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J. Evol. Biol. 8: 759 778 (1995) 1010 06lX/95/0607S9%20 ;v> 1995 Birkhauser $ 1.50 +0.20/O Verlag, Base1 Good genes and old age: Do old mates provide superior genes? T. F. Hansen’ and D. K. Price2 ‘Division of Zoology, Depurtment of Biology, University of Oslo, P.O. Box 1050, Blindern, N-0316, Oslo, Norwuy ‘Department of Biology, University of Oregon, Eugene, OR 97403, USA Key wordy: Mate choice; sexual selection; age; age-structured selection; fitness. Abstract It has been suggested that female preference for older mates in species without parental care has evolved in response to an alleged higher genetic quality of older individuals. This is based on the widespread assumption that viability selection produces older individuals that are genetically superior to younger individuals. In contrast, we propose that the oldest individuals rarely are genetically superior. Quantitative genetic models of life history evolution indicate that young to intermediately aged individuals are likely to possess the highest breeding values of fitness. This conclusion is based on four arguments: 1) Viability selection on older individuals may decrease or at least not substantially increase breeding values of fitness, because there may exist negative genetic correlations between late-age and early-age life history parameters, 2) Fertility selection is likely to raise the fitness of gametes produced by young individuals more than those produced by old individuals, because the covariance between fertility and fitness often decreases with age, 3) The history of selection on their parents makes younger individuals more fit than older individuals, 4) Germ-line mutations, which are generally deleterious, significantly decrease the breeding value of fitness of an individual throughout its lifespan, especially in males. Therefore, females that mate with the oldest males in a population are doing so for reasons other than to obtain offspring of high genetic quality. ’ Author for correspondence. ’ Current address: Department of Biological 75429 301 I, USA. The contributions from the authors arc equal. Sciences, 159 East Texas State University, Commerce, TX 760 Hansen and Price Introduction Numerous examples have been reported in which females prefer to mate with older males. By doing so, females of many species may obtain direct benefits through the superior paternal care provided by older males (Burley and Moran, 1979; Yasakawa, 1981; Price, 1984; Grant and Grant, 1987; Komers and Dhindsa, 1989; Buchholz, 1991; Coti: and Hunte, 1993). However, in species where males do not provide such benefits, females may choose older males to obtain offspring of higher genetic quality. This has been suggested for species with no paternal care (Davison, 1981; Manning, 1987, 1989; Zuk, 1987, 1988; Simmons, 1988; Stidel et al., 1991; Simmons and Zuk, 1992; Vandenberghe et al., 1993), for species in which males do not provide care to offspring of secondary females (Jarvi et al., 1982; Weatherhead, 1984) and in cases of extra pair copulation (Moller, 1992). Two evolutionary mechanisms have been proposed to explain female preferences for male traits that do not provide females with direct benefits. Fisherian sexual selection models predict that female preference may become genetically correlated with an attractive male trait and that this can lead to an increase in both traits (Fisher, 1958; Lande, 1981). In this case, the male trait is not necessarily correlated with any aspect of viability. On the other hand, good-genes sexual selection models predict that the male trait is genetically correlated with some aspect of fitness, and female preference for the trait can increase through the greater offspring survival produced by mating with attractive males (Kodric-Brown and Brown, 1984; Andersson, 1986; Pomiankowski, 1988). Female preference for older males has been proposed to evolve through this second mechanism (Trivers, 1972; Halliday, 1978, 1983; Alcock, 1984; Manning, 1985; Heisler et al., 1987; Kirkpatrick, 1987; Andersson, 1994). The potential to increase offspring genetic quality through mate choice based on age depends critically on some mechanism that maintains a genetic correlation between age and fitness. Male age has been proposed to maintain a positive genetic correlation with viability because older males have survived more episodes of viability selection (Trivers, 1972; Halliday, 1978). Manning ( 1985) suggested that deleterious mutations that enter the population at the zygote stage may maintain genetic variation for viability. As males age, the individuals with more deleterious mutations will die, leaving a cohort of older males with fewer deleterious mutations, on average, than in cohorts of younger males. The input of new mutations every generation coupled with directional selection on viability could maintain a positive correlation between age and genetic quality. All that would be required is for females to assess male age accurately through a trait that is reliably correlated with age (Heisler et al., 1987). In this way, female preference for older males would indirectly increase the genetic quality of their offspring. There are several modifications of this hypothesis that may alter the general conclusion that older males are genetically superior. First, it is important to recognize that viability, especially at older ages, is not necessarily strongly or positively correlated with total fitness. Genes that increase viability at an old age may have negative effects on early age viability and fertility. Good genes and old age 761 As viability and fertility at early ages are likely to represent a large proportion of fitness, it is possible that viability selection among old males may actually reduce fitness. Second, unlike viability selection, the effects of fertility selection do not accumulate with age. Fertility selection among young individuals acts directly on an important fitness component while fertility selection among old individuals acts on a less important fitness component that may even be negatively correlated with total fitness. This may elevate the breeding values for fitness of successful gametes from young individuals as compared to those from older individuals. Third, if the mean population fitness is increasing, younger individuals are born from parents of higher genetic quality, on average, than older individuals. An evolving mean fitness could result from ongoing adaptation to a changing biotic or abiotic environment or through soft selection within the population (e.g., Fisher, 1958). Fourth, it is now recognized that most new mutations enter the population during mitotic cell division in the germ-line (Crow, 1993). As these mutations do not affect the phenotype of the individual carrying them, they are invisible to selection. In male animals where division of the germ-line extends throughout life, mutations accumulate with age and steadily decrease the genetic quality of gametes produced. As most mutations occur in males (e.g., Shimmin et al., 1993) and may decrease fitness substantially in one generation, this harbors substantial potential for mate choice based on youth. Furthermore, these germ-line mutations cannot be detected by the female except through the age of the male. In this paper, we assess the influence of these four factors on the breeding value of fitness as a function of age. Our goal is to obtain some rough guidelines for the age at which surviving individuals have the highest breeding value of fitness under various life histories. In contradiction to widely held beliefs, our conclusion is that old individuals rarely have the best