Role of drift in evolution of sexually dimorphic traits

Role of drift in evolution of sexually dimorphic traits

We are searching data for your request:

Forums and discussions:
Manuals and reference books:
Data from registers:
Wait the end of the search in all databases.
Upon completion, a link will appear to access the found materials.

Is there a model for predicting how drift can affect the evolution of a sexually dimorphic (SD) trait? I've been trying wrap my mind around this paradoxical question; sexually dimorphic traits evolve due to sex-specific selection. So how can drift affect SD traits?

I've found the quantitative genetic equations (eq 1) in Lande 1980 very helpful for thinking about the parameters and how sexual dimorphism evolves. Can this model be applied to a population bottleneck? Or comparing the degree of SD in a trait of two divergent populations (assuming s, Ne and other parameters remains constant). $$ egin {pmatrix} Delta z Delta y end{pmatrix} = {1 over 2} egin{pmatrix} G_m B B^{T} G_f end{pmatrix} egin{pmatrix} P_m^{-1} s_m P_f^{-1} s_f end{pmatrix} $$

Edit: I've added the equation from Lande 1980, which models the phenotypic response for sexually dimorphic traits. I'm wondering how aspects of drift (Ne and fixation probabilities) can be merged with an equation such as this. From my understanding drift may affect the G, B and P matrices (that is the Genotype variance covariance, intersex (B) variance covariance and Phenotype matrices. One of the assumptions of this equation is that these matrices remain constant.

[C]an drift overcome sexual selection in the evolution of sexually dimorphic traits?

Short answer


Long answer

There are many ways to consider the effect of genetic drift. Here is one: One can approximate the probability of fixation of new mutations (using diffusion equations) with

$$P_{fix}≈frac{1-e^{-4Ns} }{1-e^{-4s}}$$

, where $s$ is the selection coefficient and $N$ is the populations size. As you can see, a larger population size (the lowest is the genetic drift) corresponds to a higher probability of fixation of a beneficial mutation (to reach frequency of 1 in the population). If you don't have a good intuition of why genetic drift is inversely proportional to the population size, please have a look at this post. The most important point to keep in mind about the effect of drift is that when drift is high, every mutation pretty much behaves like neutral mutations.

This approximation is accurate under some assumption, for instance that the population is panmictic (=random mating). This equation holds true regardless of the reasons why a mutation affects fitness. The mutation may affect the activity level of an enzyme or it may influence how attractive an individual is to the other sex. So yes, in any case, a beneficial mutation may fix although it is deleterious (because of drift), or it may not fix although it is beneficial (because of drift).

A mutation might be beneficial in both sexes, detrimental in both sexes or beneficial in one sex and not in the other. In such cases, I suppose it is possible that the above equation must take a slightly different form. In any case where the mutation has a different impact on the fitness in each gender, I don't know how the above formulation would solve to but I'd think that you could simply replace $s$, by $frac{s_m+s_f}{2}$, that is the average of the effect in both sexes (where $s_m$ and $s_f$ are the selection coefficients in males and females respectively). Intuitively, I think this should hold true as long as the sex-ratio is 1:1. The exact calculation of the probability of fixation doesn't matter to your question though. Note that mutations having the opposite effect on fitness in each gender often end up being on sexual chromosomes (if any) or at least being expressed in one sex but not in the other. In such case, a fixed mutation often end up being beneficial in one sex while neutral in the other. In any case, genetic drift will obviously affect the evolution of sexually dimorphic traits.


could you clarify "As you can see the highest is the population size (the lowest is the genetic drift),"?

The impact of genetic drift can be measured in terms of how it affects probability of fixation or how it affects the rate at which heterozygosity at a neutral site is lost. An intuitive explanation for why $N$ and genetic drift are inversely proportional can be found here.

Are you referring to the positive correlation with P fixation and Ne?

Yes. I could have referred to that as to something else though. Note that the correlation between $P$ ans $N_e$ is perfect ($r^2=1$) because $N_e$ is defined on the concept of genetic drift.

Definition of $N_e$

Let'sWR(stands for Wright-Fisher) be a population of size $N_{WR}$ where mating is random and there is no variance in fitness.

Consider now the populationA. Let's its size be $N$.Aexperiences a given level of genetic drift based on its mating system, population structure, variance in fitness, etc… the effective population size $N_e$ ofAis (by definition) the size of theWRpopulation ($N_{WR}$) that experiences the exact same level of drift, that is the same probability of fixation for a new mutation and the same rate of heterozygosity lose at a neutral site.

I wrote my question asking about the relationship of drift in the evolution of SD (sexual dimorphism), but after reading up more on the subject I've determined there are at least two parameters to consider when thinking about the evolution of SD.

  1. Population structure and demographic history (Ne and drift outlined nicely by @Remi.b )
  2. Intersexual correlation of the genetic architecture of the trait(s) evolving SD (how much genetic variation is shared between the homologous male and female traits?)

The intersexual genetic correlation between the sexes will constrain evolution in the sexes if selective forces are distinct for the sexes. This degree of correlation can be represented as rMF for single traits (Lynch and Walsh 1998 chapter 24) or the B matrix when examining the relationship between multiple traits (Lande 1980).

Two recent papers by Connallon and Clark (1 and 2) outline their adaptation to Fisher's geometric fitness model which to predict mutation affects on traits given distinct phenotype-fitness spaces for the 2 sexes. The mean phenotype of each sex is a certain distance and angle away from the fitness optima (this vector represents the magnitude and direction of directional selection). The angle of these vectors represent the difference in selective forces for male and female traits. The current phenotypes are moved along the landscape by the addition of novel genetic variation (mutations). Mutations shift the trajectory of the current phenotype towards the optima. As in the selection vectors, the difference between the mutation vectors is quantified by the angle between the sex specific vectors, and can either move both sexes towards their respective optima or move only one sex towards their optima (sexually antagonistic selection).

While this model doesn't directly take into account Ne for predictions on drift, it does emphasize that distinct fitness landscapes eventually cause antagonistic selection due to decoupled fitness effects for female and male traits due to random mutations.

“Evolution of sexual antagonism occurs whether or not selection favors phenotypic divergence between the sexes.” 1

This wasn't a direct answer, but it provided insight into how selective forces and pleiotropy of traits can shape the evolution of SD.


Mating preferences are common in natural populations, and their divergence among populations is considered an important source of reproductive isolation during speciation. Although mechanisms for the divergence of mating preferences have received substantial theoretical treatment, complementary experimental tests are lacking. We conducted a laboratory evolution experiment, using the fruit fly Drosophila serrata, to explore the role of divergent selection between environments in the evolution of female mating preferences. Replicate populations of D. serrata were derived from a common ancestor and propagated in one of three resource environments: two novel environments and the ancestral laboratory environment. Adaptation to both novel environments involved changes in cuticular hydrocarbons, traits that predict mating success in these populations. Furthermore, female mating preferences for these cuticular hydrocarbons also diverged among populations. A component of this divergence occurred among treatment environments, accounting for at least 17.4% of the among-population divergence in linear mating preferences and 17.2% of the among-population divergence in nonlinear mating preferences. The divergence of mating preferences in correlation with environment is consistent with the classic by-product model of speciation in which premating isolation evolves as a side effect of divergent selection adapting populations to their different environments.

Citation: Rundle HD, Chenoweth SF, Doughty P, Blows MW (2005) Divergent Selection and the Evolution of Signal Traits and Mating Preferences. PLoS Biol 3(11): e368.

Academic Editor: Joel Kingsolver, The University of North Carolina, United State of America

Received: May 13, 2005 Accepted: August 27, 2005 Published: October 25, 2005

Copyright: © 2005 Rundle et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Competing interests: The authors have declared that no competing interests exist.

