Life-history Characteristics
 All
organisms have been selected to
maximize reproductive success over the
course of their lifetimes.
 There
is, however, tremendous variation in
how organisms achieve this.
Life-history Characteristics
 Some
organisms produce many offspring
at once, but live only a short time.
 Others
produce a few offspring over the
course of a long life.
Life-history Characteristics
 There
is also enormous variation in the
size of offspring. Oysters produce 10-50
million tiny eggs whereas whales produce
a single large calf.
 What
explains the variation we see?
Life-history Characteristics
 Clearly,
there are constraints and tradeoffs in the strategies that organisms can
employ.
 The best strategies are determined by the
availability of energy and an organisms’
prospects of survival.
Sample life history
 Consider
a hypothetical female opossum’s
life history.
 Born and nursed by mother for about 3
months.
 Becomes independent and grows to
maturity.
 Age 10 months has first litter of 8 pups.
Age 15 months has second litter of 7 pups
 Killed by predator at 20 months.
Fig 12.2
Life-history Characteristics
 Female’s
energy came from different
sources and was allocated in different
directions over course of her life.
 For
first 3 months received energy from
her mother. After that had to obtain her
own.
Life-history Characteristics
 As
a juvenile she devoted energy to
growth, metabolism and repair.
 After
reaching maturity she devoted
energy to metabolism, repair and
reproduction.
Life-history Characteristics


Fundamentally, differences in how and when
energy is allocated affect life history strategies.
A different opossum might have matured earlier
at a smaller size, and produced babies earlier,
but perhaps fewer or smaller ones.
 Alternatively, more energy might be allocated to
repair and less to reproduction, perhaps
resulting in a longer life.
Differential energy allocation by
sand crickets

Sand crickets occur in both long-winged and
short-winged forms (papers by Zhao and Zera
2002, 2003).
 Long-winged forms have well developed flight
muscles and fuel to power them. This enables
them to disperse if conditions are poor.
 Short-winged forms cannot disperse, but can
develop eggs more quickly.
 There is a trade-off between dispersal ability and
early reproduction.
Issues in life-history analysis
 Analyzing
life history decisions involves
cost-benefit analysis and an examination
of fitness trade-offs as it relates to the
following questions:



Why do organisms age and die?
How many offspring should an individual
produce in a given year?
How big should each offspring be?
Why do organisms age and die?
 Senesence
is a late-life decline in an
individual’s fertility and probability of
reproducing.
 Same
pattern found in many organisms.
Fig 12.4
Senesence
 If
senesence reduces reproductive
success we would expect it to be opposed
by selection.
Hypotheses explaining
senesence
 Two
major hypotheses on why aging
persists:
 Rate-of-living theory
 Evolutionary trade-off theory
Rate-of-living Hypothesis

This hypothesis suggests that aging is caused
by accumulation of cellular damage caused by
accumulation of toxins and accumulation of
errors during replication, transcription and
translation of DNA.

Hypothesis suggests organisms have reached
limit of biological repair and no more genetic
variation exists for improved repair mechanisms.
Rate-of-living Hypothesis
 Hypothesis
makes two predictions.
 1. Cell and tissue damage are caused by
metabolism so aging rate should be
correlated with metabolic rate.
 2. Species should not be able to evolve
longer life spans.
Rate-of-living Hypothesis
 Austad
and Fisher (1991) tested prediction
1.
 Calculated amount of energy expended
per gram of tissue per lifetime for 164
mammal species. Theory predicts rate
should be similar across groups.
 Found large range from 39 kcal/g/lifetime
in elephant shrews to 1,102 kcal/g/lifetime
in a bat.
Fig 12.5
Rate-of-living Hypothesis
 Also
found bats have rates similar to those
of many other mammals but life spans that
are 3 times as long.
 These
patterns don’t fit rate-of-living
predictions.
Rate-of-living Hypothesis
 Luckinbill
et al. (1984) tested prediction 2
by artificially selecting for longevity in fruit
flies.
 Lineages
in which they selected for late
reproduction showed greatly increased
longevity over the course of 13
generations of selection. Average lifespan
increased from 35 to 60 days.
Fig 12.6
Rate-of-living Hypothesis
 Results
of tests thus do not support the
rate-of-living hypothesis.
Evolutionary Hypothesis for
aging
 If
selection can produce longer life spans
why does it not do so?
 Under
evolutionary hypothesis for aging,
organisms age because the body fails to
repair cell and tissue damage rather than
because it cannot do so.
Evolutionary Hypothesis for
aging
 Failure
to repair may be due to (i)
accumulation of deleterious mutations or
(ii) trade-offs between repair and
reproduction.
Evolution of senesence in a
hypothetical population.
 Population
has annual probability of
survival each year of 0.8 (death by
accident, predation, etc.). Population
declines exponentially over time.
 Individuals with wild-type genotype mature
at age 3 and die at age 16 (if not killed).
Have one offspring a year.
 Population expected lifetime reproductive
success of 2.419.
12.9a
Evolution of senesence in a
hypothetical population.
 New
mutation occurs which causes death
at age 14. Rest of life history unchanged.
 Expected lifetime RS reduced to 2.34
offspring, a small reduction and 96% of the
lifetime RS of the wildtype.
 Few individuals live beyond 14 in wildtype
population so effect is small.
12.9b
Evolution of senesence in a
hypothetical population.
 In
general, mutations that cause death late
in natural life will be only weakly selected
against.
 Mutation that causes death at a young
age, of course, will be strongly selected
against.
 Such mutations may be maintained in
population by mutation-selection balance.
Evolution of senesence in a
hypothetical population.
 An
example of the kind of mutation that
could cause death only late in life might be
one that causes cells to not repair
themselves as well as is possible.
 For example, in humans, a DNA mismatch
repair mutation causes a form of colon
cancer. Median age of diagnosis is 48
(range 17 to 92) well after reproduction
has begun.
Evolution of senesence in a
hypothetical population.
 In
our hypothetical population a second
mutation occurs that causes reproduction
to begin at age 2 and death at age 10.
 There is thus a trade-off between age of
first reproduction and longevity.
 Expected lifetime RS of individuals with
mutation is 2.66, which is 1.1 times the
wildtype’s RS.
Evolution of senesence in a
hypothetical population.

