Conserved G-matrices of morphological and life-history traits among continental and island blue tit populations

Exact expressions and numerical evaluation of average evolvability measures for characterizing and comparing [Formula: see text] matrices

Theory predicts that the additive genetic covariance ([Formula: see text]) matrix determines a population's short-term (in)ability to respond to directional selection-evolvability in the Hansen-Houle sense-which is typically quantified and compared via certain scalar indices called evolvability measures. Often, interest is in obtaining the averages of these measures across all possible selection gradients, but explicit formulae for most of these average measures have not been known. Previous authors relied either on approximations by the delta method, whose accuracy is generally unknown, or Monte Carlo evaluations (including the random skewers analysis), which necessarily involve random fluctuations. This study presents new, exact expressions for the average conditional evolvability, average autonomy, average respondability, average flexibility, average response difference, and average response correlation, utilizing their mathematical structures as ratios of quadratic forms. The new expressions are infinite series involving top-order zonal and invariant polynomials of matrix arguments, and can be numerically evaluated as their partial sums with, for some measures, known error bounds. Whenever these partial sums numerically converge within reasonable computational time and memory, they will replace the previous approximate methods. In addition, new expressions are derived for the average measures under a general normal distribution for the selection gradient, extending the applicability of these measures into a substantially broader class of selection regimes.

A quantitative genetics perspective on the body-mass scaling of metabolic rate

Widely observed allometric scaling (log-log slope<1) of metabolic rate (MR) with body mass (BM) in animals has been frequently explained using functional mechanisms, but rarely studied from the perspective of multivariate quantitative genetics. This is unfortunate, given that the additive genetic slope (bA) of the MR-BM relationship represents the orientation of the 'line of least genetic resistance' along which MR and BM may most likely evolve. Here, we calculated bA in eight species. Although most bA values were within the range of metabolic scaling exponents reported in the literature, uncertainty of each bA estimate was large (only one bA was significantly lower than 3/4 and none were significantly different from 2/3). Overall, the weighted average for bA (0.667±0.098 95% CI) is consistent with the frequent observation that metabolic scaling exponents are negatively allometric in animals (b<1). Although bA was significantly positively correlated with the phenotypic scaling exponent (bP) across the sampled species, bP was usually lower than bA, as reflected in a (non-significantly) lower weighted average for bP (0.596±0.100). This apparent discrepancy between bA and bP resulted from relatively shallow MR-BM scaling of the residuals [weighted average residual scaling exponent (be)=0.503±0.128], suggesting regression dilution (owing to measurement error and within-individual variance) causing a downward bias in bP. Our study shows how the quantification of the genetic scaling exponent informs us about potential constraints on the correlated evolution of MR and BM, and by doing so has the potential to bridge the gap between micro- and macro-evolutionary studies of scaling allometry.

Differential effects of steroid hormones on levels of broad-sense heritability in a wild bird: possible mechanism of environment × genetic variance interaction?

Genetic variation is one of the key concepts in evolutionary biology and an important prerequisite of evolutionary change. However, we know very little about processes that modulate its levels in wild populations. In particular, we still are to understand why genetic variances often depend on environmental conditions. One of possible environment-sensitive modulators of observed levels of genetic variance are maternal effects. In this study we attempt to experimentally test the hypothesis that maternally transmitted agents (e.g. hormones) may influence the expression of genetic variance in quantitative traits in the offspring. We manipulated the levels of steroid hormones (testosterone and corticosterone) in eggs laid by blue tits in a wild population. Our experimental setup allowed for full crossing of genetic and rearing effects with the experimental manipulation. We observed that birds treated with corticosterone exhibited a significant decrease in broad-sense genetic variance of tarsus length, and an increase in this component in body mass on the 2nd day post-hatching. Our study indicates, that maternally transmitted substances such as hormones may have measurable impact on the levels of genetic variance and hence, on the evolutionary potential of quantitative traits.