genes. Our discussion relates this observation to theories of mate choice and sexual selection. We further make a call for more empirical studies. Although there exists an enormous literature on the effects of age on phenotypic fitness, there is little data on how the genetic values of fitness components vary with age. Changes in mean fitness with age due to selection Model We consider a discrete time age- and sex-structured model where the zygotes are in age class zero. To study evolution we allow the age- and sex-specific demographic parameters to be genetically variable quantitative traits. Let PI:’ and P{, be the expected probability of survival from age class a to a + 1 for individual males, m, and females, f; respectively. Let Fr and F/, be the expected fertilities, measured in number of successful gametes, of individual males and females, respectively, of age a. These P’s and F’s are random variables, in the sense that they differ among 762 Hansen and Price individuals, and the demography of the population is determined by their population averages. These population averages are necessarily density dependent as the summed fertility of females must equal the summed fertility of males (Caswell, 1989, chp. 10). Density dependent population regulation does not influence our results if we assume either density independent selection or a stationary population. The trait at the focus of our study is fitness, II’. As we aim to study mate choice based on good genes, we are interested in the genetic value that is transferable to the offspring. In quantitative genetics this transferable genetic value is called the breeding value (e.g., Falconer, 1989). We define the breeding value of fitness, W,, as half its additive genetic component. In the absence of additive x additive forms of epistasis this is what is transferred to the offspring and hence the genetic value of males relevant for a choosing female. We assume that total fitness can be written as a sum of the additive effect and an independent residual effect that contains nonadditive genetic and environmental components. We further assume autosomal inheritance so that the distribution of genetic values is the same in male and female zygotes. A precise definition of fitness is given below. For now, it is only necessary to bear in mind that fitness is a function of all the age- and sex-specific viabilities and fertilities (i.e., all the P’s and F’s). Viability selection within a cohort is formally equivalent to selection by differential death in an asexual organism. In addition we consider fertility selection due to differential gamete production within the cohort. This includes selection due to differential mating success caused by inter- and intra-specific sexual selection. We consider a cohort of males; a parallel argument can be developed for females. We describe selection with Price’s ( 1970, 1972a) covariance formulation. The change in mean breeding value for fitness, indeed any trait, of a cohort of males from zygote to gametes produced at an age, a, due to selection only is where ~1:’ = F;. Py....P::‘m,, the fertility at age a times the probability of corresponding to selection from surviving to that age, is the age-specific “fitness” zygote to gametes produced at age a. These age-specific fitnesses must not be confused with total fitness, W, which is a function of all the demographic parameters including those expressed in females. The symbols E,[ ‘1, and Cou,[ , ‘1, denote the expectation and covariance taken in age class u at time t. The covariance here and in the following are additive genetic covariances. Hence, E,[W,l is the expected breeding value of fitness for gametes produced by males at age u. Equation (1) shows how gametes produced at different ages have been through different selection regimes, as the age-specific fitnesses, w;, of older cohorts include more age-specific survival parameters and a different fertility parameter. This is illustrated in Fig. 1. Equation (1) also illustrates how selection starts from genetic variation available among zygotes and that this may be different for cohorts born at different times. In this section, we shall assume that selection is weak or close to an equilibrium so that the covariance in (1) stays approximately constant within the Good 763 genes and old age Fig. I. The life cycle graph for one sex illustrates the model in the main text. Selection occurs during the transitions illustrated by arrows according to the given equation. The effect of selection over a series of transitions can be obtained either by considering the covariance with the product of the transition parameters along the transition as given by (I) in the main text, or by summing the effects of each transition as given by (3) in the main text. Total fitness (4) is a weighted average of “htnesses along all the possible pathways from zygote to zygote. Note that cohorts of different ages have been through different regimes of selection, and that even gametes produced by the oldest cohort have been selected along a pathway that is only a part of the total selective regime. time span of a generation. Accordingly, we drop time from the notation. We consider an effect of different times of birth later in the paper. At equilibrium the difference in mean fitness of gametes produced by adjacent age classes (such as 1 and 2 in Fig. 1) may be expressed as 4z+I [ WA - 4, [ WBI= Cw [EL;&,’ ~ f CO%+I WB - ] F:“, I -%+,F::I+,l’ wB r - cov,, F:: I E,[f$']' wB I ' (2) where the first term on the right expressesthe effects of viability selection due to survival from one age class to the next, and the last two terms express the difference between fertility selection in the two age classes(see Fig. 1). Viability selection in earlier age classescancels out, as this is the same for the two cohorts, and fertility selection at other agesis irrelevant. Considering a sum of such differences we arrive at a formula which, except from having time suppressedfrom the notation, can be shown to be equivalent to (1) 764 Hansen and Price This equation shows how the effects of viability selection accumulate with age while the effects of fertility selection do not. The above equations show that it is fully possible for selection to decrease the mean fitness of gametes in parts of the life span. For gamete fitness to decrease from one age class to the next, it is only necessary that (2) is negative. This may happen either because the breeding value for fitness is negatively correlated with the genetic value for survival between the age classes, or because the covariance of the breeding value for fitness with the genetic value for fertility decreases from one age class to the next. We argue below that gametic fitness tends to decrease at old age because fitness is strongly positively correlated with early survival and fertility and weakly negatively correlated with late survival and fertility. To make the above formulas more precise, we define fitness as (4) where Qj, is the proportion of the gamete pool produced by individuals of age u and sex s. Hence, total relative fitness is a weighted average of relative age- and sex-specific fitnesses where the weights are the proportional reproductive contributions of the age and sex classes. This is a reasonable definition of relative fitness under the assumptions that the age specific additive genetic covariances in (1) as well as transmission effects stay constant. Then, it can be shown that Was defined in (4) correctly predicts the change due to selection in the mean of an additive trait, x, among zygotes as 4&-4 +1- &bl, = Cov,[w, x] l+T . (5) where T = C~r.p~Q~,,is the mean age of parents. Abugov showed that (4) defines a selective gradient in a one locus, two allele model (Abugov, 1986) and in a quantitative genetic model (Abugov, 1988). Equation (4) is the two-sex generalization of standard age-specific fitness measures as in Hamilton ( 1966) and Charlesworth ( 1994). Commonly used fitness measures such as the intrinsic rate of increase and the life time reproductive success are derived as approximations of (4). We want to relate W to the age-specific survival and fertility parameters, P and F. The sensitivity of fitness to an age- and sex-specific parameter is defined as the derivative of fitness with respect to the parameter evaluated at the mean values of all the demographic parameters as (6b) Equation (6a) shows that the sensitivity of fitness to changes in the fertility of a specific age and sex class is proportional to the fraction of total reproduction provided by that class divided by its expected fertility; this simply equals the Good 765 genes and old age fraction of the total population that is in the class. Equation (6b) shows that the sensitivity to age- and sex-specific survival is roughly proportional to the ratio of expected future reproduction of the class divided by the fraction surviving into the next class. At the stable age and sex distribution, Q;, equals E,,[w~,]i. -‘I- ‘, where 1, is the growth rate of the population. Using this, it can be shown that the sensitivities in (6) reduce to the eigenvalue sensitivities discussed by Caswell ( 1989) for one sex class. Specifically, at the stable age and sex distribution, r?W/o’Flz = vi and a W/c?P:, = v;r:,, , , where v:! is the number of individuals of age u and sex s at the stable age and sex distribution measured in fraction of newborns of both sexes, and rfz is the reproductive value (i.e. expected future contribution to the zygote pool) of individuals of age u and sex s (as defined in Caswell, 1989). Through a first order Taylor expansion around the mean of the demographic parameters, we may approximate W, as a sensitivity weighted sum of the additive genetic values of the age- and sex-specific fertility and survival parameters. The covariances appearing in (2) and (3) may then be written as + f. &y Cov,[FZ’,F:l 2 I + i; iWCor:,,[P::‘, F;] ,=” i?F! , (7b) where the factor two comes from the breeding value being half the additive genetic value, and we have used the assumption that the additive genetic part of fitness is independent of the residual part. Equation (7a) shows how the additive genetic covariance of fitness with an age- and sex-specific fertility is decomposed into a sensitivity weighted sum of additive genetic covariances of that fertility with the survival and fertility at all age and sex classes.Equation (7b) establishesthe same for viabilities. These equations describe the effect of fitness sensitivities and patterns of genetic correlations on selection along single transitions in the life history graph in Fig. 1. We have now described how population parameters such as age- and sex-specific fitness sensitivities and genetic covariances can be used to predict the genetic quality of individuals of specified age and sex. In the next two sections we review what is known about patterns of fitness sensitivities and genetic covariances. Finally, we 766 Hansen and Price integrate this information with the theory to reach our conclusions regarding effects of selection on the age distribution of breeding values for fitness. The sensitivity qf’.fitness to uge- and sex-spec$c the variation The sensitivities (6) determine the magnitude of fitness change that would occur with a given change in a viability or fertility parameter. The aim in this section is to identify the age- and sex-specific parameters to which fitness is particularly sensitive. This will tell us which of the genetic covariances in (7) are important and which are not. As (6) demonstrates, fitness is most sensitive to variation in age and sex classes with large reproductive values and large numbers of individuals. If the population is growing, fitness is relatively more sensitive to parameters expressed at a young age. In the long run, this effect is counteracted by the increased sensitivity to old age parameters when the population inevitably declines. We will not attempt to discuss the effects of population oscillations here. Standard demographic theory (e.g., Caswell, 1989) shows that, in a stationary population, the number of individuals decreases geometrically with age. The rate of decrease equals the death rate. The reproductive value typically first increases and then decreases, achieving a maximum at or shortly after the onset of substantial reproduction. The decrease in number of individuals with age is directly translated into a decrease in the sensitivity to fertility with age. The sensitivity to survival is modulated by the reproductive value to the effect that it does not drop as fast before peak reproductive value, but thereafter it falls off much faster than the sensitivity to fertility. These effects should be properly scaled, as there may be large differences in potential for variation. There is, for example, no potential for selection on fertility in immature age classes. If fertility rises steeply with age, as is the case in some organisms, especially indeterminate growers, the reproductive value may not start to fall before late in life and fitness may remain sensitive to survival for a long time. Also, the decrease in sensitivity to fertility may be offset by the increased potential for variation. Excluding first attempts, most female birds and mammals do not show large increases in fecundity with age (Clutton-Brock, 1988; Newton, 1989; Roff, 1991). The sensitivity of fitness to female survival and fecundity will drop rapidly after maturation for these organisms. Estimates of fertility in males are less well known, and males may show more triangular patterns of reproduction where fertility increases to a certain age and then falls off (Clutton-Brock et al., 1988; Roff, 1991). This may be especially true in species with strong male-male competition. Examples include red deer, Cervus elqhus (Clutton-Brock et al., 1988) elephant seals, Miroungu angustirostris (Le Beouf and Reiter, 1988) and manakins, Chivoxiphiu linearis (McDonald, 1993). In these cases, sensitivities to male fitness components do not decrease rapidly before peak reproduction is reached. Insects, which have determinate growth, often show decreasing fecundity after maturation (Roff, 199 1) and thus an especially rapid decline in sensitivity of fitness to survival. Caswell ( 1989) reviewed empirical studies of fitness sensitivity from several organisms and Good 767 genes and old age showed that the sensitivity to both survival and fertility may decrease by orders of magnitude over the life span of an organism. In conclusion, excluding life histories with rapidly increasing fertility, the major components of fitness are survival from birth to onset of major reproduction as well as fertility in the early stages of reproduction. Fertility and especially survival of older individuals are clearly much less important fitness components. Using this information in (7) we see that the covariance between a demographic parameter and fitness is mainly determined by the covariance between the parameter and early male and female survival and fertility. Thus, to determine the power and direction of selection on fitness in a specific age and sex class, we need to determine the sign and magnitude of the covariance the corresponding age and sex specific parameters, P and F, have with early survival and fertility. Genetic correlations among age-spec$c jitness components There are both theoretical and