Abbreviations: CHC, cuticular hydrocarbon CV, canonical variate GC, gas chromatography MS, mean square

Pupal Remodeling and the Development and Evolution of Sexual Dimorphism in Horned Beetles

Horns or hornlike structures in beetles have become an increasingly popular study system for exploring the evolution and development of secondary sexual trait diversity and sexual dimorphisms. The horns of adult beetles originate during a rapid growth phase during the prepupal stage of larval development, and differential activation of growth during this time is either implicitly or explicitly assumed to be the sole mechanism underlying intra‐ and interspecific differences in adult horn expression. Here I show that this assumption is not based on developmental reality. Instead, after their initial prepupal growth phase, beetle horns are extensively remodeled during the subsequent pupal stage via sex‐ and size‐dependent resorption of horn tissue. I show that adult sexual dimorphism in four Onthophagus species is shaped partly or entirely by such pupal remodeling rather than by differential growth. Specifically, I show that after a sexually monomorphic growth phase, differential pupal horn resorption can generate both regular and reversed sexual dimorphism. Furthermore, I show that in cases in which initial growth is already dimorphic, pupal horn resorption can both magnify and reverse initial dimorphism resulting from differential growth. Finally, I show that complete resorption of pupal horns in both sexes can remove any trace of horn expression from all resulting adults. In such species, examination of adults only would result in the false conclusion that this species lacks the ability to develop a horn. Instead, such species appear to differ from those with sexually dimorphic adults merely in that they activate pupal horn resorption in both sexes rather than in just one. Combined, these results suggest that pupal remodeling of secondary trait expression is taxonomically widespread, at least among Onthophagus species, and is developmentally extensive and remarkably evolutionarily labile. These results have immediate implications for reconstructing the evolutionary history of horned beetles and the role of developmental processes in guiding evolutionary trajectories. I use these results to revise current understanding of the evolutionary developmental biology of secondary sexual traits in horned beetles in particular and holometabolous insects in general. The results presented here seriously call into question whether descriptions of adult diversity patterns alone suffice for meaningful inferences toward understanding the developmental and evolutionary origin of these patterns. These results illustrate that a lasting integration of development into an evolutionary framework must integrate development as a process rather than define it solely by some of its products.

Materials and methods

Acquisition of facial photographs

We used 1317 standardized frontal photographs, some of which were used in previous studies 62,63,64,65,66,67 . The number of individuals in each population is shown in supplementary table S1 and demographic characteristics of the studied populations are provided in supplementary table S4. For purposes of allometric decomposition, the dataset was restricted to 1114 individuals for whom we had reliable information about their body height (summarized in supplementary table S3). The facial images were taken by standardized protocol within each population, which allowed a subsequent measure of sexual dimorphism. All participants were asked to adopt a neutral, non-smiling expression, and to remove facial cosmetics, jewelry, or other decorations, if possible. We instructed participants to look directly into the camera to avoid vertical and horizontal head tilts. The photographs were subsequently post-produced to adjust the eyes horizontally at the same height.

To demonstrate that the variation in focal length does not pose a problem for deriving our conclusions, we regress facial shape on logarithm of focal length and considered only the residuals of this regression as a material for alternative analysis with equivalent regression models and summarizations. The results of this alternative analysis are very similar to the results of the main analysis that does not account for focal length (see

Attractiveness ratings

Rating sessions took place in each of the investigated populations, and raters judged only opposite-sex faces from their own population. Ratings were collected using images presented on a computer screen. Raters from all populations (except Colombia) were asked to judge the attractiveness of 50 faces of the opposite sex on a 7-point verbally anchored scale (from “1—not at all attractive” to “7—very attractive”). In Colombia, attractiveness was scored on a 0.0 to 10.0 scale (with one decimal place), anchored verbally from “0.0—not at all attractive” to “10.0—very attractive”. Facial images were presented in a randomized order and time spent rating was not restricted. The ratings for each face were averaged and scaled (mean = 0, SD = 1) by population before analysis. All raters were also asked to report their age and nationality for details about the sample sizes and descriptive statistics about raters from particular populations, see supplementary table S2.

Geometric morphometrics

For each of 1317 faces, we defined 72 landmark positions, from which 36 were a posteriori indicated as semi-landmarks. Landmarks are homologous points that usually correspond to well-defined anatomical and morphological facial structures and can thus be unambiguously identified across all faces in the sample. Semi-landmarks (or sliding landmarks) were used to quantify two-dimensional homologous outlines and curvatures of facial morphology that could not be characterized as traditional landmarks 68 . See supplementary figure S1 for the positions of landmarks and semilandmarks.

The measurement error was estimated on the subsample of 400 faces. The landmarks were placed manually on each facial image by two persons trained by the first author. All configurations were also visually inspected by the first author before analysis. We have employed procD.lm function from the geomorph package to execute the analysis of variance between individual faces and within each individual face landmarked my multiple digitizers (included in a model as an effect of the interaction between the digitizer and the individual) or by a single digitizer twice. Proportion of the variation accountable to the landmarked face is reported as measurement repeatability. The overall repeatability was calculated from the subsample of 400 faces: within digitizer repeatability was estimated on the subsample of 200 faces that were landmark by the same digitizer twice and the between digitizer repeatability estimated on the subsample of 200 faces that were independently landmarked by two digitizers. A repeatability of digitizing precision between two replicates was 0.951 (measurement error: 0.048). The within digitizer repeatability estimated on the subsample of 200 faces that were landmarked by the same digitizer twice was 0.963, the between digitizer repeatability estimated on the subsample of 200 faces that were landmarked by two digitizers was 0.929. The distribution of facial data was checked for possible digitizing errors due to landmark application and outliers by visual inspection of PCA plots and by using plotOutliers function in the Geomorph package in R 69 . PCA was employed by gm.prcomp function in the Geomorph package. Any outliers which were due to a digitizing error were detected prior to analysis and corrected.

All shape coordinates were superimposed by generalized Procrustes analysis (GPA) using the gpagen function in the Geomorph package in R 69,70 . Semi-landmark positions were optimized based on minimal bending energy criterion. After semi-landmarks were slid, aligned coordinates were symmetrized that is, left and right sides were reflected along the midline and mirrored configurations were then averaged using the symmetrize function in the Morpho package 71 .

We measured morphological disparity, estimated as Procrustes variance, to compare morphological variation among groups of faces defined by sex and population. To test for differences in morphological disparity between groups, the morphol.disparity function in the Geomorph package was used, with significance testing based on 9,999 permutations.

Shape variation associated with sexual shape dimorphism of all examined groups were visualized using thin-plate spline (TPS) deformation grids 72,73 . All thin-plate spline extrapolations, and combined plots, were performed with use of the plotRefToTarget function in the Geomorph R package 69 .

Calculating the degree of sexual shape dimorphism of the face

Sexual Shape Dimorphism (SShD) was computed by projection of the individual facial configurations in facial morphospace onto the vector between male and female means. This vector method, i.e. using group averages to define an axis of morphological differences between men and women, has been applied in numerous previous studies on human sexual dimorphism 20,66,74,75,76 . The position of an individual’s face (A) along the axis connecting male (MM) and female mean (FM) shape can be expressed as a dot product of a vector from the origin to the coordinates of A and a vector from FM to MM, i.e.

Higher negative scores indicate more female-like morphology, whereas higher positive scores indicate a more male-like facial shape. To visualize differences in both magnitude and direction of SShD vectors in multidimensional morphospace, we conducted a trajectory analysis using the RRPP R-package 70 .This overall measure of SShD can be decomposed to allometric and non-allometric components, i.e. to variation in SShD that is due to body size (allometric) and variation that is independent of size (non-allometric). Body height was used as a measure of an individual’s size. The allometric variation in SShD was calculated by regressing the original facial coordinates on height and projecting the estimated values from this regression on the vector of sex differences. The non-allometric component of SShD was acquired by regressing the original shape coordinates on height and then projecting the residualized facial coordinates on the sex difference vector calculated on these residuals.

The female scores of overall, allometric, and non-allometric SShD were inverted (multiplied by − 1). Higher values represents more masculine faces in the case of men and more feminine faces in women.