Phenotypic plasticity drives phenological changes in a Mediterranean blue tit population

Earlier phenology induced by climate change, such as the passerines' breeding time, is observed in many natural populations. Understanding the nature of such changes is key to predict the responses of wild populations to climate change. Genetic changes have been rarely investigated for laying date, though it has been shown to be heritable and under directional selection, suggesting that the trait could evolve. In a Corsican blue tit population, the birds' laying date has significantly advanced over 40 years, and we here determine whether this response is of plastic or evolutionary origin, by comparing the predictions of the breeder's and the Robertson-Price (STS) equations, to the observed genetic changes. We compare the results obtained for two fitness proxies (fledgling and recruitment success), using models accounting for their zero inflation. Because the trait appears heritable and under directional selection, the breeder's equation predicts that genetic changes could drive a significant part of the phenological change observed. We, however, found that fitness proxies and laying date are not genetically correlated. The STS, therefore, predicts no evolution of the breeding time, predicting correctly the absence of trend in breeding values. Our results also emphasize that when investigating selection on a plastic trait under fluctuating selection, part of the fitness-trait phenotypic covariance can be due to within individual covariance. In the case of repeated measurements, splitting within and between individual covariance can shift our perspective on the actual intensity of selection over multiple selection episodes, shedding light on the potential for the trait to evolve.

Multivariate analysis of morphology, behaviour, growth and developmental timing in hybrids brings new insights into the divergence of sympatric Arctic charr morphs

BACKGROUND

Studying the development of fitness related traits in hybrids from populations diverging in sympatry is a fundamental approach to understand the processes of speciation. However, such traits are often affected by covariance structures that complicate the comprehension of these processes, especially because the interactive relationships between traits of different nature (e.g. morphology, behaviour, life-history) remain largely unknown in this context. In a common garden setup, we conducted an extensive examination of a large suit of traits putatively involved in the divergence of two morphs of Arctic charr (Salvelinus alpinus), and investigated the consequences of potential patterns of trait covariance on the phenotype of their hybrids. These traits were measured along ontogeny and involved growth, yolk sac resorption, developmental timing (hatching and the onset of exogeneous feeding), head morphology and feeding behaviour.

RESULTS

Growth trajectories provided the strongest signal of phenotypic divergence between the two charr. Strikingly, the first-generation hybrids did not show intermediate nor delayed growth but were similar to the smallest morph, suggesting parental biases in the inheritance of growth patterns. However, we did not observe extensive multivariate trait differences between the two morphs and their hybrids. Growth was linked to head morphology (suggesting that morphological variations in early juveniles relate to simple allometric effects) but this was the only strong signal of covariance observed between all the measured traits. Furthermore, we did not report evidence for differences in overall phenotypic variance between morphs, nor for enhanced phenotypic variability in their hybrids.

CONCLUSION

Our study shed light on the multivariate aspect of development in a context of adaptive divergence. The lack of evidence for the integration of most traits into a single covariance structure suggested that phenotypic constraints may not always favour nor impede divergence toward ecological niches differing in numerous physical and ecological variables, as observed in the respective habitats of the two charr. Likewise, the role of hybridization as a disruptive agent of trait covariance may not necessarily be significant in the evolution of populations undergoing resource polymorphism.

Connecting the data landscape of long-term ecological studies: The SPI-Birds data hub

The integration and synthesis of the data in different areas of science is drastically slowed and hindered by a lack of standards and networking programmes. Long-term studies of individually marked animals are not an exception. These studies are especially important as instrumental for understanding evolutionary and ecological processes in the wild. Furthermore, their number and global distribution provides a unique opportunity to assess the generality of patterns and to address broad-scale global issues (e.g. climate change). To solve data integration issues and enable a new scale of ecological and evolutionary research based on long-term studies of birds, we have created the SPI-Birds Network and Database (www.spibirds.org)-a large-scale initiative that connects data from, and researchers working on, studies of wild populations of individually recognizable (usually ringed) birds. Within year and a half since the establishment, SPI-Birds has recruited over 120 members, and currently hosts data on almost 1.5 million individual birds collected in 80 populations over 2,000 cumulative years, and counting. SPI-Birds acts as a data hub and a catalogue of studied populations. It prevents data loss, secures easy data finding, use and integration and thus facilitates collaboration and synthesis. We provide community-derived data and meta-data standards and improve data integrity guided by the principles of Findable, Accessible, Interoperable and Reusable (FAIR), and aligned with the existing metadata languages (e.g. ecological meta-data language). The encouraging community involvement stems from SPI-Bird's decentralized approach: research groups retain full control over data use and their way of data management, while SPI-Birds creates tailored pipelines to convert each unique data format into a standard format. We outline the lessons learned, so that other communities (e.g. those working on other taxa) can adapt our successful model. Creating community-specific hubs (such as ours, COMADRE for animal demography, etc.) will aid much-needed large-scale ecological data integration.

