Transcript No Slide Title - Cal State LA

Life-history evolution
For quantitative traits, the products of different genes combine to
produce one trait
How do multiple traits interact together, to produce…
..adaptation
..fitness
..life histories
The combination of all traits in a species produces the unique
life history for that organism
- age at maturity, # of offspring, survival rate, life span
- integrates fitness over the whole lifespan of the organism
Life-history evolution: How many offspring?
Assume the more eggs you lay,
the lower the odds of surviving
are for each individual offspring
Multiplying # of offspring
(= clutch size) by odds of each
offspring’s survival gives the
optimal clutch size
(Lack’s hypothesis)
Life-history evolution: How many offspring?
Data from study on birds showed that the mean # of surviving
baby birds was highest for clutches of 12 eggs
However, birds laid 8-9 eggs per clutch – why?
Life-history evolution: How many offspring?
The bird’s life history had
evolved to maximize
total lifetime
reproductive success
- birds that laid 12 eggs in their 1st clutch did great that year,
but used up so much energy caring for that many babies,
they burned out and didn’t reproduce in future years
- birds that laid only 8-9 eggs per clutch saved energy for more
future reproduction, so had higher lifetime fitness
Roadblocks for adaptive evolution
The adaptive evolution of life histories is often limited by
trade-offs, a consequence of many traits interacting and
competing for limited resources during development
- must sacrifice effort in one area to invest in another
Results from partitioning finite resources (energy) into
alternative traits or life-history strategies
- growth vs. defense
- disperse or reproduce
- many small offspring vs. few large offspring
Trade-offs 1: growth vs. defense
A classic trade-off in many organisms is growth vs. defense
option 1) invest energy in rapid growth and fast reproduction
- pro: you’re likely to reproduce before you get eaten
- con: you will probably be eaten after you reproduce once
example: fast-growing grasses
make
seeds
eaten by cow
5 days
5 days later
Trade-offs 1: growth vs. defense
A classic trade-off in many organisms is growth vs. defense
option 2) grow slowly and put energy into defenses
- pro: if well-defended, you survive & reproduce for many years
- con: it’s risky to delay reproduction, especially when small
example: slow-growing cactus
initially, make
spines instead of
growing bigger
5 years
later
eventually, big
spiny adult that
lives for decades
Trade-offs 2: developmental dimorphisms
Many animals can develop along 1 of 2 possible pathways,
producing alternative adult morphologies
- termed developmental dimorphisms, they often reflect
basic trade-offs
- 2 equal and balanced options, but each usually has an edge
under some set of environmental conditions
short-winged versus
long-winged morphs
in crickets
Trade-offs 2: developmental dimorphisms
Many animals can develop along 1 of 2 possible pathways,
producing alternative adult morphologies
Short-winged crickets:
Long-winged crickets:
- use up energy building, fueling - have more energy for egg
production
large flight muscles
- males make more mating
- reproduce less, but...
calls
- can fly to new food patches
- cannot migrate to new
when conditions go bad
food patches, however
Trade-offs 3: reproductive investment
Another common trade-off is in reproduction-- how many kids?
option 1) invest energy in many tiny offspring, which must take
care of themselves and survive until they’re fully grown adults
- pro: you produce many offspring, with little invested in each
- con: only a few will survive to reproduce themselves
mother’s
energy
most offspring
die during the
growth period
many tiny offspring
small %
survive
Trade-offs 3: reproductive investment
Another common trade-off in reproduction is, how many kids?