empirical considerations that point to diminishing and negative correlations between early and late fitness components. One indication comes from the antagonistic pleiotropy theory of senescence, which postulates genes that are generally beneficial in young individuals but detrimental in old (Medawar, 1946; Williams, 1957). Similarly, evolutionary tradeoffs between early and late performance would introduce a component of negative covariance. Alternatively, senescence may be due to accumulation of alleles that are deleterious at old age but neutral at young age (Medawar, 1946). Such alleles would lead to a deterioration of genetic correlations between young and old components but not to negative correlations. Two recent reviews (Rose, 1991; Partridge & Barton, 1993) conclude that both kinds of alleles likely contribute to senescence but that the relative magnitudes are unknown. For our purposes the question is whether such genes are common enough to outweigh variation caused by unconditionally bad (or good) alleles that introduce positive covariances between all components. The empirical evidence for negative genetic correlations among demographic parameters expressed at different ages comes mostly from selection experiments in Drosophilu. A negative response of early female fertility to selection on longevity has been found in several experiments (Rose and ( z old age viability) Charlesworth, 1981a, 1981b; Luckinbill et al., 1984; Rose, 1984; Mueller, 1987). Similarly, selection on early (and late) female fertility has tended to produce negative responses in longevity (appendix 1b in Stearns, 1992). Evidence of negative genetic correlations between early and late female fertility have likewise been found in numerous selection experiments (appendix lb in Stearns, 1992). Service ( 1993) found evidence for negative genetic correlations in males between longevity and late mating success on one hand and early mating success on the other, but Roper et al. ( 1993) and Service and Fales ( 1993) did not find much evidence of genetic correlations in males. Roper et al. (1993) did not find correlations among female life history traits either. 768 Hansen and Price These selection experiments should be interpreted with some caution (Clark, 1987; Rose, 1991; Partridge and Barton, 1993). Firstly, it is possible that some of the response is due to the accumulation of age-specific deleterious mutations during the experiment. However, this effect is probably too small to account for the results (Service, 1993), and most spontaneous deleterious mutations may not be age-specific (Houle et al., 1994). Secondly, it is possible that inadvertent selection during the experiment may have caused some of the correlated responses (Roper et al., 1993). Finally, the experiments are generally done in a novel environment, the laboratory, where genetic variances and covariances may change (Service and Rose, 1985; Leroi et al., 1994a, b). Negative genetic correlations between early and late fitness components have also been observed in quantitative genetic studies that employed one generation breeding designs. In Drosophila, Rose and Charlesworth (1981a) and Scheiner et al. (1989) found negative correlations between early and late female fertility. Hughes and Clark (1988) found evidence of negative correlations between longevity and early female fertility but not between early and late fertility in a chromosome extraction study. Tucic et al. (1988) found negative correlations between early male and female fertility on one hand and late female fertility and longevity on the other. Tanaka ( 1993) found a negative correlation between longevity and early female fertility in the Azuki bean weevil, Cullosohruchus chinensis. In contrast to the above examples, many breeding studies have found positive genetic correlations between early and late life history parameters (Appendix la in Stearns, 1992). However, the design of most of these studies are biased towards this result (see Service and Rose, 1985; Clark, 1987; Rose, 1991). Even when positive correlations are observed, their magnitudes may decrease with the age separating the classes. This has been observed in Duphniu where the genetic correlations between age-specific female fertilities tend to decline as they become separated by larger age intervals, and in the most comprehensive study to date they became essentially zero (Spitze, in press). As seen from (7) the genetic correlations between fitness components in the two sexes are as important as those within sexes. Unfortunately, there are few estimates of genetic correlations between male and female fitness components, but see Tucic et al. (1988) mentioned above, and Price and Sigurdardottir (in prep) who found that Drosophila early male mating ability is negatively genetically correlated with female and male larval viability. In species with morphological or behavioral sex dimorphism one expects opposing selection between sexes to produce negative correlations between sex-specific fitness components. Adaptations to male-male competition may often have negative effects on female fitness as well as male viability (e.g., Andersson, 1994). In zebra finches, Tuneiopygiu guttutu., male mating ability is negatively correlated with female fertility and viability (Price and Burley, 1994). In this study, males with the reddest bills, which are the most attractive, have the highest reproductive rates, but females with the reddest bills die earlier and have lower reproductive rates. In sum, negative genetic correlations between early and late fitness components are commonly found. The extrapolation of these results to any particular species is Good 769 genes and old age indicative at best. In addition to the methodological problems discussed above, we emphasize that the data are from a very small sample of species and that the correlations are not measured in their natural environments. It is also unfortunate that the evidence for males is very much weaker than that for females. Still, the results make negative and weak genetic correlations between early and late fitness components a very realistic expectation; the consequences should be entertained. In the next two sections, we integrate these findings with the previous theory. Conclusions regarding the effects qf viability selection The consideration of fitness sensitivities motivates the assumption that fitness is largely determined by young male and female viability and fertility. Given this assumption, viability selection on males increases the breeding value for fitness from one age class, a, to the next, a + 1, if Pi:’ is positively correlated with early survival and fertility (see 2). For young individuals, Pr is a component of early male survival and is certainly positively correlated with it. The correlation between Pi; and early male and female fertility is not well known, and may well be negative, but it seems likely that viability selection raises fitness in young individuals. As individuals age, the correlation of PT with early viability may decrease. Whether this correlation decreases substantially or eventually becomes negative is not known. The data just discussed indicate that late survival, as the most important determinant of longevity, may be negatively correlated with early (and late) fertility. These considerations indicate that viability selection may eventually start to decrease the breeding value of fitness at older ages. Whether this occurs in cohorts young enough to be of any interest is hard to decide. It is clear, however, that viability selection gradually loses some efficiency to alter the breeding value of fitness as the cohort ages. Conclusions vegurding