The stability of P in coral reef fishes

The constancy of phenotypic variation and covariation is an assumption that underlies most recent investigations of past selective regimes and attempts to predict future responses to selection. Few studies have tested this assumption of constancy despite good reasons to expect that the pattern of phenotypic variation and covariation may vary in space and time. We compared phenotypic variance-covariance matrices (P) estimated for populations of six species of distantly related coral reef fishes sampled at two locations on Australia's Great Barrier Reef separated by more than 1000 km. The intraspecific similarity between these matrices was estimated using two methods: matrix correlation and common principal component analysis. Although there was no evidence of equality between pairs of P, both statistical approaches indicated a high degree of similarity in morphology between the two populations for each species. In general, the hierarchical decomposition of the variance-covariance structure of these populations indicated that all principal components of phenotypic variance-covariance were shared but that they differed in the degree of variation associated with each of these components. The consistency of this pattern is remarkable given the diversity of morphologies and life histories encompassed by these species. Although some phenotypic instability was indicated, these results were consistent with a generally conserved pattern of multivariate selection between populations.     

Drift effects on the multivariate floral phenotype of Calceolaria polyrhiza during a post‐glacial expansion in Patagonia

Quaternary environmental changes substantially impacted the landscape and promoted rapid evolutionary changes in many species; however, analyses of adaptive phenotypic variation in plants have usually neglected the underlying historical context. Here, we associate phylogeography and phenotypic evolution by analysing the divergence of Calceolaria polyrhiza multivariate floral phenotype after a Pleistocene post‐glacial expansion in Patagonia. Phenotypic matrix ( P ) properties (size, shape, orientation and phenotypic integration) of six refugium and six recent populations from two different phylogroups were compared following different approaches. We found that P ‐matrix shape and orientation remained stable despite the strong phylogeographic footprint of post‐glacial expansion. However, average proportional reductions in matrix size supported the expectation that drift had a significant effect on the floral phenotype in the northern phylogroup. When phylogeographic history was not included in the analyses, the results overestimated phenotypic differences, whereas under explicit phylogeographic control, drift appeared as the best explanation for matrix differences. In general, recent populations showed a larger phenotypic divergence among them, but a lower overall phenotypic variation than refugium populations. Random Skewers analyses indicated a lower potential response to selection in recently colonized populations than in refugium populations. We discuss that the combination of phylogeographic analyses with geographical distribution of functional phenotypic (genotypic) variation is critical not only to understand how historical effects influence adaptive evolution, but also to improve field comparisons in evolutionary ecology studies.     

TYPE I ERROR RATES FOR TESTING GENETIC DRIFT WITH PHENOTYPIC COVARIANCE MATRICES: A SIMULATION STUDY

Studies of evolutionary divergence using quantitative genetic methods are centered on the additive genetic variance–covariance matrix ( G ) of correlated traits. However, estimating G properly requires large samples and complicated experimental designs. Multivariate tests for neutral evolution commonly replace average G by the pooled phenotypic within‐group variance–covariance matrix ( W ) for evolutionary inferences, but this approach has been criticized due to the lack of exact proportionality between genetic and phenotypic matrices. In this study, we examined the consequence, in terms of type I error rates, of replacing average G by W in a test of neutral evolution that measures the regression slope between among‐population variances and within‐population eigenvalues (the Ackermann and Cheverud [AC] test) using a simulation approach to generate random observations under genetic drift. Our results indicate that the type I error rates for the genetic drift test are acceptable when using W instead of average G when the matrix correlation between the ancestral G and P is higher than 0.6, the average character heritability is above 0.7, and the matrices share principal components. For less‐similar G and P matrices, the type I error rates would still be acceptable if the ratio between the number of generations since divergence and the effective population size (t/N_e) is smaller than 0.01 (large populations that diverged recently). When G is not known in real data, a simulation approach to estimate expected slopes for the AC test under genetic drift is discussed.     

VARIATION IN GENETIC ARCHITECTURE OF CALLING SONG AMONG POPULATIONS OF ALLONEMOBIUS SOCIUS,A. FASCIATUS,AND A HYBRID POPULATION: DRIFT OR SELECTION?

