Geographic variation in the G matrices of wild populations of the barn swallow

Divergence in evolutionary potential of life history traits among wild populations is predicted by differences in climatic conditions

Short-term adaptive evolution represents one of the primary mechanisms allowing species to persist in the face of global change. Predicting the adaptive response at the species level requires reliable estimates of the evolutionary potential of traits involved in adaptive responses, as well as understanding how evolutionary potential varies across a species' range. Theory suggests that spatial variation in the fitness landscape due to environmental variation will directly impact the evolutionary potential of traits. However, empirical evidence on the link between environmental variation and evolutionary potential across a species range in the wild is lacking. In this study, we estimate multivariate evolutionary potential (via the genetic variance-covariance matrix, or G-matrix) for six morphological and life history traits in 10 wild populations of great tits (Parus major) distributed across Europe. The G-matrix significantly varies in size, shape, and orientation across populations for both types of traits. For life history traits, the differences in G-matrix are larger when populations are more distant in their climatic niche. This suggests that local climates contribute to shaping the evolutionary potential of phenotypic traits that are strongly related to fitness. However, we found no difference in the overall evolutionary potential (i.e., G-matrix size) between populations closer to the core or the edge of the distribution area. This large-scale comparison of G-matrices across wild populations emphasizes that integrating variation in multivariate evolutionary potential is important to understand and predict species' adaptive responses to new selective pressures.

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.

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

The genetic variance-covariance matrix (G-matrix) summarizes the genetic architecture of multiple traits. It has a central role in the understanding of phenotypic divergence and the quantification of the evolutionary potential of populations. Laboratory experiments have shown that G-matrices can vary rapidly under divergent selective pressures. However, because of the demanding nature of G-matrix estimation and comparison in wild populations, the extent of its spatial variability remains largely unknown. In this study, we investigate spatial variation in G-matrices for morphological and life-history traits using long-term data sets from one continental and three island populations of blue tit (Cyanistes caeruleus) that have experienced contrasting population history and selective environment. We found no evidence for differences in G-matrices among populations. Interestingly, the phenotypic variance-covariance matrices (P) were divergent across populations, suggesting that using P as a substitute for G may be inadequate. These analyses also provide the first evidence in wild populations for additive genetic variation in the incubation period (that is, the period between last egg laid and hatching) in all four populations. Altogether, our results suggest that G-matrices may be stable across populations inhabiting contrasted environments, therefore challenging the results of previous simulation studies and laboratory experiments.

Similarity in G matrix structure among natural populations of Arabidopsis lyrata

Understanding the stability of the G matrix in natural populations is fundamental for predicting evolutionary trajectories; yet, the extent of its spatial variation and how this impacts responses to selection remain open questions. With a nested paternal half-sib crossing design and plants grown in a field experiment, we examined differences in the genetic architecture of flowering time, floral display, and plant size among four Scandinavian populations of Arabidopsis lyrata. Using a multivariate Bayesian framework, we compared the size, shape, and orientation of G matrices and assessed their potential to facilitate or constrain trait evolution. Flowering time, floral display and rosette size varied among populations and significant additive genetic variation within populations indicated potential to evolve in response to selection. Yet, some characters, including flowering start and number of flowers, may not evolve independently because of genetic correlations. Using a multivariate framework, we found few differences in the genetic architecture of traits among populations. G matrices varied mostly in size rather than shape or orientation. Differences in multivariate responses to selection predicted from differences in G were small, suggesting overall matrix similarity and shared constraints to trait evolution among populations.

Are heritability and selection related to population size in nature? Meta-analysis and conservation implications

It is widely thought that small populations should have less additive genetic variance and respond less efficiently to natural selection than large populations. Across taxa, we meta-analytically quantified the relationship between adult census population size (N) and additive genetic variance (proxy: h (2)) and found no reduction in h (2) with decreasing N; surveyed populations ranged from four to one million individuals (1735 h (2) estimates, 146 populations, 83 species). In terms of adaptation, ecological conditions may systematically differ between populations of varying N; the magnitude of selection these populations experience may therefore also differ. We thus also meta-analytically tested whether selection changes with N and found little evidence for systematic differences in the strength, direction or form of selection with N across different trait types and taxa (7344 selection estimates, 172 populations, 80 species). Collectively, our results (i) indirectly suggest that genetic drift neither overwhelms selection more in small than in large natural populations, nor weakens adaptive potential/h (2) in small populations, and (ii) imply that natural populations of varying sizes experience a variety of environmental conditions, without consistently differing habitat quality at small N. However, we caution that the data are currently insufficient to determine whether some small populations may retain adaptive potential definitively. Further study is required into (i) selection and genetic variation in completely isolated populations of known N, under-represented taxonomic groups, and nongeneralist species, (ii) adaptive potential using multidimensional approaches and (iii) the nature of selective pressures for specific traits.