Introduced populations of ragweed show as much evolutionary potential as native populations

Invasive species are a global economic and ecological problem. They also offer an opportunity to understand evolutionary processes in a colonizing context. The impacts of evolutionary factors, such as genetic variation, on the invasion process are increasingly appreciated, but there remain gaps in the empirical literature. The adaptive potential of populations can be quantified using genetic variance-covariance matrices (G), which encapsulate the heritable genetic variance in a population. Here, we use a multivariate Bayesian approach to assess the adaptive potential of invasive populations of ragweed (Ambrosia artemisiifolia), a serious allergen and agricultural weed. We compared several aspects of genetic architecture and the structure of G matrices between three native and three introduced populations, based on phenotypic data collected in a field common garden experiment. We found moderate differences in the quantitative genetic architecture among populations, but we did not find that introduced populations suffer from a limited adaptive potential or increased genetic constraint compared with native populations. Ragweed has an annual life history, is an obligate outcrosser, and produces very large numbers of seeds and pollen grains. These characteristics, combined with the significant additive genetic variance documented here, suggest ragweed will be able to respond quickly to selection pressures in both its native and introduced ranges.

Population Divergence along a Genetic Line of Least Resistance in the Tree Species Eucalyptus globulus

The evolutionary response to selection depends on the distribution of genetic variation in traits under selection within populations, as defined by the additive genetic variance-covariance matrix (G). The structure and evolutionary stability of G will thus influence the course of phenotypic evolution. However, there are few studies assessing the stability of G and its relationship with population divergence within foundation tree species. We compared the G-matrices of Mainland and Island population groups of the forest tree Eucalyptus globulus, and determined the extent to which population divergence aligned with within-population genetic (co)variation. Four key wood property traits exhibiting signals of divergent selection were studied—wood density, extractive content, and lignin content and composition. The comparison of G-matrices of the mainland and island populations indicated that the G-eigenstructure was relatively well preserved at an intra-specific level. Population divergence tended to occur along a major direction of genetic variation in G. The observed conservatism of G, the moderate evolutionary timescale, and close relationship between genetic architecture and population trajectories suggest that genetic constraints may have influenced the evolution and diversification of the E. globulus populations for the traits studied. However, alternative scenarios, including selection aligning genetic architecture and population divergence, are discussed.

Demographic history and genomics of local adaptation in blue tit populations

Understanding the genomic processes underlying local adaptation is a central aim of modern evolutionary biology. This task requires identifying footprints of local selection but also estimating spatio‐temporal variations in population demography and variations in recombination rate and in diversity along the genome. Here, we investigated these parameters in blue tit populations inhabiting deciduous versus evergreen forests, and insular versus mainland areas, in the context of a previously described strong phenotypic differentiation. Neighboring population pairs of deciduous and evergreen habitats were weakly genetically differentiated (F_ST = 0.003 on average), nevertheless with a statistically significant effect of habitat type on the overall genetic structure. This low differentiation was consistent with the strong and long‐lasting gene flow between populations inferred by demographic modeling. In turn, insular and mainland populations were moderately differentiated (F_ST = 0.08 on average), in line with the inference of moderate ancestral migration, followed by isolation since the end of the last glaciation. Effective population sizes were large, yet smaller on the island than on the mainland. Weak and nonparallel footprints of divergent selection between deciduous and evergreen populations were consistent with their high connectivity and the probable polygenic nature of local adaptation in these habitats. In turn, stronger footprints of divergent selection were identified between long isolated insular versus mainland birds and were more often found in regions of low recombination, as expected from theory. Lastly, we identified a genomic inversion on the mainland, spanning 2.8 Mb. These results provide insights into the demographic history and genetic architecture of local adaptation in blue tit populations at multiple geographic scales.

Natural and human-induced environmental changes and their effects on adaptive potential of wild animal populations

A major challenge of evolutionary ecology over the next decades is to understand and predict the consequences of the current rapid and important environmental changes on wild populations. Extinction risk of species is linked to populations' evolutionary potential and to their ability to express adaptive phenotypic plasticity. There is thus a vital need to quantify how selective pressures, quantitative genetics parameters, and phenotypic plasticity, for multiple traits in wild animal populations, may vary with changes in the environment. Here I review our previous research that integrated ecological and evolutionary theories with molecular ecology, quantitative genetics, and long-term monitoring of individually marked wild animals. Our results showed that assessing evolutionary and plastic changes over time and space, using multi-trait approaches, under a realistic range of environmental conditions are crucial steps toward improving our understanding of the evolution and adaptation of natural populations. Our current and future work focusses on assessing the limits of adaptive potential by determining the factors constraining the evolvability of plasticity, those generating covariation among genetic variance and selection, as well as indirect genetic effects, which can affect population's capacity to adjust to environmental changes. In doing so, we aim to provide an improved assessment of the spatial and temporal scale of evolutionary processes in wild animal populations.