Most individuals reap benefit of early
reproduction, bur few pay cost of earlier death.
 This mutant allele should spread rapidly.
 A gene that causes less energy to be devoted to
cellular damage repair and more to be devoted
to reproduction would fit profile of such a mutant.
Several have been identified in fruit flies and
nematodes.
Evidence of a trade-off caused by
early reproduction.
 In
a study of Collared Flycatchers
individuals that bred at age 1 had smaller
clutches at ages 2-4 than individuals who
don’t first breed until age 2.
12.13
Evidence of a trade-off caused by
early reproduction.
 Also,
females whose clutches were
artificially enlarged in year 1 had
progressively smaller clutches in years 24.
Evidence of a trade-off caused by
early reproduction.
 Conclusion
is that there is a trade-off
between early and late reproduction in
Collared Flycatchers.
 First year breeders do have higher life
time RS than second year breeders.
Evolution of ageing in Opossums
 We
expect populations with low rates of
mortality due to factors such as predation
to evolve delayed senesence.
 Under these circumstances mutations that
cause senesence are more likely to make
themselves felt because animals live to be
older and so will be selected against.
Evolution of ageing in Opossums
 Austad
(1993) studied two populations of
Opossums one on Georgia mainland, the
other on Sapelo Island off the coast.
 Opposums on mainland have high
mortality rates from predators (>50% of all
deaths).
 No mammalian predators on Sapelo
Island.
Evolution of ageing in Opossums
 Austad
followed life histories of radiocollared opossums on both sites.
 Island populations aged more slowly than
mainland populations on several
measures including rate of survival,
reproductive performance, and connective
tissue physiology.
Fig 12.14
How many offspring should an
individual produce in a year?
 In
life history decisions a fundamental
choice is how many offspring to produce in
a year.
 The more offspring produced in a year, the
less each can be cared for and additional
offspring affect the parents prospects for
survival.
Clutch size in birds
 The
question of how many young is
optimal has been extensively studied in
birds.
 David Lack (1947) suggested that
selection would favor the clutch size that
produced the most surviving offspring.
Clutch size in birds
 If
probability of average offspring surviving
falls with increasing clutch size then we
can calculate optimal clutch size by
multiplying clutch size by probability of
survival.
 An intermediate clutch size is thus optimal.
Fig 12.16
Clutch size in birds
 There
have been numerous field studies
that have tested Lack’s hypothesis.
 Many
studies (including ones in which
additional eggs are added to the brood)
have found that the most productive clutch
is often several eggs larger than that laid
by the birds.
Fig 12.17
Clutch size in birds
 How
do we explain the observation that
many birds appear to lay clutches that are
smaller than the apparent optimum?
 Several
plausible hypotheses have been
put forward.
Clutch size in birds
 (i)
Lack’s hypothesis assumes that effort in
one breeding season has no effect on
effort in future years.
 Many
studies have shown that birds forced
to raise larger broods in one year, lay
smaller clutches the next year. Also, birds
that raise larger clutches have lower
survival to the next year.
Clutch size in birds
 (ii)
Increasing clutch size may reduce the
quality of the offspring.
 Schluter and Gustafsson (1993) added or
removed eggs from nests of Collared
Flycatchers.
 Monitored chicks subsequent life histories.
Clutch size in birds
 Found
young from nests with enlarged
clutches laid smaller clutches than did
birds from nests with reduced clutches.
 There
appears to be a trade-off between
number and quality of offspring so that
most productive clutch size is smaller than
that which produces the most surviving
offspring.
Fig 12.18
How big should each offspring be?
 Logically
there must be a trade-off
between number and size of offspring.
 A cake
can be cut into a few large pieces
or many small pieces, but not many large
pieces.
How big should each offspring be?
 Elgar
(1990) documented a clear negative
correlation between clutch size and egg
size in 26 families of fish.
 Fish that produce larger eggs produce
fewer eggs per clutch.
 A similar correlation between egg size and
clutch size has also been documented for