Large-scale patterns of genetic variation in a female-biased dispersing passerine: the importance of sex-based analyses

Dispersal affects the distribution, dynamics and genetic structure of natural populations, and can be significantly different between sexes. However, literature records dealing with the dispersal of migratory birds are scarce, as migratory behaviour can notably complicate the study of dispersal. We used the barn swallow Hirundo rustica as model taxon to investigate patterns of genetic variability in males and in females of a migratory species showing sex-biased dispersal. We collected blood samples (n = 186) over the period 2006 to 2011 from adults (H. r. rustica subspecies) nesting in the same breeding site at either high (Ireland, Germany and Russia) or low (Spain, Italy and Cyprus) latitude across Europe. We amplified the Chromo Helicase DNA gene in all birds in order to warrant a sex-balanced sample size (92 males, 94 females). We investigated both uniparental (mitochondrial ND2 gene) and biparental (microsatellite DNA: 10 loci) genetic systems. The mtDNA provided evidence for demographic expansion yet no significant partition of the genetic variability was disclosed. Nevertheless, a comparatively distant Russian population investigated in another study, whose sequences were included in the present dataset, significantly diverged from all other ones. Different to previous studies, microsatellites highlighted remarkable genetic structure among the studied populations, and pointed to the occurrence of differences between male and female barn swallows. We produced evidence for non-random patterns of gene flow among barn swallow populations probably mediated by female natal dispersal, and we found significant variability in the philopatry of males of different populations. Our data emphasize the importance of taking into account the sex of sampled individuals in order to obtain reliable inferences on species characterized by different patterns of dispersal between males and females.

Can invasions occur without change? A comparison of G-matrices and selection in the peach-potato aphid, Myzus persicae

Most evolutionary research on biological invasions has focused on changes seen between the native and invaded range for a particular species. However, it is likely that species that live in human-modified habitats in their native range might have evolved specific adaptations to those environments, which increase the likelihood of establishment and spread in similar human-altered environments. From a quantitative genetic perspective, this hypothesis suggests that both native and introduced populations should reside at or near the same adaptive peak. Therefore, we should observe no overall changes in the G (genetic variance-covariance) matrices between native and introduced ranges, and stabilizing selection on fitness-related traits in all populations. We tested these predictions comparing three populations of the worldwide pest Myzus persicae from the Middle East (native range) and the UK and Chile (separately introduced ranges). In general, our results provide mixed support for this idea, but further comparisons of other species are needed. In particular, we found that there has been some limited evolution in the studied traits, with the Middle East population differing from the UK and Chilean populations. This was reflected in the structure of the G-matrices, in which Chile differed from both UK and Middle East populations. Furthermore, the amount of genetic variation was massively reduced in Chile in comparison with UK and Middle East populations. Finally, we found no detectable selection on any trait in the three populations, but clones from the introduced ranges started to reproduce later, were smaller, had smaller offspring, and had lower reproductive fitness than clones from the native range.

Trade-offs, geography, and limits to thermal adaptation in a tide pool copepod

Antagonistic correlations among traits may slow the rate of adaptation to a changing environment. The tide pool copepod Tigriopus californicus is locally adapted to temperature, but within populations, the response to selection for increased heat tolerance plateaus rapidly, suggesting either limited variation within populations or costs of increased tolerance. To measure possible costs of thermal tolerance, we selected for increased upper lethal limits for 10 generations in 22 lines of T. californicus from six populations. Then, for each line, we measured six fitness-related traits. Selected lines showed an overall increase in male and female body sizes, fecundity, and starvation resistance, suggesting a small benefit from (rather than costs of) increased tolerance. The effect of selection on correlated traits also varied significantly by population for five traits, indicating that the genetic basis for the selection response differed among populations. Our results suggest that adaptation was limited by the presence of variation within isolated populations rather than by costs of increased tolerance.

