Conspicuous sexual dimorphism is a feature of many species of higher animals. The genetic basis of variation in metrical characters, including that in sexual dimorphism between families or lines, is usually polygenic (Falconer, 1960; Frankham, 1968b; Wright, 1968, 1977; Bird and Schaffer, 1972; Ehrman and Parsons, 1976). Genetic experiments on mice, birds and Drosophila flies indicate that artificial selection practiced on a character of one sex causes not only a direct response of the character in the selected sex, but also a correlated response of the homologous character, if any, in the opposite sex (Shaklee et al., 1952; Harrison, 1953; Korkman, 1957; Becker et al., 1964; Eisen and Legates, 1966; Frankham, 1968a, 1968b; Eisen and Hanrahan, 1972). Such correlated selective responses are attributable to pleiotropy (and linkage) of genes affecting the characters of both sexes, that is, correlations between the additive effects of genes as expressed in males and females. The genetic correlation between homologous characters of the sexes is often quite high (op. cit.). As will be shown, this greatly restricts the rate of evolution of sexual dimorphism relative to that for the average phenotype of the two sexes. Sexual dimorphism may result from natural and/or sexual selection. Darwin (1874, Part 2) elucidated how natural selection operating differently on males and females arises from their distinctive roles in reproduction, or from competition between the sexes for resources such as food, leading to adaptive sexual dimorphism. He also reasoned that intrasexual contests for mates and intersexual mating preferences exert sexual selection, usually on the males, producing sexual dimorphism which is maladaptive with respect to natural selection. Comparisons within and between closely related species led Darwin to conclude that adult males typically are more modified than adult females or juveniles of either sex, but that females have often acquired male characters by "transference." It was difficult for Darwin to believe that sex-limitation of characters could evolve by selection, but Fisher (1958, Ch. 6) outlined how divergent selection on the two sexes could accumulate genes with different effects in males and females, causing a character at first expressed equally in both sexes to become sexually dimorphic and finally sex-limited. The strength of sexual selection is enhanced by a polygamous mating system, but the possibility of sexual selection in monogamous systems of mating exists due to male competition for early-breeding females, and mate choice exercised by these females (Darwin, 1874; Fisher, 1958; O'Donald, 1977). Systems of mating are often thought to evolve in response to ecological pressures (reviewed by Selander, 1972; Brown, 1975; Emlen and Oring, 1977), although mating preferences may be self-reinforcing (Fisher, 1958; O'Donald, 1967, 1977; Lande, unpubl.). Darwin and Fisher described qualitative methods by which an observed sexual dimorphism could be attributed mainly to either natural or sexual selection. To assign natural selection as the primary cause requires ecological observations that males and females follow different ways of life and employ the dimorphic character(s) adaptively in their distinct modes of survival or reproduction. Darwin presented several such examples, mostly among the lower classes of animals. Selander (1972) 292

https://onlinelibrary.wiley.com/doi/pdf/10.1111/j.1558-5646.1980.tb04817.x

Evolution and the genetics of populations. Vol. 1. Genetic and biométrie foundations.

Sexual dimorphism, sexual selection, and adaptation in polygenic characters.

The past explains the present: Emotional adaptations and the structure of ancestral environments

Molecular genetics can be integrated with traditional methods of artificial selection on phenotypes by applying marker-assisted selection (MAS). We derive selection indices that maximize the rate of improvement in quantitative characters under different schemes of MAS combining information on molecular genetic polymorphisms (marker loci) with data on phenotypic variation among individuals (and their relatives). We also analyze statistical limitations on the efficiency of MAS, including the detectability of associations between marker loci and quantitative trait loci, and sampling errors in estimating the weighting coefficients in the selection index. The efficiency of artificial selection can be increased substantially using MAS following hybridization of selected lines. This requires initially scoring genotypes at a few hundred molecular marker loci, as well as phenotypic traits, on a few hundred to a few thousand individuals; the number of marker loci scored can be greatly reduced in later generations. The increase in selection efficiency from the use of marker loci, and the sample sizes necessary to achieve them, depend on the genetic parameters and the selection scheme.