The angle (alpha) between the vector of overall SShD (overrightarrow <>> = left( ight) ) and its allometric component ( (overrightarrow <>> = ) vector of coefficients of multiple regression of facial shape on body height) and between (overrightarrow <>>) and its non-allometric component (overrightarrow <>> =) ( (MM_ - FM_) ) were calculated from the ratio of a dot product of given vectors and a product of their norms following formulas

Statistical procedures

Linear mixed effect models of the influence of overall, allometric, and non-allometric SShD on average rated attractiveness were conducted using the lmer function from the lmerTest package 77 . Females were used as the reference category, and we report the slope of the regression of attractiveness on SShD. The difference between male and female intercepts and male and female slopes were included in the regression model, as fixed effects, to test the difference between males and females. Fully specified random slopes and intercepts by population were included in the model as random effects.

Pearson product moment correlation coefficients were used for all correlational analyses. These were calculated using a cor.test and cor functions from base R.

The regression relationships on populational levels (e.g., difference in body height vs the distance between male and female mean shapes, or the difference or morphological disparity versus SShD between sexes) were evaluated with Bayesian regression with vague weakly informative priors (normal distributions with mean = 0 and SD = 1 on a linear model with standardized variables). The models were fitted with quap function from the rethinking package on standardized variables. The regression estimates and the compatibility corridors were sampled from the posterior distribution using the link function from the rethinking package 78 .

To weight calculated descriptive statistics against their null distributions, two permutation tests were conducted: (1) Randomization test, where populations are assigned at random to facial shapes, while the gender assignment of each face and the number of men and women in each sample remain unchanged and (2) Random split sample test, where each sample was divided into two random subsamples of equal size, and then distribution of average differences between subsamples from the same populations was compared with the distribution of average differences between subsamples from different populations. Ten thousand randomized samples were generated within each permutation test.

Ethics statement

All the experiment protocol for involving humans was in accordance to guidelines of national/international/institutional or Declaration of Helsinki. This study does not include information or images that could lead to identification of a study participant.

Informed consent

Informed consent was obtained from all participants. All procedures mentioned and followed were approved by the Institutional Review Board of the Faculty of Science of the Charles University (protocol ref. number 06/2017).

Sexual Selection and Mate Choice: Insights from Neutralist Perspectives

Darwin’s concept of sexual selection has been an area of intense research interest for the past half-century. Research has mainly focused on intersexual selection (selection arising from mate choice), and has particularly focused on the hypothesis that mates are chosen on the basis of “genetic quality” which is “honestly” signaled by sexually dimorphic traits. I discuss these models in the light of evidence that most genetic variation in real populations is either selectively neutral or slightly deleterious. Since several well-known models have focused on the immune system as a source of heritable variation in fitness, I examine evidence from studies of the vertebrate major histocompatibility complex and its interaction with pathogens. Finally, I discuss alternative hypotheses for the evolution of secondary sexual characteristics that are consistent with the prevalence of purifying selection rather than positive selection in most populations. One such model, the random walk model, relies only on the well-attested processes of mutation, purifying selection, and genetic drift, thereby providing an attractive alternative to models that assume ubiquitous positive selection.

This is a preview of subscription content, access via your institution.

Frequency-dependent Selection

Another type of selection, called frequency-dependent selection , favors phenotypes that are either common (positive frequency-dependent selection) or rare (negative frequency-dependent selection). An interesting example of this type of selection is seen in a unique group of lizards of the Pacific Northwest. Male common side-blotched lizards come in three throat-color patterns: orange, blue, and yellow. Each of these forms has a different reproductive strategy: orange males are the strongest and can fight other males for access to their females blue males are medium-sized and form strong pair bonds with their mates and yellow males (Figure (PageIndex<2>)) are the smallest, and look a bit like females, which allows them to sneak copulations. Like a game of rock-paper-scissors, orange beats blue, blue beats yellow, and yellow beats orange in the competition for females. That is, the big, strong orange males can fight off the blue males to mate with the blue&rsquos pair-bonded females, the blue males are successful at guarding their mates against yellow sneaker males, and the yellow males can sneak copulations from the potential mates of the large, polygynous orange males.

Figure (PageIndex<2>): A yellow-throated side-blotched lizard is smaller than either the blue-throated or orange-throated males and appears a bit like the females of the species, allowing it to sneak copulations. (credit: &ldquotinyfroglet&rdquo/Flickr)

In this scenario, orange males will be favored by natural selection when the population is dominated by blue males, blue males will thrive when the population is mostly yellow males, and yellow males will be selected for when orange males are the most populous. As a result, populations of side-blotched lizards cycle in the distribution of these phenotypes&mdashin one generation, orange might be predominant, and then yellow males will begin to rise in frequency. Once yellow males make up a majority of the population, blue males will be selected for. Finally, when blue males become common, orange males will once again be favored.

Negative frequency-dependent selection serves to increase the population&rsquos genetic variance by selecting for rare phenotypes, whereas positive frequency-dependent selection usually decreases genetic variance by selecting for common phenotypes.

Materials and methods

The evolution of plumage dimorphism and other ecological variables in the Anseriformes was reconstructed over a working phylogeny based on the morphological analyses of Livezey (1986, 1991, 1995a,b,c, 1996a,b, 1997a,b) and Livezey & Humphrey (1992) see Fig. 1. Data were obtained from various reviews ( Cramp & Simmons 1977 Johnsgard 1978 Bellrose 1980 Brown, Urban & Newman 1982 Scott & Clutton-Brock 1989 Marchant & Higgins 1991 Johnsgard & Carbonell 1996 Oxford University Press, unpublished data), and the complete data set is available from the authors on request. Mean male and female body mass were recorded only when derived from at least five individuals of each sex. Male and female plumage brightness was scored following Scott & Clutton-Brock (1989) . Like them, we considered drab plumages to include those that were dull brown or grey, and also those with small patches of brighter colour. Unlike them, we also scored as drab those species with coloured plumage that probably did not contrast against their habitat (following Butcher & Rohwer 1989 ). A species was considered dichromatic when there were differences in colour great enough to allow the identification of the sexes in the field. For species not included in Scott & Clutton-Brock (1989) , scoring was done using the colour plates of Madge & Burn (1988) . To estimate the number of evolutionary changes in plumage brightness and colour dimorphism we used a modified version of Burns’ (1998) categories to score each species as one of the following: (1) monomorphic with both sexes drab (2) monomorphic with both sexes bright (3) dimorphic, male colourful and female drab (4) dimorphic with both sexes drab (5) dimorphic with both sexes colourful (6) dimorphic with male drab and female colourful. The minimum, maximum and mean number of changes occurring in dichromatism and plumage brightness were estimated using parsimony algorithms with the macclade program ( Maddison & Maddison 1992 ). Species were classified as open or cavity nesters according to descriptions in the above revisions. Frequency of pair formation was used as an estimate of intensity of sexual selection, considering the two categories defined by Scott & Clutton-Brock (1989) : species that pair less than once per season, and species that pair on one or more occasions per season. Insular species were defined as those endemic to small islands with an area of less than 20 000 km 2 (after Green 1996 ). The number of species living in sympatry was estimated by plotting the breeding distribution maps in Madge & Burn (1988) over a worldmap grid, a projection of the world divided into 611 000-km 2 grid squares ( Gaston & Blackburn 1996 Williams 1996 ). The total number of species of the same tribe breeding in the squares occupied by the species was used as an index of sympatry. This index is likely to overestimate the number of species living in sympatry because some of them could breed in different habitats with no real possibility of interaction during the breeding season. Another potential problem associated with this index is that a variable proportion of the individuals of some Anseriformes pair in winter ( Baldassarre & Bolen 1994 ), when the species could be in sympatry with different species than during the breeding season. Consequently, our sympatry index is an imperfect measure of the real number of potential competitors living in sympatry.

Phylogeny for the Anseriformes used in this study, based on the morphological analyses of Livezey (1986, 1991, 1995a,b,c, 1996a,b, 1997a,b) and Livezey & Humphrey (1992) . The characters in some parts of the tree could not be resolved by parsimony algorithms and are reported as equivocal. This is why the number of unambiguous changes and mean number of changes are reported in Table 1.

The associations between the evolution of mating systems or nest placement and plumage brightness and dichromatism were analysed separately following Pagel (1994) . This method is based on a Markov-transition rate model of trait evolution, and since the results do not depend on the particular set of ancestral values that might be assigned by parsimony, the problems derived from ancestral character reconstruction are avoided ( Pagel 1997 ). However, the model assumes a constant probability of change throughout the tree. A model of independent evolution and another of correlated evolution were calculated and the model best fitting the data was identified by maximum likelihood statistical methods, using the discrete program ( Pagel 1997, 1999 ). To ensure that the most stable solution was reached, analyses were repeated until four estimates of model likelihood were obtained that differed only at the second or lower decimal place. The statistical significance of differences between the evolution-dependent and independent models was determined using Monte Carlo tests, because the statistic does not match any commonly used statistical distribution. The likelihood ratio (LR) obtained from the data was compared to those derived from 200 runs simulating the evolution of the two characters studied over the phylogeny using the independent model parameters. Each of these simulations was analysed with the models of dependent and independent changes, and the LR was calculated. The directionality of the significant relationships was tested according to Pagel (1994) , by forcing the relevant parameter in the model of dependent evolution to take the same value as another related parameter in the model. For example, to determine whether shorter pair bonds are associated with increased frequency of evolution of sexual dichromatism, the probabilities of change in dichromatism in species with short and long pair bonds were forced to take the same value. If this model had a significantly reduced fit to the data, the hypothesis of equal probability of change with respect to mating frequency was rejected. In these analyses, the statistical significance of the changes in likelihood was determined using the χ 2 distribution (1 df). Pagel’s method cannot deal with polytomies (multiple speciation events or unresolved parts of the tree, see Fig. 1), and for these analyses a fully resolved parsimonious version of the tree was used (i.e. that tree minimizing the number of evolutionary changes in the characters of interest).

In most cases, interspecific data should not be analysed with traditional regression methods, because data from different species are not statistically independent. Thus, to examine the relation between size and different ecological variables, independent contrasts were used ( Felsenstein 1985 Harvey & Pagel 1991 ). The contrasts were calculated as the differences in the characters of interest between pairs of closely related taxa. These contrasts were standardized in relation to the time elapsed since the separation of the lineages in the tree, by using estimated branch lengths. Although the original data are not independent between taxa, under a Brownian motion model of evolution, each contrast is independent of other contrasts calculated over the tree ( Harvey & Pagel 1991 ). To calculate size dimorphism in body mass, the independent contrasts of male mass were regressed on the contrasts of female mass. The slope of the regression through the origin was used to calculate the residuals for each species ( Purvis & Rambaut 1995a ). The relationships between mating system or nesting behaviour and male mass, female mass and size dimorphism were analysed separately using the brunch procedure in the caic program. This method is particularly appropriate if the main predictor is a categorical variable, when most of the statistical assumptions are violated if the data are analysed with normal independent contrasts analysis ( Harvey & Pagel 1991 ). With the brunch method, a reduced number of contrasts are calculated because of the way species data are used in this procedure ( Purvis & Rambaut 1995b ). Since no detailed information was available to estimate branch length for the whole Anseriformes phylogeny, unity branch lengths were used in all the analyses ( Purvis, Gittleman & Luh 1994 ).

Independent comparisons were used to analyse the relationship between sexual dichromatism and the number of sympatric species. The evolution of sexual dichromatism was reconstructed using the macclade program. Based on this reconstruction ( Fig. 1), we chose pairs of species formed by one species with and another without sexual dichromatism, with the only constraint being that both should pertain to the same tribe (in order to allow comparison of the sympatry index). Only one pair of species was constructed for each independent change in sexual dichromatism. The size of breeding ranges and the number of sympatric species were compared using paired t-tests (t) or Wilcoxon matched pairs signed rank tests (W) where data were not normally distributed. To investigate the relationship between the differences in number of sympatric species and size dimorphism, the same pairs of species were rearranged into two groups, containing the more size dimorphic (with larger males in relation to female size) and less dimorphic species of each pair, respectively.

Mean values ± SD are presented throughout the paper. To determine the extent to which our results were dependent on the phylogeny used, all the above analyses were repeated incorporating an alternative phylogeny for the tribe Anatini, based on molecular data ( Johnson & Sorenson 1999 ). Since the results of this second set of analyses did not differ from analyses performed with the morphologically based Livezey phylogeny, only results for the latter phylogeny are reported below, owing to the higher number of species included in this phylogeny. Additionally, all the analyses using traditional non-phylogenetic methods were repeated using species raw data. The results of these analyses have been discussed only when differing significantly from phylogenetic analyses. Details of these other analyses are available from the authors.

Our analyses are subjected to the biases resulting from a large number of extinctions of wildfowl species caused by human activities ( Green 1996 Young, Tonge & Hume 1997 ). Most of these were insular species with unknown degrees of sexual dimorphism. Likewise, anthropogenic factors have doubtless led to range modifications in many extant species, affecting our measures of sympatry.

Role of drift in evolution of sexually dimorphic traits - Biology

Publications for Derek Roff, UC Riverside

Roff, D. A. 1992. The Evolution of Life Histories: Theory and Analysis, Chapman and Hall, New York

Roff, D. A. 1997. Evolutionary Quantitative Genetics, Chapman and Hall, New York

Fox, C. W. , Roff, D. A. and Fairbairn, D. J. (eds) 2001 Evolutionary Ecology: Concepts and Case Studies, Oxford University Press, Oxford

Roff, D. A. 2002. Life History Evolution, Sinauer Associates, Sunderland, MA

Roff, D. A. 2006. Introduction to Computer-Intensive Methods of Data Analysis in Biology, Cambridge University Press, Cambridge


1. Roff, D.A. 1973. On the accuracy of some mark-recapture estimators. Oecologia 12:15-34.

2. Roff, D.A. 1973. An examination of some statistical tests used in the analysis of mark-recapture data.Oecologia 12:35-54.

3. Roff, D.A. 1974. A comment on the number of factors model of Reddingi¬us and den Boer. Am. Nat. 108:391-393.

4. Roff, D.A. 1974. Spatial heterogeneity and the persistence of popula¬tions. Oecologia 15:245-258.

5. Roff, D.A. 1974. The analysis of a population model demonstrating the importance of dispersal in a heterogeneous environment. Oecologia 15: 259-275.

6. Roff, D.A. 1975. Population stability and the evolution of dispersal in a heterogeneous environment. Oecologia 19:217-237.

7. Roff, D.A. 1976. Stabilizing selection in Drosophila melanogaster: A comment. J. Heredity 67:245-246.

8. Roff, D.A. 1977. Does body size evolve by quantum steps? Evol. Theory 3:149-153.

9. Roff, D.A. 1977. Dispersal in dipterans: its costs and consequences. J. Anim. Ecol. 46:443-456.

10. Roff, D.A. 1978. Size and survival in a stochastic environment. Oeco¬lo¬gia 36:163-172.

11. Roff, D.A. 1980. A motion for the retirement of the Von Bertalanffy function. Can. J. Fish. Aquat. Sci. 37: 127-129.

12. Roff, D.A. 1980. On defining the sufficient causes for natural se¬lection to occur. Evol. Theory 4:195-201.

13. Smith, J.N.M. and D.A. Roff. 1980. Temporal spacing of broods, brood size, and parental care in song sparrows (Melospiza melodia). Can. J. Zoology 58:1007-1015.

14. Fairbairn, D.J. and D.A. Roff. 1980. Testing genetic models of iso¬zyme variability without breeding data: can we depend upon the ?2. Can. J. Fish. Aquat. Sci. 37:1149-1159.

15. Roff, D.A. and D.J. Fairbairn. 1980. An evaluation of Gulland's method for fitting the Schaefer model. Can. J. Fish. Aquat. Sci. 37:1229-1235.

16. Roff, D.A. 1980. Optimizing development time in a seasonal environment: the "ups and downs" of clinal variation. Oecologia 45:202-208.

17. Roff, D.A. 1981. On being the right size. Am. Nat. 118: 405-422.

18. Roff, D.A. 1981. On estimating partial recruitment in virtual population analysis. Can. J. Fish. Aquat. Sci. 38:1003-1005.

19. Roff, D.A. 1981. Reproductive uncertainty and the evolution of iteroparity: why don't flatfish put all their eggs in one basket? Can. J. Fish. Aquat. Sci. 38:968-977.

20. Roff, D.A. 1982. Reproductive strategies in Flatfish: a first synthesis. Can. J. Fish. Aquat Sci. 39:1686-1698

21. Roff, D.A. and W.C. Bowen. 1982. Population dynamics and management of the northwest atlantic harp seal (Phoca groenlandica). Can. J. Fish. Aquat. Sci. 40:919-932.

22. Roff, D.A. 1983. Phenological adaptation in a seasonal environment: a theoretical perspective. In V.K. Brown and I. Hodek (eds.), "Diapause and life cycle strategies in insects". Dr. W. Junk Publish¬ers, The Hague.

23. Roff, D.A. 1983. A reply to Gavaris. Can. J. Fish. Aquat. Sci. 40: 384.

24. Roff, D.A. 1983. Development rates and the optimal body size in Drosophila: a reply to Ricklefs. Amer. Nat. 122:570-575.

25. Roff, D.A. 1983. Analysis of catch effort data: a comparison of three methods. Can. J. Fish. Aquat. Sci. 40:1496-1506.

26. Roff, D.A. 1983. An allocation model of growth and reproduction in fish. Can. J. Fish. Aquat. Sci. 40:1395-1404.

27. Roff, D.A. 1984. On the cost of being able to fly: a study of wing polymorphism in two species of crickets. Oecologia 63:30-37.

28. Roff, D.A. 1984. The evolution of life history parameters in teleosts. Can. J. Fish. Aquat. Sci. 41:984-1000.

29. Roff, D.A. 1986. The evolution of wing polymorphism and its impact on life cycle adaptation in insects. pp 209-221. In F. Taylor and R. Karban (eds.), "The Evolution of Insect Life Cycles". Springer-Verlag, New York.

30. Roff, D.A. 1986. The evolution of wing dimorphism in insects. Evolution 40:1009-1020.

31. Roff, D.A. 1986. The genetic basis of wing dimorphism in the sand crick¬et, Gryllus firmus and its relevance to the evolution of wing polymorphism in insects. Heredity 57:221-231.

32. Roff, D.A. and W.D. Bowen. 1986. A further analysis of population trends in the northwest Atlantic harpseal (Phoca groenlandica) from 1967-1983. Can. J. Fish. Aquat. Sci. 43:553-564.

33. Roff, D.A. 1986. Predicting body size with life history models. BioScience 36:316-323.

34. Lemon, R.E., S. Monette and D.A. Roff. 1986. Song repertoires of American warblers (Parulinae): honest advertising or assessment? Condor 87:457-470.

35. Roff, D.A. and T.A. Mousseau. 1987. Quantitative genetics and fitness: lessons from Drosophila. Heredity 58:103-118.

36. Heath, D. and D.A. Roff. 1987. A test of genetic differentiation in growth of stunted and non-stunted populations of perch and pumpkin¬seed. Transactions of the American Fisheries Society 116:98-102.

37. Mousseau, T.A. and D.A. Roff. 1987. Natural selection and the heritability of fitness components. Heredity 59:181-198.

38. Roff, D.A. 1988. The evolution of migration and life history in marine fish. Env. Biol. Fishes 22: 133-146.

39. Morin, A., T.A. Mousseau and D.A. Roff. 1988. Accuracy and precision of secondary production estimates. Limnol. Oceanogr. 32: 1342-1352.

40. Shackell, N.L., R.E. Lemon and D.A. Roff. 1988. Song similarity between neighboring American redstarts (Setophagaruticilla): a statis¬ti¬cal analy¬sis. Auk 105: 609-615.

41. Roff, D.A. 1989. Exaptation and the evolution of dealation in insects. Journal of Evolutionary Biology 2: 109-123.

42. Roff, D.A. and P. Bentzen. 1989. The statistical analysis of mitochondrial DNA polymorphisms: ?2 and the problem of small samples, Mol. Biol. Evol. 6:539-545.

43. Mousseau, T.A. and D.A. Roff. 1989. Geographic variability in the incidence and heritability of wing dimorphism in the striped ground cricket, Allonemobius fasciatus. Heredity 62:315-318.

44. Mousseau, T.A. and D.A. Roff. 1989 Adaptation to seasonality in a cricket: patterns of phenotypic and genotypic variation in body size and diapause expression along a cline in season length. Evolution 43: 1483-1496.

45. Roff, D.A. 1990. Understanding the evolution of insect life cycles: the role of genetical analysis. In, F. Gilbert (ed.), "Genetics, Evolution and Coordination of Insect Life Cycles". Springer Verlag, New York.

46. Roff, D.A. 1990. Antagonistic pleiotropy and the evolution of wing dimorphism in Gryllus firmus. Heredity 65:169-177.

47. Roff, D.A. 1990. The evolution of flightlessness in insects. Ecological Monographs 60:389-421.

48. Roff, D.A. 1990. Selection for changes in the incidence of wing dimorphism in Gryllus firmus. Heredity 65:163-168.

49. Fairbairn, D.J. and D.A. Roff. 1990. Evidence of genetic correlations among traits determining migratory tendency in the sand cricket Gryllus firmus. Evolution 44:1787-1795.

50. Roff, D.A. 1991. The evolution of life history variation in fishes with particular reference to flatfishes. Neth. J. Sea Res. 27:197-207.

51. Roff, D.A. 1991. Life history consequences of bioenergetic and biomechanical constraints on migration. American Zoologist 31:205-215

52. Roff, D.A. and D.J. Fairbairn. 1991. Wing dimorphisms and the evolution of migratory polymorphisms among the insects. Am. Zool. 31:243-251.

53. Duarte, C.M. and D.A. Roff. 1991. Architectural and life-history constraints to submersed macrophyte community structure. Aquat. Bot.. 42:15-29.

54. Roff, D.A. 1992. The evolution of alternative life histories: quantitative genetics and the evolution of wing dimorphism in insects. Bull. Soc. Pop. Ecol. 49: 28-35.

55. Roff, D.A. and P. Bentzen 1992. Detecting geographic subdivision: a comment on a paper by Hudson et al. (1992) Mol. Biol. Evol. 9:968.

56. Potvin, C. and D.A. Roff. 1993. Distribution-free and robust methods: viable alternatives to parametric statistics? Ecology 74:1617-1628.

57. Webb, K.L. and D.A. Roff. 1993. The quantitative genetics of sound production in Gryllus firmus. Animal Behaviour 44: 823-832.

58. Roff. D.A. and D.J. Fairbairn 1993. The evolution of alternate morphologies: fitness and wing morphology in male sand crickets. Evolution 47:1572-1584.

59. Bradford, M.J. and D.A. Roff 1993. Bet-hedging and phenotypic plasticity in the diapause strategies of the cricket Allonemobius fasciatus. Ecology 74:1129-1135.

60. Bradford, M.J., P.A. Guerette, and D.A. Roff. 1993. Testing hypotheses of adaptive variation in cricket ovipositor lengths. Oecologia 93:263-267.

61. Roff, D.A. and P. Shannon. 1993. Genetic and ontogenetic variation in behaviour: its possible role in the maintenance of genetic variation in the wing dimorphism of Gryllus firmus. Heredity 71:481-487.

62. Roff, D.A. 1994. Optimality modelling: assumptions and relationship to quantitative genetics. pp 49-66 In C. Boake and A.V. Hedrick (eds.), "Quantitative Genetic Studies of the Evolution of Behavior", University of Chicago Press.

63. Roff, D.A. 1994. The evolution of dimorphic traits: predicting the genetic correlation between environments. Genetics 136:395-401.

64. Roff, D.A. 1994. The evolution of dimorphic traits: effect of directional selection on heritability. Heredity 72: 36-41.

65. Simons, A.M. and D.A. Roff 1994. The effect of environmental variability on heritabilities of traits in a species of field cricket. Evolution 48:1637-1649.

66. Roff D.A. 1994. Habitat persistence and the evolution of wing dimorphism in insects. Am. Nat. 144: 772-798.

67. Roff, D.A. 1994. The evolution of flightlessness: is history important? Evol. Ecol. 8:639-657.

68. Roff, D.A. 1994. Evidence that the magnitude of the trade-off in a dichotomous trait is frequency-dependent. Evolution 48: 1650-1656.