Limited plasticity in the phenotypic variance-covariance matrix for male advertisement calls in the black field cricket, Teleogryllus commodus

Phenotypic integration and plasticity are central to our understanding of how complex phenotypic traits evolve. Evolutionary change in complex quantitative traits can be predicted using the multivariate breeders' equation, but such predictions are only accurate if the matrices involved are stable over evolutionary time. Recent study, however, suggests that these matrices are temporally plastic, spatially variable and themselves evolvable. The data available on phenotypic variance-covariance matrix (P) stability are sparse, and largely focused on morphological traits. Here, we compared P for the structure of the complex sexual advertisement call of six divergent allopatric populations of the Australian black field cricket, Teleogryllus commodus. We measured a subset of calls from wild-caught crickets from each of the populations and then a second subset after rearing crickets under common-garden conditions for three generations. In a second experiment, crickets from each population were reared in the laboratory on high- and low-nutrient diets and their calls recorded. In both experiments, we estimated P for call traits and used multiple methods to compare them statistically (Flury hierarchy, geometric subspace comparisons and random skewers). Despite considerable variation in means and variances of individual call traits, the structure of P was largely conserved among populations, across generations and between our rearing diets. Our finding that P remains largely stable, among populations and between environmental conditions, suggests that selection has preserved the structure of call traits in order that they can function as an integrated unit.

Quantitative genetics of migration syndromes: a study of two barn swallow populations

Migration is a complex trait although little is known about genetic correlations between traits involved in such migration syndromes. To assess the migratory responses to climate change, we need information on genetic constraints on evolutionary potential of arrival dates in migratory birds. Using two long-term data sets on barn swallows Hirundo rustica (from Spain and Denmark), we show for the first time in wild populations that spring arrival dates are phenotypically and genetically correlated with morphological and life history traits. In the Danish population, length of outermost tail feathers and wing length were negatively genetically correlated with arrival date. In the Spanish population, we found a negative genetic correlation between arrival date and time elapsed between arrival date and laying date, constraining response to selection that favours both early arrival and shorter delays. This results in a decreased rate of adaptation, not because of constraints on arrival date, but constraints on delay before breeding, that is, a trait that can be equally important in the context of climate change.

Understanding the evolution and stability of the G-matrix

The G-matrix summarizes the inheritance of multiple, phenotypic traits. The stability and evolution of this matrix are important issues because they affect our ability to predict how the phenotypic traits evolve by selection and drift. Despite the centrality of these issues, comparative, experimental, and analytical approaches to understanding the stability and evolution of the G-matrix have met with limited success. Nevertheless, empirical studies often find that certain structural features of the matrix are remarkably constant, suggesting that persistent selection regimes or other factors promote stability. On the theoretical side, no one has been able to derive equations that would relate stability of the G-matrix to selection regimes, population size, migration, or to the details of genetic architecture. Recent simulation studies of evolving G-matrices offer solutions to some of these problems, as well as a deeper, synthetic understanding of both the G-matrix and adaptive radiations.

A quantitative measure of migratory connectivity

The study of the extent of the connection between areas where populations of birds breed and areas where they winter has flourished in recent years mainly thanks to the development of new techniques, but also due to traditional ringing and recovery schemes, which allow tracking of individuals or populations linking wintering and breeding distributions. Currently, studies on migratory connectivity focus on retention of breeding population spatial structure on the non-breeding grounds and vice versa. Here we propose a method to quantify migratory connectivity based on Mantel correlation coefficients and to statistically test for deviations of the observed connectivity from a random mix of individuals. In addition, we propose a procedure, based on clustering algorithms, to identify whether observed connectivity depends on aggregation of individuals or on rigid transference of distribution patterns between areas. We applied this method to a large dataset of ringing recoveries of barn swallows (Hirundo rustica L) migrating from their Western Palearctic breeding areas to sub-Saharan winter quarters. We show that migration of barn swallow populations connects specific breeding and wintering areas, and that the "sub-populations" quantitatively identified by our method are consistent with qualitative patterns of migratory connectivity identified by studies of individual geographical populations based on other methods. Finally, we tested the performance of the method by running simulations under different scenarios. Such simulations showed that the method is robust and able to correctly detect migratory connectivity even with smaller datasets and when a strong geographical pattern is not present in the population. Our method provides a quantitative measure of migratory connectivity and allows for the identification of populations showing high connectivity between the breeding and wintering areas. This method is suitable for a generalized application to diverse animal taxa as well as to large scale analyses of connectivity for conservation purposes.

Strong artificial selection in the wild results in predicted small evolutionary change

Estimates of genetic variation and selection allow for quantitative predictions of evolutionary change, at least in controlled laboratory experiments. Natural populations are, however, different in many ways, and natural selection on heritable traits does not always result in phenotypic change. To test whether we were able to predict the evolutionary dynamics of a complex trait measured in a natural, heterogeneous environment, we performed, over an 8-year period, a two-way selection experiment on clutch size in a subdivided island population of great tits (Parus major). Despite strong artificial selection, there was no clear evidence for evolutionary change at the phenotypic level. Environmentally induced differences in clutch size among years are, however, large and can mask evolutionary changes. Indeed, genetic changes in clutch size, inferred from a statistical model, did not deviate systematically from those predicted. Although this shows that estimates of genetic variation and selection can indeed provide quantitative predictions of evolutionary change, also in the wild, it also emphasizes that demonstrating evolution in wild populations is difficult, and that the interpretation of phenotypic trends requires great care.