the eflkts oj’jkrtility selection Fertility selection increases gamete fitness with age if early survival and fertility, as main components of fitness, have larger genetic covariances with F::‘+, than with F::’ (see 2). Hence, the breeding value for fitness in gametes produced could decline with age even though the correlation between fertility and fitness remains positive at all ages. It seems most likely that the covariance of PC:’ with early male and female fertility will decrease with age after the cohort has reached an age of substantial reproductive contribution. In fact, if we allow the extrapolation from females to males, the data discussed above indicate that genetic correlations between early and late fertility are often negative. Although there are no pure estimates of the genetic correlation between late age fertility and early survival, it seems unlikely that this correlation is highly positive. Thus, the genetic correlation between fertility and fitness may decrease with age and possibly become negative at 770 Hansen and Price older ages. Note that the actual strength of selection depends on covariances and not correlations. Covariances tend to be larger for age classes with high fertilities due to a larger potential for variation. However, excluding life histories and parts of life histories where fertilities increase strongly with age, we tentatively conclude that fertility selection leads to a decrease in the fitness of gametes with age. Nonequilibrium populations: Effects of selection on the parents So far, we have assumed that the population is at an evolutionary equilibrium with respect to fitness, as one would expect from mutation-selection balance, for example. Now, we consider a situation where fitness is transmitted undiminished from parents to offspring such that the mean fitness among zygotes increases over the generations as described by Fisher’s fundamental theorem of natural selection (Fisher, 1958; Price, 1972b). In this situation, younger individuals tend to have elevated fitness due to being born more recently from parents that have on average higher fitness than the parents of older individuals. According to the fundamental theorem, the mean fitness of zygotes changes by an amount Vur,,[W] per generation, assuming that the variance in relative fitness among zygotes stays constant. Hence, the difference in mean fitness between the parents of two cohorts of ages a and a + i, respectively, must be iVuv,,[W]/g where g is generation time. This factor is then subtracted from equations (1) -( 3). As an example, equation (1) becomes where the factor 2 is due to selection operating on both male and female parents. Clearly, this reduces the fitness of older individuals as compared to contemporary younger individuals. Whether the mean fitness in a population typically increases is far from clear. Fisher’s view seemsto have been that it often does (Fisher, 1958, p. 45). Frank and Slatkin (1992) have viewed his fundamental theorem in this light. The Red Queen hypothesis by Van Valen (1973) suggeststhat populations are continually evolving becausethe biotic interactions with other speciesare in constant change. Models of community evolution have indicated that this indeed can lead to a steady state of evolutionary change (Stenseth and Maynard Smith, 1984). It is unclear whether such processescan be significant on a generation to generation basis. Changes due to rapidly evolving pathogens may be a case in point (Hamilton, 1980; Bell, 1985; Ladle, 1992). Charlesworth (1988) has shown that mate choice in a fluctuating environment can result in preferences for attractive traits that reflect viability increasing in a population. The periodicity of the fluctuations must be relatively long for female preference for viability related attractive traits to increase in frequency. In conclusion, selection on parents is potentially a very powerful force for shifting the distribution of genetic quality towards young individuals, but this requires Good 771 genes and old age ongoing evolution towards improved adaptation. is an open question in evolutionary theory. Whether this is the common state Effects of germ-line mutations The model developed by Manning ( 1985) to explain female preference for older males assumed that spontaneous mutations entered the population at the zygote stage. Each new cohort would start with the same average number of new mutations. As a cohort aged those individuals that possessed more of these new mutations would die early in life. Older cohorts would then possess, on average, fewer new mutations than younger cohorts. However, it is now recognized that spontaneous mutations enter populations not predominantly at the zygote stage but rather in adult male germ-line cells that produce gametes (Crow, 1993). The effect of this is to decrease the breeding value of males continuously throughout their life as new mutations appear. The first type of evidence for male germ-line mutations comes from studies of the relative mutation rates between males and females in primates, mice and Drosophila Estimates of the ratio of male to female substitution rates for homologous genes on the Y and X chromosomes range from as low as two to as high as infinity (Crow and Temin, 1964; Abrahamson et al., 1981; Miyata et al., 1990; Russell and Russell, 1992; Shimmin et al., 1993; Chang et al., 1994). Although these estimates have substantial uncertainty they are consistent with the hypothesis that most mutations are generated in males (Crow, 1993; Shimmin et al., 1993). A second indication comes from direct observation in humans of a correlation between the age of the father, but not the mother, with the frequency of several dominant genetic diseases (Haldane, 1947; Model1 and Kuliev, 1990; Crow, 1993). In fact, there seems to be a faster than linear increase of the occurrence of such illnesses with parental age (Model1 and Kuliev, 1990). Crow (1993) speculates that this is due to a decrease in the efficiency of repair mechanisms with age. A third indication comes from the observations of clusters of mutations in offspring from the same father in several species which are attributed to mutations at the premeiotic stage (Woodruff and Thompson, 1992). A reasonable explanation of all these phenomena is that mutations occur during mitotic cell divisions in the germ-line. For example, many mammalian males continually produce gametes throughout life, and thus the number of cell divisions increases with the father’s age. Most mammalian females, however, produce all their gametes before first reproduction, and thus there is no change in the number of cell divisions between young and old gametes. Crow ( 1993) estimated the number of cell divisions between zygote and egg in humans to be 24, while a sperm produced at puberty has been through 36 cell divisions, and thereafter there are approximately 23 cell divisions per year for sperm. Hence, a sperm produced at age 30 has been through about 430 cell divisions, 18 times the number of cell divisions in an egg produced by a similarly aged female. These figures may be less extreme in other species (Chang et al., 1994), but it is likely that older males, as compared 772 Hansen and Price to younger males and females, have reduced breeding values of fitness due to accumulated germ-line mutations. Differences in mutation rates between age and sex classes are only important if the amount of variation introduced by mutation per generation is significant in comparison with standing genetic variation. Mutation accumulation experiments with Drosophila melunogaster, such as those of Mukai et al. (1972), have obtained estimates on the order of 1% reduction in