Predictions using quantitative genetic models generally assume that the variance-covariance matrices remain constant over time. This assumption is based on the supposition that selection is generally weak and hence variation lost through selection can be replaced by new mutations. Whether this is generally true can only be ascertained from empirical studies. Ideally for such a study we should be able to make a prediction concerning the relative strength of selection versus genetic drift. If the latter force is prevalent then the variance-covariances matrices should be proportional to each other. Previous studies have indicated that females in the two sibling cricket species Allonemobius socius and A. fasciatus do not discriminate between males of the two species by their calling song. Therefore, differences between the calling song of the two males most likely result from drift rather than sexual selection. We test this hypothesis by comparing the genetic architecture of calling song of three populations of A. fasciatus with two populations of A. socius. We found no differences among populations within species, but significant differences in the G (genetic) and P (phenotypic) matrices between species, with the matrices being proportional as predicted under the hypothesis of genetic drift. Because of the proportional change in the (co)variances no differences between species are evident in the heritabilities or genetic correlations. Comparison of the two species with a hybrid population from a zone of overlap showed highly significant nonproportional variation in genetic architecture. This variation is consistent with a general mixture of two separate genomes or selection. Qualitative conclusions reached using the phenotypic matrices are the same as those reached using the genetic matrices supporting the hypothesis that the former may be used as surrogate measures of the latter.     

Structure and stability of genetic variance–covariance matrices: A Bayesian sparse factor analysis of transcriptional variation in the three‐spined stickleback

The genetic variance–covariance matrix ( G ) is a quantity of central importance in evolutionary biology due to its influence on the rate and direction of multivariate evolution. However, the predictive power of empirically estimated G ‐matrices is limited for two reasons. First, phenotypes are high‐dimensional, whereas traditional statistical methods are tuned to estimate and analyse low‐dimensional matrices. Second, the stability of G to environmental effects and over time remains poorly understood. Using Bayesian sparse factor analysis (BSFG) designed to estimate high‐dimensional G ‐matrices, we analysed levels variation and covariation in 10,527 expressed genes in a large (n = 563) half‐sib breeding design of three‐spined sticklebacks subject to two temperature treatments. We found significant differences in the structure of G between the treatments: heritabilities and evolvabilities were higher in the warm than in the low‐temperature treatment, suggesting more and faster opportunity to evolve in warm (stressful) conditions. Furthermore, comparison of G and its phenotypic equivalent P revealed the latter is a poor substitute of the former. Most strikingly, the results suggest that the expected impact of G on evolvability—as well as the similarity among G ‐matrices—may depend strongly on the number of traits included into analyses. In our results, the inclusion of only few traits in the analyses leads to underestimation in the differences between the G ‐matrices and their predicted impacts on evolution. While the results highlight the challenges involved in estimating G , they also illustrate that by enabling the estimation of large G ‐matrices, the BSFG method can improve predicted evolutionary responses to selection.     

Patterns of phenotypic covariation and correlation in modern humans as viewed from morphological integration

Proportionality of phenotypic and genetic distance is of crucial importance to adequately focus on population history and structure, and it depends on the proportionality of genetic and phenotypic covariance. Constancy of phenotypic covariances is unlikely without constancy of genetic covariation if the latter is a substantial component of the former. If phenotypic patterns are found to be relatively stable, the most probable explanation is that genetic covariance matrices are also stable. Factors like morphological integration account for such stability. Morphological integration can be studied by analyzing the relationships among morphological traits. We present here a comparison of phenotypic correlation and covariance structure among worldwide human populations. Correlation and covariance matrices between 47 cranial traits were obtained for 28 populations, and compared with design matrices representing functional and developmental constraints. Among-population differences in patterns of correlation and covariation were tested for association with matrices of genetic distances (obtained after an examination of 10 Alu-insertions) and with Mahalanobis distances (computed after craniometrical traits). All matrix correlations were estimated by means of Mantel tests. Results indicate that correlation and covariance structure in our species is stable, and that among-group correlation/covariance similarity is not related to genetic or phenotypic distance. Conversely, genetic and morphological distance matrices were highly correlated. Correlation and covariation patterns were largely associated with functional and developmental factors, which probably account for the stability of covariance patterns.     