A CENTENNIAL CELEBRATION FOR QUANTITATIVE GENETICS

Quantitative genetics is at or is fast approaching its centennial. In this perspective I consider five current issues pertinent to the application of quantitative genetics to evolutionary theory. First, I discuss the utility of a quantitative genetic perspective in describing genetic variation at two very different levels of resolution, (1) in natural, free-ranging populations and (2) to describe variation at the level of DNA transcription. Whereas quantitative genetics can serve as a very useful descriptor of genetic variation, its greater usefulness is in predicting evolutionary change, particularly when used in the first instance (wild populations). Second, I review the contributions of Quantitative trait loci (QLT) analysis in determining the number of loci and distribution of their genetic effects, the possible importance of identifying specific genes, and the ability of the multivariate breeder's equation to predict the results of bivariate selection experiments. QLT analyses appear to indicate that genetic effects are skewed, that at least 20 loci are generally involved, with an unknown number of alleles, and that a few loci have major effects. However, epistatic effects are common, which means that such loci might not have population-wide major effects: this question waits upon (QTL) analyses conducted on more than a few inbred lines. Third, I examine the importance of research into the action of specific genes on traits. Although great progress has been made in identifying specific genes contributing to trait variation, the high level of gene interactions underlying quantitative traits makes it unlikely that in the near future we will have mechanistic models for such traits, or that these would have greater predictive power than quantitative genetic models. In the fourth section I present evidence that the results of bivariate selection experiments when selection is antagonistic to the genetic covariance are frequently not well predicted by the multivariate breeder's equation. Bivariate experiments that combine both selection and functional analyses are urgently needed. Finally, I discuss the importance of gaining more insight, both theoretical and empirical, on the evolution of the G and P matrices.

Testing the phenotypic gambit: phenotypic, genetic and environmental correlations of colour

Evolutionary theory is primarily concerned with genetic processes, yet empirical testing of this theory often involves data collected on phenotypes. To make this tenable, the implicit assumption is often made that phenotypic patterns are good predictors of genetic patterns; an assumption that coined the phenotypic gambit. Although this assumption has been validated for traits with high heritability, such as morphology, its generality for traits with low heritabilities, such as life-history and behavioural traits, remains controversial. Using a large-scale cross-fostering experiment, we were able to measure genetic, common environmental and phenotypic correlations between four colour traits and two skeletal traits in a wild population of passerine birds, the blue tit (Parus caeruleus). Colour traits had little heritable variation but common environment effects were found to be important; skeletal traits showed the opposite pattern. Positive correlations because of a shared natal environment were found between all traits, obscuring negative genetic correlations between some colour and skeletal traits. Consequently, phenotypic patterns were poor surrogates for genetic patterns and we suggest that this may be common if trade-offs or substantial parental effects exist. For this group of traits, the phenotypic gambit cannot be made and we suggest caution when inferring genetic patterns from phenotypic data, especially for behavioural and life-history traits.

Environmental quality and evolutionary potential: lessons from wild populations

An essential requirement to determine a population's potential for evolutionary change is to quantify the amount of genetic variability expressed for traits under selection. Early investigations in laboratory conditions showed that the magnitude of the genetic and environmental components of phenotypic variation can change with environmental conditions. However, there is no consensus as to how the expression of genetic variation is sensitive to different environmental conditions. Recently, the study of quantitative genetics in the wild has been revitalized by new pedigree analyses based on restricted maximum likelihood, resulting in a number of studies investigating these questions in wild populations. Experimental manipulation of environmental quality in the wild, as well as the use of naturally occurring favourable or stressful environments, has broadened the treatment of different taxa and traits. Here, we conduct a meta-analysis on recent studies comparing heritability in favourable versus unfavourable conditions in non-domestic and non-laboratory animals. The results provide evidence for increased heritability in more favourable conditions, significantly so for morphometric traits but not for traits more closely related to fitness. We discuss how these results are explained by underlying changes in variance components, and how they represent a major step in our understanding of evolutionary processes in wild populations. We also show how these trends contrast with the prevailing view resulting mainly from laboratory experiments on Drosophila. Finally, we underline the importance of taking into account the environmental variation in models predicting quantitative trait evolution.