viability per haploid genome per generation due to new mutations (Crow, 1993). This does not provide much basis for mate choice. However, these estimates are based on experiments in benign noncompetitive environments and do not include fertility related fitness components (Houle et al. 1992). The genomic mutation rate in vertebrates may also be orders of magnitude higher due to their larger number of genes (Kondrashov, 1988). Hence, the reduction in fitness due to mutation may very well be on the order of 10% or more and potentially very important. This is especially true when considering that the above per generation mutation rate estimates are obtained for relatively young males. If the majority of mutations are occurring in the germ-line cells prior to gamete formation, they may reduce the breeding value in fitness of an old male substantially more than is indicated by current estimates. Discussion We have reviewed factors that influence the age distribution of the mean breeding value of fitness to address the potential for mate choice based on the age of individuals to produce offspring of high genetic quality. We have shown that the distribution of breeding values is a complex function of the sensitivity of fitness to and the genetic correlations among age-specific fecundity and viability parameters, the input of germ-line mutations, the magnitude of selection among the age classes, and the rate of evolution of the mean population fitness. The assertion that older males are genetically superior to younger males (e.g., Trivers, 1972; Halliday, 1978; Manning, 1985) is not supported by our analysis. Viability selection is the only proposed mechanism for creating a peak in fitness at an old age. It has been argued that, as older individuals must survive both early and late age viability selection, there will be a positive correlation between the ability to survive to an old age and overall viability-related fitness. However, the likely existence of negative correlations between late age male viability on the one hand and young male and female fitness components on the other substantially weakens this argument. Considering that the effects of fertility selection, selection on parents and new germ-line mutations all favor young or intermediately aged individuals, it does appear likely that older males often have reduced breeding values of fitness. Life-histories in which fertility is steeply increasing with age appear to be the only situation that lends some credibility to the “old is most fit” hypothesis. An increasing fertility with age postpones the rapid drop-off of the sensitivity of fitness to survival and increases the potential for selection on fertility with age. However, Good genes and old age 773 we believe that this type of life-history is relatively uncommon in determinate growers such as birds, insects and mammals. The potential for mate choice based on age depends critically on the amount of genetic variation in fitness explained by age. Viability selection at old age is possibly too inefficient to cause much difference among ages, whether positive or negative. Fertility selection, on the other hand, can clearly make for substantial differences and we have argued that this may possibly also be the case for germ-line mutations. Fitness differences between parents due to ongoing adaptation are clearly important in nonequilibrium populations, but whether populations are commonly far from equilibrium is an open question. Tt has been argued that good genes models are in general unlikely to work due to lack of additive genetic variance in fitness (e.g., Williams, 1975; Maynard Smith, 1978); see Partridge (1980), Heisler (1984) and Rice (1988) for discussion. However, it has been demonstrated that fitness components as a group have large amounts of additive genetic variation, in fact larger than that of any other trait group considered (Houle, 1992). This is likely due to the multitude of genetic factors influencing them, and it is therefore reasonable to expect that total fitness also shows substantial additive genetic variation. In conclusion, we have established the plausibility of the hypothesis that fairly young individuals tend to have the highest breeding values of fitness. The theory depends on many factors, such as genetic covariances and life history parameters, that are poorly known and highly variable from species to species, thus we cannot claim more than plausibility of the hypothesis. However, we have shown that the alternative hypothesis of older individuals having the highest breeding values of fitness cannot, as is often the case, be assumed uncritically. Within the present state of knowledge, it must be considered somewhat less plausible. It is unlikely that theory and circumstantial evidence can resolve the hypotheses to a much greater extent than what is attempted in this paper. Further progress must come from direct experiments designed to estimate the breeding values of males as a function of age. Alatalo et al. (1986) presented data indicating that female collared flycatchers, Ficedulu albicollis, mated with yearling males produce offspring, male and especially female, with higher life time reproductive success than females mated to older males. We caution that these estimates are very uncertain and that environmental effects are not ruled out. Howard et al. (1994) performed a breeding experiment with toads, Bufo americanus, to test the good genes hypothesis that older and larger males had better offspring. They measured the effects of father’s size and age on larval survival and developmental rates. Their results gave no support to the hypothesis that larger males had better genes. Neither could they reject the null hypothesis that offspring quality was independent of age, but estimates of effects were not given. Their design excluded fertility selection. Price and Hansen (in prep) measured the effects of father’s age on three components of offspring fitness in Drosophilu melunoguster. The fitness components were larval survival in a competitive environment, daughter early fecundity, and son early competitive mating ability. The preliminary results are indicative of a weak negative effect of father’s age on larval survival and son mating ability, but of no 774 Hansen and Price effect on daughter fecundity. Additional studies are needed before the direction and potential for mate choice based on age can be adequately assessed. Our results provide a new challenge to explain observations, such as those cited in the introduction, of females preferring older males in cases where paternal investment cannot be correlated with female mating preference. First, it is possible that the ages of males in some studies range from young to intermediate age. Females may indeed discriminate against very old males (e.g., Burley and Moran, 1979). Experiments designed to measure female preference of young, intermediate aged and older males would help to discriminate among the different models. A second possible explanation for females preferring older males is that an attractive male trait may be correlated with age (Manning, 1989; Cote and Hunte, 1993; but see Petrie, 1993). Thus females mating with attractive males also mate with older males. Male traits may be correlated with age because they are correlated with body size, e.g. acoustic traits and morphological traits, or exaggerated development of traits, e.g. tail length in birds. Thus, these traits may take time to develop fully, creating a correlation between age and the size of the trait. Although there would be selection to develop these attractive traits rapidly, there may be constraints on the development of the attractive