DISSECTING CORRELATED CHARACTERS: ADAPTIVE ASPECTS OF PHENOTYPIC COVARIATION IN MELANIZATION PATTERN OF PIERIS BUTTERFLIES

In this study we address the question of how much of the covariation among phenotypic characters observed in natural populations is adaptive. We examine covariation among a set of phenotypic characters that describe the wing-melanization pattern of Pieris butterflies. Previous functional analyses of thermoregulatory performance allow us to predict a priori whether and how different wing melanic characters should be correlated. We quantify and analyze the variation in the wing-melanization pattern within species for a series of Pieris populations from relatively cool environments in North America and compare these results with the predictions based on our adaptive hypothesis. We consider adaptive covariation both for biogeographic variation among populations and for seasonal polyphenism (phenotypic plasticity) within populations. Our hypothesis correctly predicts many of the qualitative features of covariation in melanization among major regions of the wings, at the level of biogeographic variation among populations, for both males and females of Pieris occidentalis. When within-population variation is considered, agreement with the adaptive predictions varies considerably in different populations for both P. occidentalis and P. napi males and females. Agreement for P. napi, particularly the females, is generally poorer than for P. occidentalis. In both species, there is a consistent difference in melanization pattern between alpine and arctic sites; this difference is discussed in relation to the differences in the radiative environment between these two types of “cold” habitats. Our results suggest that some important aspects of phenotypic correlation among wing melanic characters in Pieris are adaptive. We emphasize the important distinction between covariation and co-occurrence of characters, and we discuss these results in relation to the extensive biogeographic variation and phenotypic plasticity (seasonal polyphenism) in Pieris wing-melanization patterns.     

The constancy of the G matrix through species divergence and the effects of quantitative genetic constraints on phenotypic evolution: a case study in crickets

Long-term phenotypic evolution can be modeled using the response-to-selection equation of quantitative genetics, which incorporates information about genetic constraints (the G matrix). However, little is known about the evolution of G and about its long-term importance in constraining phenotypic evolution. We first investigated the degree of conservation of the G matrix across three species of crickets and qualitatively compared the pattern of variation of G to the phylogeny of the group. Second, we investigated the effect of G on phenotypic evolution by comparing the direction of greatest quantitative genetic variation within species (g(max)) to the direction of phenotypic divergence between species (Delta(z)). Each species, Gryllus veletis, G. firmus, and G. pennsylvanicus, was reared in the laboratory using a full-sib breeding design to extract quantitative genetic information. Five morphological traits related to size were measured. G matrices were compared using three statistical approaches: the T method, the Flury hierarchy, and the MANOVA method. Results revealed that the differences between matrices were small and mostly caused by differences in the magnitude of the genetic variation, not by differences in principal component structure. This suggested that the G matrix structure of this group of species was preserved, despite significant phenotypic divergence across species. The small observed differences in G matrices across species were qualitatively consistent with genetic distances, whereas ecological information did not provide a good prediction of G matrix variation. The comparison of g(max) and Delta(z) revealed that the angle between these two vectors was small in two of three species comparisons, whereas the larger angle corresponding to the third species comparison was caused in large part by one of the five traits. This suggests that multivariate phenotypic divergence occurred mostly in a direction predicted by the direction of greatest genetic variation, although it was not possible to demonstrate the causal relationship from G to Delta(z). Overall, this study provided some support for the validity of the predictive power of quantitative genetics over evolutionary time scales.     

Population divergence of genetic (co)variance matrices in a subdivided plant species,Brassica cretica

Abstract The present study of Brassica cretica had two objectives. First, we compared estimates of population structure (Q_st) for seven phenotypic characters with the corresponding measures for allozyme markers (F_st) to evaluate the supposition that genetic drift is a major determinant of the evolutionary history of this species. Secondly, we compared the genetic (co)variance ( G ) matrices of five populations to examine whether a long history of population isolation is associated with large, consistent differences in the genetic (co)variance structure. Differences between estimates of F_st and Q_st were too small to be declared significant, indicating that stochastic processes have played a major role in the structuring of quantitative variation in this species. Comparison of populations using the common principal component (CPC) method rejected the hypothesis that the G matrices differed by a simple constant of proportionality: most of the variation involved principal component structure rather than the eigenvalues. However, there was strong evidence for proportionality in comparisons using the method of percentage reduction in mean‐square error (MSE), at least when characters with unusually high (co)variance estimates were included in the analyses. Although the CPC and MSE methods provide different, but complementary, views of G matrix variation, we urge caution in the use of proportionality as an indicator of whether genetic drift is responsible for divergence in the G matrix.     