3 orders of insects Berrigan (1991).
Fig 12.21
Selection on offspring size
 Smith
and Fretwell (1974) analyzed the
problem of how parents could strike a
balance between size and number of
offspring.
 Their
analysis was based on two
assumptions (i) there is a trade-off
between size and number of offspring
Fig 12.22a
Selection on offspring size
 (ii)
Larger offspring have a better chance
of surviving.
 There must be a minimum size below
which offspring have no chance of
surviving, but above this survival
probability increases sharply with size
before leveling off (as it cannot exceed a
probability of 1).
Fig 12.22b
Selection on offspring size
 Given
the two assumptions it is easy to
determine an optimal balance for a pair of
curves.
 Parental fitness for an offspring size is
given by multiplying number of offspring by
survival probability.
 Plotting fitness against offspring size
allows optimum to be identified.
Fig. 12.22c
Selection on offspring size
 Optimal
offspring size will differ depending
on the shapes of the curves used in the
analysis.
 However,
an intermediate offspring size
will be favored. If relationship between
survival and size was linear rather than
curvilinear extreme offspring size might be
favored instead.
Selection on offspring size
 Note
that parental and individual offspring
optima differ.
 Producing
more, but smaller offspring
enhances parental fitness, but smaller
offspring have reduced survival
probabilities.
Selection on offspring size in
salmon
 Smith
and Fretwell’s model has been tested
in salmon.
 Heath
et al. (2003) studied Chinook salmon
at a commercial hatchery.
 They
confirmed Smith and Fretwell’s first
assumption that there is a trade-off between
egg size and number of eggs laid.
12.23 A
Mean egg mass
Selection on offspring size in
salmon
 They
also examined the relationship
between egg size and survival of young
fish (fry).
Fig 12.23b
Selection on offspring size in
salmon
 Using
the two curves, Heath et al.
calculated an optimal egg mass of 0.15g
for hatchery salmon.
 Optimal
egg size for hatchery salmon is
smaller than it is for wild salmon because
smaller fry survive better in the hatchery
than in the wild.
Fig 12.23c
Selection on offspring size in
salmon
 The
hatchery population was founded from
wild stock in the late 1980’s and given the
reproductive advantage females with
smaller eggs have, the population has
been evolving towards smaller egg sizes
since then.
12.23d
Conflicts of interest between life
histories
 Mammals
nourish their offspring using a
placenta.
 This
system of nourishing the offspring
allows an opportunity for conflict between
paternal and maternal genes.
Conflicts of interest between life
histories
 The
conflict stems from the fact that males
would prefer the female to invest heavily in
current offspring, whereas the female also
wishes to invest in future offspring (likely
fathered by other males).
Conflicts of interest between life
histories
 Selection
should favor males that can
coerce the female to invest more heavily in
the current offspring and mechanisms to
do this have been found.
 Certain
genes are biochemically imprinted
during gamete production, which allows
male and female alleles to be
distinguished.
Conflicts of interest between life
histories
 Imprinting
affects transcription of genes
within the embryo.
 For
example, in mice the paternal allele of
a hormone called Insulin-like Growth
Factor II (IGF II) is widely expressed, but
the maternal copy is hardly transcribed.
Conflicts of interest between life
histories
 This
pattern of imprinting is puzzling
because equal expression of alleles is the
norm.
 Female’s
turning off their allele runs the
risk of the fetus not producing an essential
enzyme if the male’s version is nonfunctional.
Conflicts of interest between life
histories

Haig et al. have explained the observed pattern
of imprinting as the result of a tug-of-war
between male and female alleles within the
fetus.

The paternally transcribed IGF-II is selected to
maximize rates of cell division (and hence
growth and monopolization of female
resources). The female allele is turned off to
preserve resources for future reproduction.
Conflicts of interest between life
histories
 Consistent
with the expectation that males
will attempt to influence resource
distribution when they can, genomic
imprinting does not occur in birds and
frogs where all resources are distributed
before fertilization.