Comparative analysis of the multivariate genetic architecture of morphological traits in three species of Gomphocerine grasshoppers

Evolutionary change is the change in trait values across generations, and usually occurs in multidimensional trait space rather than along isolated traits. Genetic covariation influences the magnitude and direction of evolutionary change and can be statistically summarized by the additive genetic (co)variance matrix, G. While G can affect the response to selection, it is exposed to evolutionary change by selection and genetic drift, but the magnitude and speed of these changes are poorly understood. We use comparative G matrix analyses to assess evolution of the shape and orientation of G over longer timescales in three species of Gomphocerine grasshoppers. We estimate 10 × 10 G matrices for five morphological traits expressed in both sexes. We find low-to-moderate heritabilities (average 0.36), mostly large cross-sex correlations (average 0.54) and moderate between-trait correlations (average 0.34). G matrices differ significantly among species with wing length contributing most to these differences. Wing length is the trait that is most divergent among species, suggesting it has been under selection during species divergence. The more distantly related species, Pseudochorthippus parallelus, was the most different in the shape of G. Projection of contemporary genetic variation into the divergence space D illustrates that the major axis of genetic variation in Gomphocerippus rufus is aligned with divergence from Chorthippus biguttulus, while the major axis of genetic variation in neither of the species is aligned with the divergence between Pseudochorthippus parallelus and the other two species. Our results demonstrate significant differences in G matrices with a phylogenetic signal in the differentiation.

Adaptation to local climate in multi-trait space: evidence from silver fir (Abies alba Mill.) populations across a heterogeneous environment

Heterogeneous environments, such as mountainous landscapes, create spatially varying selection pressure that potentially affects several traits simultaneously across different life stages, yet little is known about the general patterns and drivers of adaptation in such complex settings. We studied silver fir (Abies alba Mill.) populations across Switzerland and characterized its mountainous landscape using downscaled historical climate data. We sampled 387 trees from 19 populations and genotyped them at 374 single-nucleotide polymorphisms (SNPs) to estimate their demographic distances. Seedling morphology, growth and phenology traits were recorded in a common garden, and a proxy for water use efficiency was estimated for adult trees. We tested whether populations have more strongly diverged at quantitative traits than expected based on genetic drift alone in a multi-trait framework, and identified potential environmental drivers of selection. We found two main responses to selection: (i) populations from warmer and more thermally stable locations have evolved towards a taller stature, and (ii) the growth timing of populations evolved towards two extreme strategies, 'start early and grow slowly' or 'start late and grow fast', driven by precipitation seasonality. Populations following the 'start early and grow slowly' strategy had higher water use efficiency and came from inner Alpine valleys characterized by pronounced summer droughts. Our results suggest that contrasting adaptive life-history strategies exist in silver fir across different life stages (seedling to adult), and that some of the characterized populations may provide suitable seed sources for tree growth under future climatic conditions.

Antagonistic selection and pleiotropy constrain the evolution of plant chemical defenses

When pleiotropy is present, genetic correlations may constrain the evolution of ecologically important traits. We used a quantitative genetics approach to investigate constraints on the evolution of secondary metabolites in a wild mustard, Boechera stricta. Much of the genetic variation in chemical composition of glucosinolates in B. stricta is controlled by a single locus, BCMA1/3. In a large-scale common garden experiment under natural conditions, we quantified fitness and glucosinolate profile in two leaf types and in fruits. We estimated genetic variances and covariances (the G-matrix) and selection on chemical profile in each tissue. Chemical composition of defenses was strongly genetically correlated between tissues. We found antagonistic selection between defense composition in leaves and fruits: compounds that were favored in leaves were disadvantageous in fruits. The positive genetic correlations and antagonistic selection led to strong constraints on the evolution of defenses in leaves and fruits. In a hypothetical population with no genetic variation at BCMA1/3, we found no evidence for genetic constraints, indicating that pleiotropy affecting chemical profile in multiple tissues drives constraints on the evolution of secondary metabolites.