Deciphering the Palimpsest: Studying the Relationship Between Morphological Integration and Phenotypic Covariation

Organisms represent a complex arrangement of anatomical structures and individuated parts that must maintain functional associations through development. This integration of variation between functionally related body parts and the modular organization of development are fundamental determinants of their evolvability. This is because integration results in the expression of coordinated variation that can create preferred directions for evolutionary change, while modularity enables variation in a group of traits or regions to accumulate without deleterious effects on other aspects of the organism. Using our own work on both model systems (e.g., lab mice, avians) and natural populations of rodents and primates, we explore in this paper the relationship between patterns of phenotypic covariation and the developmental determinants of integration that those patterns are assumed to reflect. We show that integration cannot be reliably studied through phenotypic covariance patterns alone and argue that the relationship between phenotypic covariation and integration is obscured in two ways. One is the superimposition of multiple determinants of covariance in complex systems and the other is the dependence of covariation structure on variances in covariance-generating processes. As a consequence, we argue that the direct study of the developmental determinants of integration in model systems is necessary to fully interpret patterns of covariation in natural populations, to link covariation patterns to the processes that generate them, and to understand their significance for evolutionary explanation.     

Multivariate Phenotypic Evolution: Divergent Acoustic Signals and Sexual Selection in <Emphasis Type="Italic">Gryllus</Emphasis> Field Crickets

Predicting the response to selection is at the core of evolutionary biology. Presently, thorough understanding of the effects of selection on the multivariate phenotype is lacking, in particular for behavioral traits. Here, we compared multivariate acoustic mating signals among seven field cricket species contrasting two selection regimes: (1) species producing songs with long trains of pulses for which preference functions for acoustic energy (chirp duty cycle) are linear and likely exert strong directional selection (‘trillers’); (2) species producing songs consisting of short chirps and for which preference functions for chirp duty cycle are concave and directional selection is likely weak or absent (‘chirpers’). We compared the phenotypic variance–covariance matrix (P) among species and uncovered two main patterns: First, surprisingly, pulse rate and chirp rate were positively correlated in six of seven species thus suggesting phenotypic coupling of timescales. Second, chirp rate and chirp duty cycle also covaried, but the direction of covariation differed between chirpers (positive) and trillers (negative). Multi-population Bayesian methods for matrix comparisons, Krzanowski’s subspace comparison and tensor analysis, revealed significant variation in P unrelated to phylogenetic distance, but strongly contrasting chirpers and trillers. We also found differences in the predicted selection response between chirpers and trillers. We thus report that variation in P is higher between than within selection regimes. Although effects from drift and shared ancestry cannot be fully excluded, these findings highlight a role for sexual selection in shaping patterns of phenotypic covariation that can ultimately affect the evolutionary trajectory of a multivariate mating signal.     

The evolution of sexual dimorphism in the house finch. I. Population divergence in morphological covariance structure

Abstract Patterns of genetic variation and covariation strongly affect the rate and direction of evolutionary change by limiting the amount and form of genetic variation available to natural selection. We studied evolution of morphological variance-covariance structure among seven populations of house finches (Carpodacus mexicanus) with a known phylogenetic history. We examined the relationship between within- and among-population covariance structure and, in particular, tested the concordance between hierarchical changes in morphological variance-covariance structure and phylogenetic history of this species. We found that among-population morphological divergence in either males or females did not follow the within-population covariance patterns. Hierarchical patterns of similarity in morphological covariance matrices were not congruent with a priori defined historical pattern of population divergence. Both of these results point to the lack of proportionality in morphological covariance structure of finch populations, suggesting that random drift alone is unlikely to account for observed divergence. Furthermore, drift alone cannot explain the sex differences in within- and among-population covariance patterns or sex-specific patterns of evolution of covariance structure. Our results suggest that extensive among-population variation in sexual dimorphism in morphological covariance structure was produced by population differences in local selection pressures acting on each sex.     

