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J. Evol.
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8: 759
778 (1995)
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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.
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Received 7 July 1994;
revised 9 March
1995;
accepted 25 April 1995.
Corresponding
Editor: M. R. Rose