69. Roff, D.A. and R. Preziosi. 1994. The estimation of the genetic correlation: the use of the jackknife. Heredity 73: 544-548.

70. Roff, D.A. 1994. Why is there so much genetic variation for wing dimorphism? Res. Popul. Ecol. 36: 145-150.

71. Carrière, Y., S.-P. Deland, D.A. Roff and C. Vincent. 1994. Life-history costs associated with the evolution of insecticide resistance. Proc. Roy. Soc. Lond. (B), 258: 35-40.

72. Roff, D.A. 1995 The estimation of genetic correlations from phenotypic correlations: a test of Cheverud's conjecture. Heredity 74:481-490.

73. Roff, D.A. 1995. Antagonistic and reinforcing pleiotropy: a study of differences in development time in wing dimorphic insects. J. Evol. Biol. 8: 405-419.

74. Bradford, M. J. and D. A. Roff. 1995. Genetic and phenotypic sources of life history variation along a cline in voltinism in the cricket Allonemobius socius. Oecologia 103: 319-326.

75. Carrière, Y. and D.A. Roff. 1995. The evolution of offspring size and number: a test of the Smith-Fretwell model in three species of crickets. Oecologia 102: 389-396.

76. Carrière, Y., D.A. Roff and J.-P. Deland. 1995. The joint evolution of diapause and insecticide resistance: a test of an optimality model. Ecology 76: 1497-1505.

77. Carrière, Y. and D.A. Roff. 1995. Change in genetic architecture resulting from the evolution of insecticide resistance: a theoretical and empirical analysis. Heredity 75: 618-629.

78. Mousseau, T. and D.A. Roff. 1995. Genetic and environmental contributions to geographic variation in the ovipositor length of a cricket. Ecology 76: 1473-1482.

79. Crnokrak, P. and D.A. Roff. 1995. Fitness differences associated with calling behaviour in the two wing morphs of male sand crickets Gryllus firmus Animal Behaviour 50: 1475-1481.

80. Crnokrak, P. and D.A. Roff. 1995. Dominance variance: associations with selection and fitness. Heredity 75: 530-540.

81. Carrière, Y., J.-P Deland and D. A. Roff. 1996. Oblique-banded leafroller (Lepidoptera: Tortricidae) resistance to insecticides: among orchard variation and cross-resistance. Journal of Economic Entomology 89: 577-582.

82. Heath, D.D. and D.A. Roff. 1996. The role of trophic bottlenecks in stunting: a field test of an allocation model of growth and reproduction in yellow perch (Perca flavescens). Environmental Biology of Fishes 45: 530-540.

83. Simons, A.M. and D.A. Roff. 1996. The effect of a variable environment on the genetic correlation structure in a field cricket. Evolution 50: 267-275.

84. Roff, D. A. 1996. The evolution of genetic correlations: an analysis of patterns. Evolution 50: 1392-1403.

85. Roff, D.A. 1996. The evolution of threshold traits in animals. Quart. Rev. Biol. 71: 3-35.

86. Roff, D.A. and M. Bradford. 1996. The quantitative genetics of the trade-off between fecundity and wing dimorphism in the cricket Allonemobius socius. Heredity 76: 178-185.

87. Carriere, Y., A. Simons and D. A. Roff. 1996. The effect of timing of post-diapause egg development on survival, growth, and body size in Gryllus pennsylvanicus. Oikos 75:463-470.

88. Weigensberg, I. and D. A. Roff. 1996. Natural heritabilities: can they be reliably estimated in the laboratory? Evolution 50:2149-2157.

89. Preziosi, R. F., D. J. Fairbairn, D. A. Roff and J. M. Brennan. 1996. Body size and fecundity in the waterstrider Aquarius remigis: a test of Darwin’s fecundity advantage hypothesis. Oecologia 108: 424-431.

90. Bradford, M. J. and D. A. Roff. 1997. An empirical model of diapause strategies of the cricket Allonemobius socius. Ecology 78: 442-451 .

91. Carrière, Y., S. Masaki and D. A. Roff. 1997. The coadaptation of female morphology and offspring size: a comparative analysis in crickets. Oecologia 110: 197-204.

92. Roff, D. A. and A. M. Simons. 1997. The quantitative genetics of wing dimorphism under laboratory and “field” conditions in the cricket Gryllus pennsylvanicus. Heredity 78: 235-240.

93. Roff, D. A., G. Stirling, and D. J. Fairbairn. 1997. The evolution of threshold traits: a quantitative genetic analysis of the physiological and life history correlates of wing dimorphism in the sand cricket. Evolution 51: 1910-1919.

94. Crnokrak, P., and D. A. Roff. 1998. The contingency of fitness: an analysis of food restriction on the macroptery-reproduction trade-off in Gryllus firmus. Anim. Behav. 56: 433-441.

95. Crnokrak, P., and D. A. Roff. 1998. The genetic basis of the trade-off between calling and wing morph in males of the cricket, Gryllus firmus. Evolution 52: 1111-1118.

96. Preziosi, R. F., and D. A. Roff. 1998. Evidence of genetic isolation between sexually monomorphic and sexually dimorphic traits in the water strider Aquarius remigis. Heredity 81: 92-99.

97. Roff, D. A. 1998. The detection and measurement of maternal effects. Maternal Effects as Adaptations. editors T. A. Mousseau and C. W. Fox, 83-96. Oxford: Oxford University Press.

98. Roff, D. A. 1998. Effects of inbreeding on morphological and life history traits of the sand cricket, Gryllus firmus. Heredity 81: 28-37.

99. Roff, D. A. 1998. Evolution of threshold traits: the balance between directional selection, drift and mutation. Heredity 80: 25-32.

100.Roff, D. A. 1998. The maintenance of phenotypic and genetic variation in threshold traits by frequency-dependent selection. Journal of Evolutionary Biology 11: 513-529.

101. Roff, D. A. 1998. Multiple entries in. The Encyclopedia of Ecology & Environmental Management. editor P. Calow. Oxford: Blackwell Science Ltd.

102. Simons, A. M., Y. Carriere, and D. A. Roff. 1998. The quantitative genetics of growth in a field cricket. J. Evol. Biol. 11: 721-734.

103. Weigensberg, I., Y. Carriere, and D. A. Roff. 1998. Effects of male genetic contribution and paternal investment on egg and hatchling size in the cricket Gryllus firmus. J. Evol. Biol. 11: 135-146.

104. Marschall, E. A., D. A. Roff, T. P. Quinn, J. A. Hutchings, N. B. Metcalfe, T. A. Bakke, R. L. Saunders, and L. Poff. 1998. A framework for understanding Atlantic salmon life history. Canadian Journal of Fisheries and Aquatic Sciences 55(suppl. 1): 48-58.

105. Roff, D. A. and M. J. Bradford 1998. The evolution of shape in the wing dimorphic cricket, Allonemobius socius. Heredity 80: 446-455.

106. Fox, C. W., M. E. Czesak, T. A. Mousseau, and D. A. Roff. 1999. The evolutionary genetics of an adaptive maternal effect: egg size plasticity in a seed beetle. Evolution 53: 552-560.

107. Roff, D. A., J. Tucker, G. Stirling, and D. J. Fairbairn. 1999. The evolution of threshold traits: effects of selection on fecundity and correlated response in wing dimorphism in the sand cricket. J. Evol. Biol. 12: 535-546.

108. Roff, D. A., and T. A. Mousseau. 1999. Does natural selection alter genetic architecture? An evaluation of quantitative genetic variation among populations of Allonemobius socius and A. fasciatus. J. Evol. Biol. 12: 361-369.

109. Roff, D. A., T. A. Mousseau, and D. J. Howard. 1999. Variation in genetic architecture of calling song among populations of Allonemobius socius, A. fasciatus and a hybrid population: drift or selection? Evolution 53: 216-224.

110. Stirling, G., D. A. Roff and D. J. Fairbairn. 1999. Four characters in a tradeoff: dissecting their phenotypic and genetic relations. Oecologia 120:492-498.