Genetics of body shape and armour variation in threespine sticklebacks

Patterns of genetic variation and covariation can influence the rate and direction of phenotypic evolution. We explored the possibility that the parallel morphological evolution seen in threespine stickleback (Gasterosteus aculeatus) populations colonizing freshwater environments is facilitated by patterns of genetic variation and covariation in the ancestral (marine) population. We estimated the genetic (G) and phenotypic (P) covariance matrices and directions of maximum additive genetic (g(max) ) and phenotypic (p(max) ) covariances of body shape and armour traits. Our results suggest a role for the ancestral G in explaining parallel morphological evolution in freshwater populations. We also found evidence of genetic constraints owing to the lack of variance in the ancestral G. Furthermore, strong genetic covariances and correlations among traits revealed that selective factors responsible for threespine stickleback body shape and armour divergence may be difficult to disentangle. The directions of g(max) and p(max) were correlated, but the correlations were not high enough to imply that phenotypic patterns of trait variation and covariation within populations are very informative of underlying genetic patterns.     

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.     

Covariation of larval gene expression and adult body size in natural populations of Drosophila melanogaster

Understanding adaptive phenotypic variation is one of the most fundamental problems in evolutionary biology. Genes involved in adaptation are most likely those that affect traits most intimately connected to fitness: life-history traits. The genetics of quantitative trait variation (including life histories) is still poorly understood, but several studies suggest that (1) quantitative variation might be the result of variation in gene expression, rather than protein evolution, and (2) natural variation in gene expression underlies adaptation. The next step in studying the genetics of adaptive phenotypic variation is therefore an analysis of naturally occuring covariation of global gene expression and a life-history trait. Here, we report a microarray study addressing the covariation in larval gene expression and adult body weight, a life-history trait involved in adaptation. Natural populations of Drosophila melanogaster show adaptive geographic variation in adult body size, with larger animals at higher latitudes. Conditions during larval development also affect adult size with larger flies emerging at lower temperatures. We found statistically significant differences in normalized larval gene expression between geographic populations at one temperature (genetic variation) and within geographic populations between temperatures (developmental plasticity). Moreover, larval gene expression correlated highly with adult weight, explaining 81% of its natural variation. Of the genes that show a correlation of gene expression with adult weight, most are involved in cell growth or cell maintenance or are associated with growth pathways.     

Evolutionary divergence in directions of high phenotypic variance in the ostracode genus poseidonamicus

Trait variation and covariation are understood to influence the response of populations to natural selection on generational time scales, but their role, if any, in shaping long-term macroevolutionary divergence is still unclear. The present study uses the rich fossil record of the ostracode genus Poseidonamicus to reconstruct in great detail the evolutionary history of a set of landmark-based morphometric characters. This reconstruction included two kinds of evolutionary inferences: ancestor-descendant transitions among populations repeatedly sampled at the same location and divergence between lineages measured as independent contrasts on a phylogeny. This reconstructed history was then used to test if evolutionary changes were concentrated in directions (traits or combinations of traits) with high phenotypic variance. Two different statistics of association between evolution and variation tested the null hypothesis that evolutionary changes occur in random directions with respect to trait variability. The first of these measured the similarity between the directions of evolutionary change and the axis of maximum variance, and the second measured the degree to which evolutionary changes were concentrated in directions of high phenotypic variation. Randomization tests indicated that both kinds of evolutionary inferences (ancestor-descendant and phylogenetic contrasts) occurred preferentially in directions of high phenotypic variance (and close to the axis of maximal variation), suggesting that within-population variation can structure long-term divergence. This effect decayed after a few million years, but at least for one metric, never disappeared completely. These results are consistent with Schluter's genetic constraints model in which evolutionary trajectories on adaptive landscapes are deflected by variation within and covariation among traits.     