trait. Opposing selection between the sexes combined with a positive genetic correlation would be one mechanism displacing males from their optimal expression of a trait (Lande, 1980; Price and Burley, 1994) and possibly altering the developmental rate of the male trait (Price and Enstrom, in prep.). Furthermore, an attractive trait correlated with age may evolve in a runaway evolutionary processes that eventually results in a lack of a correlation between age and the male trait in a similar manner as proposed by Fisher ( 1958). Experiments designed to determine the correlation between female choice and male age would need to control, either statistically or experimentally, for the variation in attractive male traits. Finally, we note the possibility that, in the light of our hypothesis, observations of preference for old mates in species with no parental investment may now be interpreted as evidence against good genes models of mate choice. Acknowledgements We thank I. L. Helsler, H. Lampe, R. Lande, E. P. Martins and two anonymous referees for helpful discussions and comments on the manuscript. D. Houle and K. Spitze kindly provided unpublished results. TFH thanks M. Lynch for hospitality during a stay in his lab where this work was initiated. DKP was supported by a NSF grant through the University of Oregon. References Abrahamson, S.. H. U. Meyer and C. De Johgh. 1981. The shapes of the radiation dose-mutation in Drosophila: Mechanisms and implications, pp. 477 492. In G. C. Berg and H. D. Maillie Measurement of Risk. Plenum Press, New York. curves (eds.), Good genes and old age 775 Abugov, R. 1986. Genetics of Darwinian Fitness III. A generalized approach to age structured selection and life history. J. Theor. Biol. 122: 31 I-323. Abugov, R. 1988. A sex-specific quantitative genetic theory for life-history and development. J. Theor. Biol. 132: 437-447. Alatalo, R. V., L. Gustafsson and A. Lundberg. 1986. Do females prefer older males in polygynous bird species? Am. Nat. 127: 241-245. Alcock, J. 1984. Animal Behaviour: An Evolutionary Approach. 3 ed. Sinauer Assoc., Sunderland, Massachusets. Andersson, M. 1986. Evolution of condition-dependent sex ornaments and mating preferences: Sexual selection based on viability differences. Evolution 40: 804-816. Andersson, M. 1994. Sexual Selection. Princeton Univ. Press, Princeton, New Jersey. Bell, G. 1985. Two theories of sex and variation. Experientia 41: 123% 1245. Buchholz, R. 1991. Older males have bigger knobs: Correlates of ornamentation in two species of curassow. The Auk 108: 153-160. Burley, N. and N. Moran. 1979. The significance of age and reproductive experience in the mate preferences of feral pigeons, Columha livia. Anim. Behav. 27: 686-698. Caswell, H. 1989. Matrix Population Models. Sinauer Press, Sunderland, MA. Chang. B. H.-J., L. C. Shimmin, S.-K. Shyue, D. Hewett-Emmett and W.-H. Li. 1994. Weak male-driven molecular evolution in rodents. Proc. Natl. Acad. Sci. 91: 827-831. Charlesworth, B. 1988. The evolution of mate choice in a fluctuating environment. J. Theor. Biol. 130: 191-204. Charlesworth, B. 1994. Evolution in Age-structured Populations. Sec. Ed. Cambridge Univeristy Press. Cambridge, U. K. Clark, A. G. 1987. Senescence and the genetic correlation hang-up. Amer. Natur. 129: 932-940. Clutton-Brock, T. H. 1988. Reproductive Success: Studies of Individual Variation in Contrasting Breeding Systems. University of Chicago Press. Chicago. Clutton-Brock, T. H., S. D. Albon and F. E. Guinnes. 1988. Reproductive success in male and female red deer, pp. 325 343. In T. H. Clutton-Brock (ed.), Reproductive Success. University of Chicago Press, Chicago. Cc%& I. M. and W. Hunte. 1993. Female redlip blennies prefer older males. Anim. Behav. 46: 203 205. Crow, J. F. 1993. How much do we know about spontaneous human mutation rates? Envir. Mol. Mut. 21: 122-129. Crow, J. F. and R. Temin. 1964. Evidence for the partial dominance of recessive lethal genes in natural populations of Drosophilu psrudooohscurrr. Am. Nat. 98: 21 -33. Davison, G. W. H. 198 I, Sexual selection and the mating system of Arguiunus LI~~~‘US( Aves: Phasanidae). Biol. J. Linn. Sot. 15: 91-104. Falconer, D. S. 1989. Quantitative genetics. Third ed. Longman, Harlow, U.K. Fisher, R. A. 1958. The Genetical Theory of Natural Selection. Sec. ed. Dover Press, New York. Frank, S. A. and M. Slatkin. 1992. Fisher’s fundamental theorem of natural selection. TREE 7( 3): 92 95. Grant, B. R. and P. R. Grant. 1987. Mate choice in Darwin’s finches. Biol. J. Lin. Sot. 32: 247-270. Haldane, J. B. S. 1947. The rate of mutation of the gene for hemophilia and its segregation ratios in males and females. Ann. Eugen. 13: 262-271. Hamilton, W. D. 1966. The moulding of senescence by natural selection. J. Theor. Biol. 12: 12-45. Hamilton. W. D. 1980. Sex versus non-sex versus parasite. Oikos 35: 282-290. Halliday, T. R. 1978. Sexual selection and mate choice. Behavioral Ecology. London, U. K., Blackwell Press. Halliday, T. R. 1983. The study of mate choice, pp. 3-32. In P. Bateson (ed.), Mate Choice. Cambridge Univ. Press, Cambridge UK. Heisler, I. L. 1984. A quantitative genetic model for the origin of mating preferences. Evolution 38: 1283-1295. Heisler, I. L.. M. B. Andersson, S. J. Arnold, C. R. Boake, G. Borgia. G. Hausfater, M. Kirkpatrick, R. Lande, J. Maynard Smith, P. O’Donald, A. R. Thornhill and F. J. Weissing. 1987. 776 Hansen and Price The evolution of mating preferences and sexually selected traits group report, pp 96-I 18. In J. W. Bradbury and M. Anderson (eds.). Sexual Selection: Testing the Alternatives. John Wiley and Sons, New York. Houle, D. 1992. Comparing evolvability and variability of quantitative traits. Genetics 130: l95- 204. Houle. D., D. K. Hoffmaster, S. Assimacopoulos and B. Charlesworth. 1992. The genomic mutation rate for fitness in Drosophilrr. Nature 359: 5860. (Correction in Nature (1994) 371: p. 358). Houle, D., K. Hughes, D. K. Hoffmaster. J. Ihard, S. Assimacopolus, D. Canada and B. Charlesworth. 1994. The effects of mutation on quantitative traits. 1. Variance and covariance of life history traits. Genetics 138: 773- 785. Howard, R. D., H. H. Whiteman and T. 1. Schueller. 1994. Sexual selection in american toads: A test of a good-genes hypothesis. Evolution 48: 1286- 1300. Hughes, D. M. and A. G. Clark. 1988. Analysis of the genetic structure of life history of Drosophiku melanogaster using recombinant extracted lines. Evolution 42: 1309- 1320. Jlrvi. T.. E. Rsskaft and T. Slagsvold. 1982. The conflict between male polygamy and female monogamy: Some comments on the “cheating hypothesis”. Am. Nat. 120: 68YY6Yl. Kirkpatrick, M. 1987. Sexual selection by female choice in polygynous animals. Ann. Rev. Ecol. Syst. IS: 43370. Kodric-Brown, A. and J. H. Brown. 1984. Truth in advertising: the kinds of traits favored by sexual selection. Am. Nat. 124: 795581 1. Komers, P. E. and M. S. Dhindsa. 1989. Inlluence of dominance and age on mate choice in black-billed magpies-An experimental study. Anim. Behav. 37: 645 655. Kondrashov, A. S. 1988. Deleterious mutations and the evolution of sexual reproduction. Nature 336: 4355440. Ladle, R. J. 1992. Parasites and Sex: Catching the Red Queen. TREE 7( 12): 4055408. Lande, R. 1980. Sexual dimorphism, sexual selection, and adaptation in polygenic characters. Evolution 34: 292p 305. Lande, R. 1981. Models of speciation by sexual selection on polygenic traits. Proc. Natl. Acad. Sci. (USA) 78: 3721-3725. LeBoeuf, B. J. and J. Reiter. 