111. Roff, D. A. and D. J. Fairbairn. 1999. Predicting correlated responses in natural populations: changes in JHE activity in the Bermuda population of the sand cricket. Heredity 83: 440-450.

112. Crnokrak, P. and D. A. Roff. 1999. Inbreeding depression in the wild. Heredity 83: 260-270.

113. Derose, M. A. and D. A. Roff. 1999. A comparison of inbreeding depression in life history and morphological traits in animals. Evolution 53:1288-1292.

114. Stirling, G. and D. A. Roff. 2000. Behavioral plasticity without learning: phenotypic and genetic variation of naive Daphnia in an ecological tradeoff. Animal Behaviour 59: 929-941.

115. Roff, D. A. and M. J. Bradford. 2000. A quantitative genetic analysis of phenotypic plasticity of diapause induction in the cricket Allonemobius socius. Heredity 84: 193-200.

116. Roff, D. A. 2000. The evolution of the G matrix: selection or drift? Heredity 84: 135-142.

117. Crnokrak, P. and D. A. Roff. 2000. The trade-off to macroptery in the cricket Gryllus firmus: a path analysis in males. J. Evol. Biol. 13: 396-408.

118. Roff, D. A. 2000. Trade-offs between growth and reproduction: an analysis of the quantitative genetic evidence. J. Evol. Biol. 13: 434-445.

119. Stirling, G., D. J. Fairbairn, S. Jensen, D. A. Roff. 2001. Does a negative genetic correlation between wing morph and early fecundity imply a functional constraint in Gryllus firmus. Evol. Ecol. Res. 3: 157-177.

120. Roff, D. A. and D. J. Fairbairn. 2001. The genetic basis of migration and its consequences for the evolution of correlated traits. pp191-202 In C Clobert, J. Nichols, J. D. Danchin, and A. Dhondt (editors), Causes, consequences and mechanisms of dispersal at the individual, population and community level, Oxford University Press, Oxford.

121. Roff, D. A. and M. A. DeRose. 2001. The evolution of trade-offs: effects of inbreeding on fecundity relationships in the cricket Gryllus firmus. Evolution 55: 111-121.

122. Begin, M. and D. A. Roff. 2001. An analysis of G matrix variation in two closely related cricket species, Gryllus firmus and G. pennsylvanicus. J. Evol. Biol. 14: 1-13.

123. Roff, D. A. 2001. The threshold model as a general purpose normalizing transformation. Heredity 86: 404-411.

124. Reale, D. and D. A. Roff. 2001. Estimating genetic correlations in natural populations in the absence of pedigree information: accuracy and precision of the Lynch method. Evolution 55:1249-1255.

125. Roff, D. A., S. Mostowy and D. J. Fairbairn. 2002. The evolution of trade-offs: testing predictions on response to selection and environmental variation. Evolution 56:84-95.

126. Roff, D. A. 2002. Inbreeding depression: tests of the overdominance and partial dominance hypotheses. Evolution 56:768-775.

127. Crnokrak, P. and D. A. Roff. 2002. Trade-offs to flight capability in Gryllus firmus: the influence of whole-organism respiration rate on fitness. J. Evol. Biol. 15:388-398.

128. Stirling, D. G., D. Reale, and D. A. Roff. 2002. Selection, structure and the heritability of behaviour. Journal of Evolutionary Biology 15:277-289.

129. Roff, D. A. 2002. Comparing G matrices: a MANOVA method. Evolution 56:1286-1291.

130. Reale, D. and D. A. Roff. 2002. Quantitative genetics of oviposition behaviour and interactions between oviposition traits in the sand cricket. Animal Behaviour 64: 397-406.

131. Begin, M., and D. A. Roff. 2002. The common quantitative genetic basis of wing morphology and diapause occurrence in the cricket Gryllus veletis. Heredity 89:473-479.

132. Reale, D., and D. A. Roff. 2003. Inbreeding, developmental stability and canalization in the sand cricket Gryllus firmus. Evolution, 57: 597-605.

133. Roff, D. A. 2003. The evolution of genetic architecture in M. Pigliucci and K. Preston, eds. The Evolutionary Biology of Complex Phenotypes. Oxford University Press, Oxford.

134. Roff, D. A., and M. B. Gelinas. 2003. Phenotypic plasticity and the evolution of trade-offs: the quantitative genetics of resource allocation in the wing dimorphic cricket, Gryllus firmus. J. Evol. Biol. 16: 55-63

135. Roff, D. A. and R. J. Roff 2003. Of rats and Maoris: A novel method for the analysis of patterns of extinction in the New Zealand avifauna prior to European contact. Evolutionary Ecology Research 5: 1-21.

136. Roff, D. A., P. Crnokrak, and D. J. Fairbairn. 2003. The evolution of trade-offs: geographic variation in call duration and flight ability in the sand cricket, Gryllus firmus. Journal of Evolutionary Biology. 16:744-753

137. Begin, M., and D. A. Roff. 2003. The constancy of the G matrix through species divergence and the effects of quantitative genetic constraints on phenotypic evolution: a case study in crickets. Evolution 57:597-605.

138. Roff, D. A. 2003. Evolutionary quantitative genetics: Are we in danger of throwing out the baby with the bathwater? Ann. Zool. Fennici 40:315-320.

139. Roff, D. A. 2003. Evolutionary danger for rainforest species. Science 301:58-59. (Perspectives section)

141. Roff, D. A. 2004. The evolution of genetic architecture, In: Phenotypic Integration (Pigliucci, M. &Preston, K. ed), pp. 345-365. Oxford University Press, Oxford.

142. Roff, D. A., Mousseau, T., Møller, A. P., Lope, F. d. & Saino, N. 2004. Geographic variation in the G matrices of wild populations of the barn swallow. Heredity 93: 8-14.

143. Roff, D. A. & Reale, D. 2004. The quantitative genetics of fluctuating asymmetry: a comparison of two models. Evolution 58: 47-58.

144. Roff, D. A. & Sokolovska, N. 2004. Extra-nuclear effects on growth and development in the sand cricket, Gryllus firmus. J. Evol. Biol. 17: 663-671.

145. Reznick David, N., Bryant, M. J., Roff, D. A., Ghalambor, C. K. & Ghalambor, D. E. 2004. Effect of extrinsic mortality on the evolution of senescence in guppies. Nature 1095-1099

146. Fox, C. W., Bush, M. L., Roff, D. A. & Wallin, W. G. 2004. The evolutionary genetics of lifespan and mortality rates in two populations of the seed beetle, Callosobruchus maculatus. Heredity 92: 170-181.

147. Begin, M., Roff, D. A. & Debat, V. 2004. The effect of temperature and wing morphology on quantitative genetic variation in the cricket Gryllus firmus, with an appendix examining the statistical properties of the Jackknife-manova method of matrix comparison. J. Evol. Biol. 17: 1255-1267.

148. Begin, M. & Roff, D. A. 2004. From micro- to macroevolution through quantitative genetic variation: Positive evidence from field crickets. Evolution 58: 2287-2304.

149. Nespolo, R. F., Castaneda, L. E. & Roff, D. A. 2005. The effect of fasting on activity and resting metabolism in the sand cricket, Gryllus firmus: a multivariate approach. J. Insect Physiol. 51: 61-66.

150. Davidowitz, G., Roff, D. A. & Nijhout, H. 2005. A physiological perspective on the response of body size and development time to simultaneous directional selection. Integrative and Comparative Biology 45: 525-531

151. Roff, D. A. 2004 Variation and life history evolution. In Variation (ed. B. Hallgrimsson & B. K. Hall), pp. 333-355. New York: Elsevier Academic Press.

152. Rantala, M. J. & Roff, D. A. 2005 (in press). An analysis of trade-offs in immune function, body size and development time in the Mediterranean Field Cricket, Gryllus bimaculatus. Functional Ecology

153 Nespolo, R. F., Castaneda, L. E. & Roff, D. A. 2005 (in press) Dissecting the variance-covariance structure in insect physiology: The multivariate association between metabolism and morphology in the nymphs of the sand cricket (Gryllus firmus). Journal of Insect Physiology.