Concordance between stabilizing sexual selection,intraspecific variation,and interspecific divergence in Phymata

Empirical studies show that lineages typically exhibit long periods of evolutionary stasis and that relative levels of within‐species trait covariance often correlate with the extent of between‐species trait divergence. These observations have been interpreted by some as evidence of genetic constraints persisting for long periods of time. However, an alternative explanation is that both intra‐ and interspecific variation are shaped by the features of the adaptive landscape (e.g., stabilizing selection). Employing a genus of insects that are diverse with respect to a suite of secondary sex traits, we related data describing nonlinear phenotypic (sexual) selection to intraspecific trait covariances and macroevolutionary divergence. We found support for two key predictions (1) that intraspecific trait covariation would be aligned with stabilizing selection and (2) that there would be restricted macroevolutionary divergence in the direction of stabilizing selection. The observed alignment of all three matrices offers a point of caution in interpreting standing variability as metrics of evolutionary constraint. Our results also illustrate the power of sexual selection for determining variation observed at both short and long timescales and account for the apparently slow evolution of some secondary sex characters in this lineage.     

Phenotypic Variation in Infants,Not Adults,Reflects Genotypic Variation among Chimpanzees and Bonobos

Studies comparing phenotypic variation with neutral genetic variation in modern humans have shown that genetic drift is a main factor of evolutionary diversification among populations. The genetic population history of our closest living relatives, the chimpanzees and bonobos, is now equally well documented, but phenotypic variation among these taxa remains relatively unexplored, and phenotype-genotype correlations are not yet documented. Also, while the adult phenotype is typically used as a reference, it remains to be investigated how phenotype-genotye correlations change during development. Here we address these questions by analyzing phenotypic evolutionary and developmental diversification in the species and subspecies of the genus Pan. Our analyses focus on the morphology of the femoral diaphysis, which represents a functionally constrained element of the locomotor system. Results show that during infancy phenotypic distances between taxa are largely congruent with non-coding (neutral) genotypic distances. Later during ontogeny, however, phenotypic distances deviate from genotypic distances, mainly as an effect of heterochronic shifts between taxon-specific developmental programs. Early phenotypic differences between Pan taxa are thus likely brought about by genetic drift while late differences reflect taxon-specific adaptations.     

High evolutionary constraints limited adaptive responses to past climate changes in toad skulls

Interactions among traits that build a complex structure may be represented as genetic covariation and correlation. Genetic correlations may act as constraints, deflecting the evolutionary response from the direction of natural selection. We investigated the relative importance of drift, selection, and constraints in driving skull divergence in a group of related toad species. The distributional range of these species encompasses very distinct habitats with important climatic differences and the species are primarily distinguished by differences in their skulls. Some parts of the toad skull, such as the snout, may have functional relevance in reproductive ecology, detecting water cues. Thus, we hypothesized that the species skull divergence was driven by natural selection associated with climatic variation. However, given that all species present high correlations among skull traits, our second prediction was of high constraints deflecting the response to selection. We first extracted the main morphological direction that is expected to be subjected to selection by using within- and between-species covariance matrices. We then used evolutionary regressions to investigate whether divergence along this direction is explained by climatic variation between species. We also used quantitative genetics models to test for a role of random drift versus natural selection in skull divergence and to reconstruct selection gradients along species phylogeny. Climatic variables explained high proportions of between-species variation in the most selected axis. However, most evolutionary responses were not in the direction of selection, but aligned with the direction of allometric size, the dimension of highest phenotypic variance in the ancestral population. We conclude that toad species have responded to selection related to climate in their skulls, yet high evolutionary constraints dominated species divergence and may limit species responses to future climate change.     

An analysis of G matrix variation in two closely related cricket species,Gryllus firmus and G. pennsylvanicus

An important issue in evolutionary biology is understanding the pattern of G matrix variation in natural populations. We estimated four G matrices based on the morphological traits of two cricket species, Gryllus firmus and G. pennsylvanicus, each reared in two environments. We used three matrix comparison approaches, including the Flury hierarchy, to improve our ability to perceive all aspects of matrix variation. Our results demonstrate that different methods perceive different aspects of the matrices, which suggests that, until more is known about these methods, future studies should use several different statistical approaches. We also found that the differences in G matrices within a species can be larger than the differences between species. We conclude that the expression of the genetic architecture can vary with the environment and that future studies should compare G matrices across several environments. We also conclude that G matrices can be conserved at the level of closely related species.