A Practical Guide to the Study of Distribution Limits

Factors that limit the geographic distribution of species are broadly important in ecology and evolutionary biology, and understanding distribution limits is imperative for predicting how species will respond to environmental change. Good data indicate that factors such as dispersal limitation, small effective population size, and isolation are sometimes important. But empirical research highlights no single factor that explains the ubiquity of distribution limits. In this article, we outline a guide to tackling distribution limits that integrates established causes, such as dispersal limitation and spatial environmental heterogeneity, with understudied causes, such as mutational load and genetic or developmental integration of traits limiting niche expansion. We highlight how modeling and quantitative genetic and genomic analyses can provide insight into sources of distribution limits. Our practical guide provides a framework for considering the many factors likely to determine species distributions and how the different approaches can be integrated to predict distribution limits using eco-evolutionary modeling. The framework should also help predict distribution limits of invasive species and of species under climate change.

Development of G: a test in an amphibious fish

Heritable variation in, and genetic correlations among, traits determine the response of multivariate phenotypes to natural selection. However, as traits develop over ontogeny, patterns of genetic (co)variation and integration captured by the G matrix may also change. Despite this, few studies have investigated how genetic parameters underpinning multivariate phenotypes change as animals pass through major life history stages. Here, using a self-fertilizing hermaphroditic fish species, mangrove rivulus (Kryptolebias marmoratus), we test the hypothesis that G changes from hatching through reproductive maturation. We also test Cheverud's conjecture by asking whether phenotypic patterns provide an acceptable surrogate for patterns of genetic (co)variation within and across ontogenetic stages. For a set of morphological traits linked to locomotor (jumping) performance, we find that the overall level of genetic integration (as measured by the mean-squared correlation across all traits) does not change significantly over ontogeny. However, we also find evidence that some trait-specific genetic variances and pairwise genetic correlations do change. Ontogenetic changes in G indicate the presence of genetic variance for developmental processes themselves, while also suggesting that any genetic constraints on morphological evolution may be age-dependent. Phenotypic correlations closely resembled genetic correlations at each stage in ontogeny. Thus, our results are consistent with the premise that-at least under common environment conditions-phenotypic correlations can be a good substitute for genetic correlations in studies of multivariate developmental evolution.

Environmental coupling of heritability and selection is rare and of minor evolutionary significance in wild populations

Predicting the rate of adaptation to environmental change in wild populations is important for understanding evolutionary change. However, predictions may be unreliable if the two key variables affecting the rate of evolutionary change-heritability and selection-are both affected by the same environmental variable. To determine how general such an environmentally induced coupling of heritability and selection is, and how this may influence the rate of adaptation, we made use of freely accessible, open data on pedigreed wild populations to answer this question at the broadest possible scale. Using 16 populations from 10 vertebrate species, which provided data on 50 traits (relating to body mass, morphology, physiology, behaviour and life history), we found evidence for an environmentally induced relationship between heritability and selection in only 6 cases, with weak evidence that this resulted in an increase or decrease in the expected selection response. We conclude that such a coupling of heritability and selection is unlikely to strongly affect evolutionary change, even though both heritability and selection are commonly postulated to be dependent on the environment.

The genetic variance but not the genetic covariance of life-history traits changes towards the north in a time-constrained insect

Seasonal time constraints are usually stronger at higher than lower latitudes and can exert strong selection on life-history traits and the correlations among these traits. To predict the response of life-history traits to environmental change along a latitudinal gradient, information must be obtained about genetic variance in traits and also genetic correlation between traits, that is the genetic variance-covariance matrix, G. Here, we estimated G for key life-history traits in an obligate univoltine damselfly that faces seasonal time constraints. We exposed populations to simulated native temperatures and photoperiods and common garden environmental conditions in a laboratory set-up. Despite differences in genetic variance in these traits between populations (lower variance at northern latitudes), there was no evidence for latitude-specific covariance of the life-history traits. At simulated native conditions, all populations showed strong genetic and phenotypic correlations between traits that shaped growth and development. The variance-covariance matrix changed considerably when populations were exposed to common garden conditions compared with the simulated natural conditions, showing the importance of environmentally induced changes in multivariate genetic structure. Our results highlight the importance of estimating variance-covariance matrixes in environments that mimic selection pressures and not only trait variances or mean trait values in common garden conditions for understanding the trait evolution across populations and environments.