154. Roff, D. A., Remeš, V. & Martin, G. M. 2005. The evolution of fledging age in songbirds. Journal of Evolutionary Biology 18: 1425-1433.

155. Roff, D. A. & Mousseau, T. A. 2005 The evolution of the phenotypic covariance matrix: Evidence for selection and drift in Melanoplus. Journal of Evolutionary Biology 18, 1104-1114.

156. Roff, D. A. 2006 (in press). Introduction to Computer-Intensive Methods of Data Analyis in Biology. Cambridge University Press, Cambridge.

157. Rantala, M. J. & Roff, D. A. 2005 An analysis of trade-offs in immune function, body size and development time in the Mediterranean Field Cricket, Gryllus bimaculatus. Functional Ecology 19, 323-330.


The evolution of exaggerated morphological traits in animals is a topic that has captured the interest of biologists for centuries [ 1 , 2 ]. Sexual selection can lead to the rapid evolution of exaggerated traits via two mechanisms: intersexual selection by female choice (for example, peacock's tail) or intrasexual selection by male–male competition (for example, male deer antlers) [ 3 ]. The theoretical framework on the roles of sexual selection on the evolution of sexually dimorphic traits has been extensively studied since Darwin first proposed sexual selection as the second force of evolution [ 1 , 3 ]. In contrast, knowledge on the molecular mechanisms underlying the evolution of sexually dimorphic traits by sexual selection is rather limited. To address this topic, we investigated beetle horns one of the best examples of exaggerated traits evolved via intrasexual selection [ 1 ]. To our knowledge, hornedness has been independently acquired in at least 13 families of Coleoptera. The number and location of beetle horns varies and horn morphology shows a diverse range of shapes and sizes. These traits are largely male specific, as horns are used as weapons in male–male combat [ 4 ].

How novelties arise and how similar structures are created independently remain central questions in evolutionary developmental biology. Sexually dimorphic beetle horns provide an ideal opportunity to address these questions: they are an evolutionary novelty that is not homologous to any existing trait and have arisen independently in many taxa. Because beetle horns are sexually dimorphic, it is logical to assume that sex-determination genes are involved in the evolution of this novelty. The developmental genetic mechanisms underlying sexual dimorphisms have been well studied in various animal taxa [ 5 , 6 ]. One of the key factors involved in sexual dimorphisms is the Doublesex/Mab-3 related (Dmrt) transcription factor family, which is evolutionarily conserved from worms (mab-3) to mammals (DMRT-1) [ 5 , 6 ]. The functions of Dmrt genes in somatic sexual dimorphism has diverged among taxa but is deeply conserved in gonad development across phyla [ 5 ].

In insects, the bottom downstream gene in the sex-determination cascade is doublesex (dsx) [ 7 ]. Sex-specific alternative splicings produce male- and female-specific isoforms. Both Dsx isoforms share a common zinc finger-like DNA-binding motif called the DM domain and act as transcription factors to control all aspects of sex-specific morphologies. Therefore, dsx is key to understanding how sexually dimorphic morphologies in insects are acquired during evolution. The roles of dsx on the evolution of sexual dimorphisms such as male-specific sex combs and abdominal pigmentation, and the female-specific sex pheromone-producing enzyme in Drosophila have been well studied [ 8–12 ]. These studies have revealed general principles for the evolution of novel sex-specific traits, namely, cis-regulatory changes in dsx regulation that affect the expression domain of dsx, and modifications of Dsx-binding sites in downstream dsx target genes [ 5 , 8 , 11 ]. Functional studies on dsx have demonstrated that dsx modifies sexually monomorphic pre-existing structures, thereby creating sexual dimorphisms [ 13 , 14 ]. However, little is known about the roles of dsx in the development of evolutionary novelty. Recently, Kijimoto et al [ 15 ] have shown that dsx has a crucial role in morph-, sex- and species-specific development of horns in Onthophagus (Coleoptera, Scarabaeidae, Scarabaeinae).

To gain further insights into the evolution of exaggerated horns, we studied the Japanese rhinoceros beetle (Trypoxylus dichotomus Coleoptera, Scarabaeidae, Dynastinae), which has sexually dimorphic exaggerated horns on the head and prothorax (Fig 1) and has acquired horns independently from Onthophagus. These male-specific structures develop from horn primordia that arise during the prepupal larval stage (Fig 1A,C). Behavioural studies have revealed that they are used as weapons in male–male combat for access to female [ 16 ]. Therefore, intrasexual selection by male–male competition drives the evolution of the horns of T. dichotomus.

We focused on dsx to understand male-specific horn formation in T. dichotomus and examined its function using RNA interference (RNAi). In Drosophila, loss-of-function of dsx resulted in two distinct intersexual phenotypes, namely an intermediate phenotype between male and female as is the case for sex combs, or a male-like phenotype as seen in abdominal pigmentation and segment number [ 13 , 14 ]. In Onthophagus, dsx RNAi resulted in an intersexual phenotype in both sexes, involving reduction of horn size in the horned sex and induction of horn development in the hornless sex [ 15 ]. Thus, there are three possibilities for the dsx RNAi phenotype concerning horn formation in T. dichotomus. (1) If both male and female dsx isoforms have a function in horn formation (antagonistic), an intermediate sized horn is expected to develop in both sexes. (2) If only the male dsx isoform has a function in horn formation (induction), a hornless male dsx RNAi phenotype similar to the wild-type female phenotype is expected. (3) If only the female dsx isoform has a function in horn formation (repression), a horn similar to the male wild-type horn is expected to appear in the female dsx RNAi phenotype. To our surprise, we found that the sex-specific isoforms of dsx have different regulatory functions for the head and prothoracic horns.

13.2 Every body is different.

Humans come in a variety of shades, sizes and proportions, yet in total, our bodies are more similar to each other than they are different. In fact the human body shares similarities with bodies across the diversity of life. We share aspects of our reproductive system with all mammals, aspects of our basic physiology with all vertebrates, and aspects of our cell structure, biochemistry and genetics with all living things. In this chapter we will look at the human body specifically, not because the human body in terms of reproduction is very distinct from that of a 3-toed sloth, or because the basic structure is very different from a Galápagos tortoise, or because our cellular biology varies much from that of the fungus that inhabits bleu cheese. Instead we focus on the human body because the authors and readers of this text presumably each have a human body, and reading about ourselves is interesting.

Humans are sexually dimorphic

Like lions, peafowl, and marine iguanas, male and female humans are often superficially different in appearance (e.g. male hair patterns, female breasts), sounds (men typically have deeper voices), and smells (males and females have characteristic odors) this phenomenon is called sexual dimorphism and is observed in contrast to sexually monomorphic species (e.g. Laysan albatrosses, and emperor penguins see chapter 7 for further discussion of sexual dimorphism) in which males and females are difficult for humans to distinguish.

Further, there are generalizable differences between males and females in terms of reproductive organs, circulating hormones, and secondary sex characteristics. Secondary sex characteristics are traits that become more pronounced during puberty they are generally distinct between males and females, but they are not directly reproductive (i.e., they are not primary sex characteristics). Examples of secondary sex characteristics include breast development in females and thickening of vocal chords in males. While these generalizable traits are different on average between the sexes, there is wide variation in male and female anatomy and physiology, such that there is significant overlap in many of the traits. For example human males, on average, are taller than females. However there is quite a bit of overlap between the height ranges of males and female (see figure below).

Figure 13.1 Average height for males and females in the United States.

Humans have specialized organs that aid in reproduction (primary sex characteristics). Some of these are located between the ears, some of these are located in the abdomen and some of these are located between the legs. The body orchestrates the functions of reproductive organs through small signaling molecules called hormones that circulate in the bloodstream. The endocrine system involves hormones that are secreted from glands in one area of the body and have an effect at one or more distant locations. The development of secondary sex characteristics and the maturation of the reproductive organs happen in response to increases in circulating hormones (primarily estrogen, progesterone and testosterone) that occurs during adolescence.


  1. Jukasa

    Of course. I subscribe to all of the above.

  2. Baxter

    Thank you very much, cool creatively written

  3. Kurt

    Thank you, useful thing.

  4. Nishura

    Many thanks for the help in this question, now I will not commit such error.

Write a message