CAN ONE PREDICT THE EVOLUTION OF QUANTITATIVE CHARACTERS WITHOUT GENETICS

When natural selection or genetic drift acts on a group of characters, the rate and direction of their evolution is determined by their genetic variances and covariances. Estimating these quantities has therefore become a major goal of evolutionary quantitative geneticists. This task is often very difficult because it requires data on a large number of individuals of known ancestry. Estimating phenotypic variances and covariances, on the other hand, is much easier because it requires no information about ancestry. In addition, for a given sample size, estimates of phenotypic parameters are less subject to sampling error than are additive-genetic ones. Because reliable estimates of quantitative genetic parameters are difficult or impossible to obtain for many species, it is important to know whether phenotypic parameters are similar to genetic ones. If phenotypic and genetic parameters are quite similar in general, then perhaps phenotypic parameters could be substituted for genetic ones in evolutionary models and evolutionary inferences could be made in a wide range of species. This observation motivated Cheverud (1988) to investigate the relationship between genetic and phenotypic correlation matrices from 41 empirical studies. He concluded that "phenotypic correlations are likely to be fair estimates of their genetic counterparts in many situations" (p. 958). This similarity led him to propose that a matrix of additive-genetic covariances in a population might be estimated by multiplying its matrix of phenotypic covariances by a constant factor equal to the average heritability of the traits. He noted that although the method "will certainly lead to errors in evolutionary inference in specific instances" (p. 965), it may be especially useful in rare, hard-to-breed, or extinct species for which quantitative genetic data are lacking. Cheverud concludes that, "when reliable genetic estimates are unavailable, phenotypic correlations and scaled variances may be substituted for their genetic counterparts in evolutionary models of phenotypic evolution" (p. 966). Cheverud's paper is valuable in emphasizing the great difficulty of estimating genetic parameters and in showing how comparisons of genetic and phenotypic correlations can increase our understanding of morphological integration and the evolution of development. We do not, however, agree with his suggestions that phenotypic variances and correlations are similar to genetic ones and that they therefore may be used in quantitative genetic models of evolution. Reexamining the data that Cheverud used to support his conclusions, we find that the data sets he analyzed have peculiarities that may make them unrepresentative of data from natural populations. In addition, we find several difficulties with the statistical analysis that led Cheverud to conclude that phenotypic correlations reflect genetic correlations. We find that although there are great difficulties in accurately estimating additivegenetic covariances, methods based only on phenotypic correlations are not reliable substitutes. Difficulties with the Data. -The data used by Cheverud do not permit the conclusion that genetic and phenotypic patterns of variation in nature are similar. First, nearly all of the data (at least 36 out of the 41 studies) are based on populations reared under laboratory or agricultural conditions. Such rearing in controlled environments imposes on populations an artificial constancy of environment and diet. This minimizes sources of environmental variation that can greatly weaken the similarity between genetic and phenotypic correlations. In Drosophila, for example, the phenotypic variance of body size in wild-caught flies can be up to eight times larger than that of laboratory-raised flies (McFarquhar and Robertson, 1963; David et al., 1980; Coyne and Beecham, 1987), probably because of the great variation in the quantity and quality of larval food in nature. The effect of environmental constancy on the relationship among the phenotypic, genetic, and environmental correlations for a pair of traits may be seen in the equation: