Explore the vast range of titles available.

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.

Metamorphosis is common in animals, yet the genetic associations between life cycle stages are poorly understood. Given the radical changes that occur at metamorphosis, selection may differ before and after metamorphosis, and the extent that genetic associations between pre- and post-metamorphic traits constrain evolutionary change is a subject of considerable interest. In some instances, metamorphosis may allow the genetic decoupling of life cycle stages, whereas in others, metamorphosis could allow complementary responses to selection across the life cycle. Using a diallel breeding design, we measured viability at four ontogenetic stages (embryo, larval, juvenile and adult viability), in the ascidian Ciona intestinalis and examined the orientation of additive genetic variation with respect to the metamorphic boundary. We found support for one eigenvector of G (gobsmax), which contrasted larval viability against embryo viability and juvenile viability. Target matrix rotation confirmed that while gobsmax shows genetic associations can extend beyond metamorphosis, there is still considerable scope for decoupled phenotypic evolution. Therefore, although genetic associations across metamorphosis could limit that range of phenotypes that are attainable, traits on either side of the metamorphic boundary are capable of some independent evolutionary change in response to the divergent conditions encountered during each life cycle stage.

Theoretical quantitative genetics provides a framework for reconstructing past selection and predicting future patterns of phenotypic differentiation. However, the usefulness of the equations of quantitative genetics for evolutionary inference relies on the evolutionary stability of the additive genetic variance–covariance matrix (G matrix). A fruitful new approach for exploring the evolutionary dynamics of G involves the use of individual-based computer simulations. Previous studies have focused on the evolution of the eigenstructure of G. An alternative approach employed in this paper uses the multivariate response-to-selection equation to evaluate the stability of G. In this approach, I measure similarity by the correlation between response-to-selection vectors due to random selection gradients. I analyze the dynamics of G under several conditions of correlational mutation and selection. As found in a previous study, the eigenstructure of G is stabilized by correlational mutation and selection. However, over broad conditions, instability of G did not result in a decreased consistency of the response to selection. I also analyze the stability of G when the correlation coefficients of correlational mutation and selection and the effective population size change through time. To my knowledge, no prior study has used computer simulations to investigate the stability of G when correlational mutation and selection fluctuate. Under these conditions, the eigenstructure of G is unstable under some simulation conditions. Different results are obtained if G matrix stability is assessed by eigenanalysis or by the response to random selection gradients. In this case, the response to selection is most consistent when certain aspects of the eigenstructure of G are least stable and vice versa.

Evolutionary theory predicts that interactions between species such as resource competition or reproductive interference will generate selection for character displacement where similar species co-occur. However, the rate and direction of character displacement will depend not only on the strength of selection for trait divergence, but also on the amount of genetic variation for selected traits and the nature of genetic correlations between them. To assess the importance of genetic constraints for the evolution of character displacement, we examined the genetic architecture of a suite of floral traits previously shown to be under selection in the annual plant Ipomoea hederacea when this species co-occurs with Ipomoea purpurea. We found that the six floral traits we measured are all positively genetically correlated. We also demonstrate, using new statistical approaches, that the predicted response to selection for four of these six traits is substantially constrained by their genetic correlation structure. Most notably, the response to selection for reduced separation of the tallest and shortest anthers, which reduces the degree of detrimental heterospecific pollen flow, is substantially constrained. Our results suggest that the rate of evolution of reproductive character displacement in I. hederacea is limited by the genetic architecture of floral traits.

Measurements of the genetic variation and covariation underlying quantitative traits are crucial to our understanding of current evolutionary change and the mechanisms causing this evolution. This fact has spurred a large number of studies estimating heritabilities and genetic correlations in a variety of organisms. Most of these studies have been done in laboratory or greenhouse settings, but it is not well known how accurately these measurements estimate genetic variance and covariance expressed in the field. We conducted a quantitative genetic half‐sibling analysis on six floral traits in wild radish. Plants were grown from seed in the field and were exposed to natural environmental variation throughout their lives, including herbivory and intra‐ and interspecific competition. The estimates of heritabilities and the additive genetic variance‐covariance matrix (G) obtained from this analysis were then compared to previous greenhouse estimates of the same floral traits from the same natural population. Heritabilities were much lower in the field for all traits, and this was due to both large increases in environmental variance and decreases in additive genetic variance. Additive genetic covariance expressed was also much lower in the field. These differences resulted in highly significant differences in the G matrix between the greenhouse and field environments using two complementary testing methods. Although the G matrices shared some principal components in common, they were not simply proportional to each other. Therefore, the greenhouse results did not accurately depict how the floral traits would respond to natural selection in the field.