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Efficiency of marker-assisted selection in the improvement of quantitative traits.

Part I. A Beginning: 1. Introduction 2. Illustration of structural equation modeling with observed variables: the temporal dynamics of a plant-insect interaction Part II. Basic Principles of Structural Equation Modeling: 3. The anatomy of structural equation models I: overview and observed variable models 4. The anatomy of structural equation models II: latent variables 5. Principles of estimation and model assessment Part III. Advanced Topics: 6. Composite variables and their use in representing concepts 7. Additional techniques for complex situations Part IV. Applications and Illustrations: 8. Model evaluation in practice 9. Multivariate experiments 10. The systematic application of a multivariate perspective to understanding plant diversity patterns in ecological communities 11. Cautions and recommendations for the application of SEM Part V. The Implications of Structural Equation Modeling for the Study of Natural Systems: 12. How can structural equation modeling contribute to the advancement of the natural sciences? 13. Tuning in to nature's symphony: frontiers in the study of multivariate relations Appendix I. Example analyses References.

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Structural Equation Modeling and Natural Systems

In this paper, we use measures of selection developed by quantitative geneticists and some new results (Arnold and Wade, 1984) to analyze multiple episodes of selection in natural populations of amphibians, reptiles, and insects. These examples show how different methods of data collection influence the potential for relating field observations to formal evolutionary theory. We adhere to the Darwinian tradition of distinguishing between natural and sexual selection (Darwin, 1859, 1871; Ghiselin, 1974). We view sexual selection as selection arising from variance in mating success and natural selection as arising from variance in other components of fitness. The justification for this formal distinction is developed by Wade (1979), Lande (1980), Wade and Arnold (1980), Arnold and Houck (1982) and Arnold (1 983 a). (We define mating success as the number of mates that bear progeny given survival of the mating organsim to sexual maturity. We do not equate mating success with mere copulatory success.) The utility of the distinction between sexual and natural selection is that the two forms of selection may often act in opposite directions on particular characters (Darwin, 1859, 1871). While we find the distinction between these two forms of selection useful, the difference is not crucial to our analysis. The essential point is that the recognition of selection episodes permits analysis of selection that may change in magnitude and direction during the life cycle. Defining Fitness Components. -The key first step in the analysis of data is to define multiplicative components of fitness so that selection can be partitioned into parts corresponding to these components or episodes of selection. Using an animal example, if the number of offspring zygotes is taken as total fitness, we can define the following components of fitness: viability (survivorship to sexual maturity), mating success (the number of mates) and fertility per mate (the average number of zygotes produced per mate). These components of fitness are defined so that their product gives total fitness. As a second example, consider the components of fitness in a plant in which yield (seeds/plant) is taken as the measure of total fitness (Primack and Antonovics, 1981). We might define the following components of fitness: number of stems per plant, average number of inflorescences per stem, average number of seed capsules per inflorescence, and average number of seeds per capsule. Again, these four fitness components are defined so that their product gives total fitness. We will need to measure each component of fitness and each character on each individual in order to partition selection into parts corresponding to the separate episodes of selection or to the separate components of fitness. Thus in the animal example, we need to measure the viability, mating success and fertility of each individual. With this accomplished we can estimate the separate forces of viability, sexual and fertility selection on each phenotypic character. In addition we can calculate the opportunities of selection corresponding to these three episodes and covariances between the different kinds of selection. In the plant example, we might begin with the intuition that larger plants have a greater yield. Using our methodology we can reword and extend this intuition. We can not only test the proposition of

https://onlinelibrary.wiley.com/doi/pdf/10.1111/j.1558-5646.1984.tb00345.x

Evolution and the genetics of populations. Vol. 1. Genetic and biométrie foundations.

Citations

Sexual dimorphism, sexual selection, and adaptation in polygenic characters.

The past explains the present: Emotional adaptations and the structure of ancestral environments

Efficiency of marker-assisted selection in the improvement of quantitative traits.

Structural Equation Modeling and Natural Systems

On the measurement of natural and sexual selection: applications.

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