate and bivariate approaches to detecting genetic constraints can underestimate their prevalence, with important aspects potentially tractable only within a multivariate framework. However, multivariate genetic analyses of data from natural populations are challenging because of modest sample sizes, incomplete pedigrees, and missing data. Here we present results from a study of a comprehensive set of life history traits (juvenile survival, age at first breeding, annual fecundity, and longevity) for both males and females in a wild, pedigreed, population of red deer (Cervus elaphus). We use factor analytic modeling of the genetic variance–covariance matrix (G) to reduce the dimensionality of the problem and take a multivariate approach to estimating genetic constraints. We consider a range of metrics designed to assess the effect of G on the deflection of a predicted response to selection away from the direction of fastest adaptation and on the evolvability of the traits. We found limited support for genetic constraint through genetic covariances between traits, both within sex and between sexes. We discuss these results with respect to other recent findings and to the problems of estimating these parameters for natural populations.