Genetic correlations between parasite resistance and other traits can act as an evolutionary constraint and prevent a population from evolving increased resistance. For example, previous studies have found negative genetic correlations between host resistance and life-history traits. In invertebrates, the level of resistance often depends on the combination of the host and parasite genotypes, and in this study, we have investigated whether such specific resistance also acts as an evolutionary constraint. We measured the resistance of different genotypes of the fruit fly Drosophila melanogaster to different genotypes of a naturally occurring pathogen, the sigma virus. Using a multitrait analysis, we examine whether genetic covariances alter the potential to select for general resistance against all of the different viral genotypes. We found large amounts of heritable variation in resistance, and evidence for specific interactions between host and parasite, but these interactions resulted in little constraint on Drosophila evolving greater resistance.

The constancy of the genetic variance‐covariance matrix (G matrix) across environments and populations has been discussed and tested empirically over the years but no consensus has so far been reached. In this paper, I present a model in which morphological traits develop hierarchically, and individuals differ in their resource allocation and acquisition patterns. If the variance in resource acquisition is many times larger than the variance in resource allocation then strong genetic correlations are expected, and with almost isometric relations among traits. As the variation in resource acquisition decreases below a certain threshold, the correlations decrease overall and the relations among traits become a function of the allocation patterns, and in particular reflecting the basal division of allocation. A strong bottleneck can break a pattern of strong genetic correlation, but this effect diminishes rapidly with increasing bottleneck size. This model helps to understand why some populations change their genetic correlations in different environments, whereas others do not, since the key factor is the relation between the variances in resource acquisition and allocation. If a change in environment does not lead to a change in this ratio, no change can be expected, whereas if the ratio is changed substantially then major changes can be expected. This model can also help to understand the constancy of morphological patterns within larger taxa as a function of constancy in resource acquisition patterns over time and environments. When this pattern breaks, for example on islands, larger changes can be expected.

Quantitative genetic theory predicts that when populations diverge by drift the interspecific divergence (D matrix), calculated from species means, will be proportional to the average value of the additive genetic variance–covariance matrix, or G matrix. Most empirical studies in which this hypothesis has been investigated have ignored phylogenetic nonindependence among included taxa. Baker and Wilkinson (2003; also Revell et al. 2007) used a test for constraint in which the D matrix is calculated from phylogenetically independent contrasts (Felsenstein 1985) instead of directly from the species means. I use computer simulations to show that, on average, when the process of evolution is genetic drift, the divergence matrix calculated from independent contrasts (DIC) is more highly correlated with G than is the divergence matrix calculated ignoring phylogenetic nonindependence (D). This effect is more pronounced when speciation is initially slow but increases over time than when speciation decreases over time. Finally, when evolution is primarily by drift but phenotype space is bounded (as if by functional constraint) the average correlation is decreased between both G and D or DIC, however the correlation between G and DIC is much larger than between G and D. Although limited in scope, to my knowledge this is the first study to use individual-based quantitative genetic simulations in a phylogenetic context.

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.

For terrestrial plant communities, the increase in frequency and intensity of drought events is considered as one of the most severe consequences of climate change. While single‐species studies demonstrate that drought can lead to relatively rapid adaptive genetic changes, the evolutionary potential and constraints to selection need to be assessed in comparative approaches to draw more general conclusions. In a greenhouse experiment, we compare the phenotypic response and evolutionary potential of two co‐occurring grassland plant species, Bromus erectus and Trifolium pratense, in two environments differing in water availability. We quantified variation in functional traits and reproductive fitness in response to drought and compared multivariate genetic variance–covariance matrices and predicted evolutionary responses between species. Species showed different drought adaptation strategies, reflected in both their species‐specific phenotypic plasticity and predicted responses to selection indicating contrasting evolutionary potential under drought. In T. pratense we found evidence for stronger genetic constraints under drought compared to more favourable conditions, and for some traits plastic and predicted evolutionary responses to drought had opposing directions, likely limiting the potential for adaptive change. Our study contributes to a more detailed understanding of the evolutionary potential of species with different adaptive strategies in response to climate change and may help to inform future scenarios for semi‐natural grassland ecosystems. In a greenhouse experiment, we compare the phenotypic response and evolutionary potential of two co‐occurring grassland plant species, Bromus erectus and Trifolium pratense, in two environments differing in water availability. We quantified variation in functional traits and reproductive fitness in response to drought and compared multivariate genetic variance–covariance matrices and predicted evolutionary responses between species. Species showed different drought adaptation strategies, reflected in both their species‐specific phenotypic plasticity and predicted responses to selection indicating contrasting evolutionary potential under drought.