1988. Lifetime reproductive success of northern elephant seals. In T. 11. Clutton-Brock (ed.), Reproductive Success: Studies of Individual Variation in Contrasting Breeding Systems. University of Chicago Press, Chicago. Leroi, A. M., A. K. Chippindale and M. R. Rose. 1994a. Long-term laboratory evolution of a genetic life-history trade-off in Drosophila melunogaster. I. The Role of Genotype-by-Environment Interaction. Evolution 48: 1244- 1257. Leroi, A. M., W. R. Chen and M. R. Rose. 1994b. Long-term laboratory evolution of a genetic life-history trade-off in Drosophila m&nogaster. 2. Stability of genetic correlations. Evolution 48: 12581268. Luckinbill. L. S., R. Arking, M. J. Glare, W. C. Cirocco and S. A. Buck. 1984. Selection for dclaycd senescence in Drosophiku mrkmogrrster. Evolution 38: Y96- 1003. Manning, J. T. 1985. Choosy females and correlates of male age. J. Theor. Biol. 116: 3499354. Manning, J. T. 1987. The peacock’s train and the age-dependency model of female choice. J. World Pheasant Assoc. 12: 44456. Manning, J. T. 1989. Age-advertisement and the evolution of the peacock’s train. J. Evol. Biol. 2: 3799384. Maynard Smith, J. 1978. The Evolution of Sex. Cambridge Univ. Press, Cambridge, UK. McDonald, D. B. 1993. Demographic consequences of sexual selection in the long-tailed manakin. Behav. Ecol. 4: 297-309. Medawar, P. B. 1946. Old age and natural death. Modern Quarterly 1: 30. Reprinted in: The Uniqueness of the Individual (1957). Methuen, London. Miyata, T., K. Kuma, N. Jwabe, H. Hayashida and T. Yasunaga. 1990. Different rates of evolution in autosome-, X chromosome-, and Y chromosome-linked genes: Hypothesis of male-driven molecular evolution, pp. 341 357. In N. Takahata and J. Crow (eds.), Population Biology of Genes and Molecules. Baifukan, Tokyo. Good Modell, genes and old age 777 B. and A. Kuliev. 1990. Changing paternal age distribution and the human mutation rate in Europe. Hum. Genet. 86: 1988202. Mueller, L. D. 1987. Evolution of accelerated senescence in laboratory populations of Drosophila. PNAS 84: 1974 1977. Mukai, T., S. I. Chigusa, L. E. Mettler and J. F. Crow. 1972. Mutation rate and dominance of genes affecting viability in Drosophila mrlunogaster. Genetics 72: 3355355. Moller, A. P. 1992. Frequency of female copulations with multiple males and sexual selection. Am. Nat. 139: 1089~1101. Newton, I. 1989. Lifetime Reproduction in Birds. Academic Press. Partridge, L. 1980. Mate choice increases a component of otfspring fitness in fruitflies. Nature 283: 290-291. Partridge, L. and N. H. Barton. 1993. Optimality, mutation and the evolution of ageing. Nature 362: 305 311. Petrie, M. 1993. Do peacock’s trains advertise age? J. Evol. Biol. 6: 4433448. Pomiankowski, A. 1988. The evolution of female mate preference for male genetic quality. Oxford surveys of Evolutionary Biology. 5: l36- 184. Poole, J. H. 1989. Mate guarding, reproductive success and female choice in African elephants. Anim. Behav. 37: 8422849. Price, D. K. and N. T. Burley. 1994. Constraints on the evolution of attractive traits: selection in male and female zebra finches. Am. Nat. 144: 908 934. Price. G. R. 1970. Selection and covariance. Nature 227: 520~-521. Price, G. R. 1972a. Extension of covariance selection mathematics. J. Hum. Genet. 35: 4855490. Price, G. R. 1972b. Fisher’s fundamental theorem made clear. Ann. Hum. Genet. 36: l29- 140. Price, T. D. 1984. Sexual selection on body size, territory and plumage variables in a population of Darwin’s finches, Evolution 38: 3277341. Rice, W. R. 1988. Heritable variation in fitness as a prerequisite for adaptive female choice: The effect of mutation-selection balance. Evolution 42: 817-820. Roff, D. A. 1991. The Evolution of Life Histories. Chapman & Hall. Roper, C., P. Pignatelli and L. Partridge. 1993. Evolutionary effects of selection on age at reproduction melmogaster. Evolution 47: 445 455. in larval and adult Drosophila Rose, M. R. 1984. Laboratory evolution of postponed senescence in Drosophilu melunoguster. Evolution 38: 1004- 1010. Rose, M. R. 1991. Evolutionary Biology of Aging. Oxford University Press, New York. Rose, M. R. and B. Charlesworth. 198la. Genetics of life history in Drosophila mrlmogaster. I. Sib analysis of adult females. Genetics 97: 173 186. Rose. M. R. and B. Charlesworth. 1981 b. Genetics of life history in Drosophila nwhnoguster. II. Exploratory selection experiments. Genetics 97: l87- 196. Russell, L. B. and W. L. Russell. 1992. Frequency and nature of specific locus mutations induced in female mice by radiations and chemicals: A review. Mut. Res. 296: 1077128. Scheiner, S. M.. R. L. Caplan and R. F. Lyman. 1989. A search for trade-offs among life history traits in Drosophikr mrkmogu.vtrr. Evol. Ecol. 3: 5 I 63. Service, P. M. 1993. Laboratory evolution of longevity and reproductive fitness components in male fruit flies: Mating ability. Evolution 47: 387 399. Service, P. M. and A. J. Fales. 1993. Evolution of delayed reproductive senescence in male fruit flies: Sperm competition. Genetica 91: I I I 125. Service, P. M. and M. R. Rose. 1985. Genetic covariation among life-history components: The effect of novel environments. Evolution 39: 9433944. Shimmin, L. C.. B. H-J. Chang and W-H. Li. 1993. Male-driven evolution of DNA sequences. Nature 362: 745 747. Simmons, L. W. 1988. Male size, mating potential and lifetime reproductive success in the held cricket, Gry1lu.r himrrculutus (De Geer). Anim. Behav. 36: 372 379. Simmons, L. W. and M. Zuk. 1992. Variability in call structure and pairing success of male field crickets, The effects of age. size and parasite load. Anim. Behav. 44: II455 I 152. GrJl1u.s hin~crcu1rtu.s: 778 Hansen and Price Spitze. K. 1995. Quantitative genetics of zooplankton life histories. Experentia 51: 4544464. Stearns, S. C. 1992. The Evolution of Life Histories. Oxford University Press, Oxford, U. K. Stenseth, N. C. and Maynard Smith, 1984. Coevolution in ecosystems: Red Queen evolution or stasis‘? Evolution 38: 870 -880. Stidel, O., U. Bickmeyer and K. Kalmring. (1991). Tooth impact rate alteration in the song of males of Ephippiger ephippiger Fiebig (Orthoptera, Tettigoniidae) and its consequences for phonotaxic behavior of females. Bioacoustics 3: l-16. Tanaka, Y. 1993. A genetic mechanism for the evolution of senescence in Callosobruchus chinensis (the aruki bean weevil). Heredity 70: 31 g-321. Trivers, R. L. 1972. Parental investment and sexual selection. pp 136- 179. In B. Campbell (ed.). Sexual Selection And The Descent Of Man 187 1~ 197 I. Chicago, Il., Aldine Press. Tucii-, N., Cvetkovii: and D. Milanovic. 1988. The genetic variation and covariation among fitness components in Drosophilcr melunogaster females and males. Heredity 60: 55560. Van Valen, L. 1973. A new evolutionary law. Evol. Theory I: l--30. Vandenberghe, E. P., F. Wernerus and R. R. Warner. Female choice and the mating cost of peripheral males. Anim. Behav. 38: 8755884. Weatherhead, P. J. 1984. Mate choice in avian polygyny: Why do females prefer older males? Am. Nat. 123: 873-875. Williams. G. C. 1957. Pleiotropy, natural selection. and the evolution of senescence. Evolution I I: 398-411. Williams, G. C. 1975. Sex and Evolution. Princeton Univ. Press, Princeton. New Jersey. Woodruff, R. C. and J. N. Thompson, Jr. 1992. Have premeiotic clusters of mutation been overlooked in evolutionary theory? J. Evol. Biol. 5: 4577464. Yasakawa, K. 1981. Male quality and female choice of mate in the red-winged blackbird (Ageluius phoeniceus). Ecology 62: 9222929. Zuk, M. 1987. Variability in attractiveness of male field crickets (Orthoptrrrr: Gryllidue). Anim. Behav. 35: 124Om 1248. Zuk, M. 1988. Parasite load, body size, and age of wild-caught male field crickets (Ovthoptrrrr: Gryllidue): Effects on sexual selection. Evolution 42: 969 976. Received 7 July 1994; revised 9 March 1995; accepted 25 April 1995. Corresponding Editor: M. R. Rose