Evolution of sex-specific pace-of-life syndromes: genetic architecture and physiological mechanisms

Sex differences in life history, physiology, and behavior are nearly ubiquitous across taxa, owing to sex-specific selection that arises from different reproductive strategies of the sexes. The pace-of-life syndrome (POLS) hypothesis predicts that most variation in such traits among individuals, populations, and species falls along a slow-fast pace-of-life continuum. As a result of their different reproductive roles and environment, the sexes also commonly differ in pace-of-life, with important consequences for the evolution of POLS. Here, we outline mechanisms for how males and females can evolve differences in POLS traits and in how such traits can covary differently despite constraints resulting from a shared genome. We review the current knowledge of the genetic basis of POLS traits and suggest candidate genes and pathways for future studies. Pleiotropic effects may govern many of the genetic correlations, but little is still known about the mechanisms involved in trade-offs between current and future reproduction and their integration with behavioral variation. We highlight the importance of metabolic and hormonal pathways in mediating sex differences in POLS traits; however, there is still a shortage of studies that test for sex specificity in molecular effects and their evolutionary causes. Considering whether and how sexual dimorphism evolves in POLS traits provides a more holistic framework to understand how behavioral variation is integrated with life histories and physiology, and we call for studies that focus on examining the sex-specific genetic architecture of this integration.

Current spring warming as a driver of selection on reproductive timing in a wild passerine

Evolutionary adaptation as a response to climate change is expected for fitness-related traits affected by climate and exhibiting genetic variance. Although the relationship between warmer spring temperature and earlier timing of reproduction is well documented, quantifications and predictions of the impact of global warming on natural selection acting on phenology in wild populations remain rare. If global warming affects fitness in a similar way across individuals within a population, or if fitness consequences are independent of phenotypic variation in key-adaptive traits, then no evolutionary response is expected for these traits. Here, we quantified the selection pressures acting on laying date during a 24-year monitoring of blue tits in southern Mediterranean France, a hot spot of climate warming. We explored the temporal fluctuation in annual selection gradients and we determined its temperature-related drivers. We first investigated the month-specific warming since 1970 in our study site and tested its influence on selection pressures, using a model averaging approach. Then, we quantified the selection strength associated with temperature anomalies experienced by the blue tit population. We found that natural selection acting on laying date significantly fluctuated both in magnitude and in sign across years. After identifying a significant warming in spring and summer, we showed that warmer daily maximum temperatures in April were significantly associated with stronger selection pressures for reproductive timing. Our results indicated an increase in the strength of selection by 46% for every +1°C anomaly. Our results confirm the general assumption that recent climate change translates into strong selection favouring earlier breeders in passerine birds. Our findings also suggest that differences in fitness among individuals varying in their breeding phenology increase with climate warming. Such climate-driven influence on the strength of directional selection acting on laying date could favour an adaptive response in this trait, since it is heritable.

Evidence for Selection-by-Environment but Not Genotype-by-Environment Interactions for Fitness-Related Traits in a Wild Mammal Population

How do environmental conditions influence selection and genetic variation in wild populations? There is widespread evidence for selection-by-environment interactions (S*E), but we reviewed studies of natural populations estimating the extent of genotype-by-environment interactions (G*E) in response to natural variation in environmental conditions and found that evidence for G*E appears to be rare within single populations in the wild. Studies estimating the simultaneous impact of environmental variation on both selection and genetic variation are especially scarce. Here, we used 24 years of data collected from a wild Soay sheep population to quantify how an important environmental variable, population density, impacts upon (1) selection through annual contribution to fitness and (2) expression of genetic variation, in six morphological and life history traits: body weight, hind leg length, parasite burden, horn length, horn growth, and testicular circumference. Our results supported the existence of S*E: selection was stronger in years of higher population density for all traits apart from horn growth, with directional selection being stronger under more adverse conditions. Quantitative genetic models revealed significant additive genetic variance for body weight, leg length, parasite burden, horn length, and testes size, but not for horn growth or our measure of annual fitness. However, random regression models found variation between individuals in their responses to the environment in only three traits, and did not support the presence of G*E for any trait. Our analyses of St Kilda Soay sheep data thus concurs with our cross-study review that, while natural environmental variation within a population can profoundly alter the strength of selection on phenotypic traits, there is less evidence for its effect on the expression of genetic variance in the wild.