option 2) put energy into a few large offspring, which mature
quickly due to maternal provisioning
- pro: many offspring will survive to reproduce
- con: you can only make a few in the first place
mother’s
energy
most offspring
survive
few big offspring
big %
survive
Trade-offs 3: reproductive investment
Marine invertebrates can exhibit planktotrophy or lecithotrophy
planktotrophy: make many tiny larvae which must feed in the
plankton for a month before they are big enough to settle down
lecithotrophy: make a few big larvae that metamorphose right
after hatching
Importance for understanding trade-offs: a given species can do
one or the other, but --
(1) can’t do both (except in rare cases)
(2) in-between strategies do not work (no species makes
a medium # of medium-sized larvae)
Maximizing fitness in a changing world
Selection can result in a population adapting to changing
environmental conditions over many generations
However, individuals (and thus, individual genotypes) often face
conditions that change during their lifetime
Fluctuating conditions favor the ability to change your
phenotype on the run
- Note: this sounds like Lamarck, or “directed mutation” –
organisms change in response to conditions they experience
however, these changes are not inherited by offspring –
although the ability to change phenotype is heritable
Maximizing fitness in a changing world
Selection can result in a population adapting to changing
environmental conditions over many generations
However, individuals (and thus, individual genotypes) often face
conditions that change during their lifetime
Fluctuating conditions favor the ability to change your
phenotype on the run
Two ways an individual genotype can maximize its fitness in
fluctuating environments are:
(1) Bet-hedging
(2) Phenotypic plasticity
Bet-hedging
After a touchdown in football, a team has two choices:
1) kick for 1 extra point (almost 100% successful)
2) try to throw or carry ball into endzone for 2 extra points
 however, teams rarely ever go for two points... why?
Chicago Bears
Minnesota Vikings
Pittsburgh Steelers
Denver Broncos
Buffalo Bills
St. Louis Rams
Miami Dolphins
Cincinnati Bengals
Atlanta Falcons
Carolina Panthers
Arizona Cardinals
Green Bay Packers
Detroit Lions
Baltimore Ravens
Jacksonville Jaguars
Washington Redskins
New York Jets
New England Patriots
New York Giants
Cleveland Browns
Seattle Seahawks
Indianapolis Colts
Tennessee Titans
Kansas City Chiefs
New Orleans Saints
100
100
100
100
100
100
100
100
50
50
40
33
33
25
25
0
0
0
0
0
0
0
0
0
0
% success at attempted 2-point
conversions by NFL team
- variance in success for 2-point
conversions is extremely high
- most teams either complete 100%
or 0% of attempts
 thus, high chance that instead of
a sure-thing 1 point, you end up with
nothing
Taking the guaranteed 1 point is termed
bet-hedging: give up the chance for
more points, to ensure that you get
something no matter what
Bet-hedging genotypes
Bet-hedging strategies increase the growth rate of a genotype
by decreasing fitness variance between generations
- a bet-hedging genotype trades a reduction in fitness
during good seasons for an advantage in bad seasons
This way, you avoid complete wipe-outs
- over many generations, this strategy will always result in
the greatest growth rate for a genotype (how fast its alleles
rise in frequency)
- out-competes genotypes that do great in good years, but
bust during bad years
Bet-hedging dispersal strategy in Alderia
My slugs employ a bet-hedging strategy to make sure some of
their offspring disperse to find new seaweed patches, while
others stay close to home
drift for days until they locate
the seaweed that adults eat
tiny, swimming larvae
either...
two-thirds
one-third
settle immediately, no
matter what’s nearby
Bet-hedging germination in plants
Many plants produce a mixture of seeds: some germinate and
start to grow after one winter, while others don’t germinate
until they have experienced two winters
2009
2010
2011
This scatters offspring in time – if there is a drought, odds
are good that at least some offspring will survive by sleeping
through it
However, cannot exploit a really good year by having all seeds
germinate when it’s nice and rainy
Phenotypic plasticity
An individual can regulate its phenotype in response to cues
that may indicate impending changes in the environment
- Is winter coming?? Is a predator nearby??
This is phenotypic plasticity, the condition-sensitive
expression of alternative phenotypes
- a phenotype may show a continuous variation in response
to an environmental factor (such as temperature)
- phenotypic plasticity is itself a genetically variable trait,
and can evolve in response to natural selection
Phenotypic plasticity 1: Inducible defenses
Rather than invest initially in energetically costly defenses, an
organism can wait until it senses a threat
- only produce defenses (spines, toxins) when danger is near
Sort of like-- start out life as a fast-growing grass, but if you
sense danger, turn into a prickly cactus
summer
or, change color
with the seasons
to always blend
in, even when the
background
changes around
you
winter
snowshoe hare
Phenotypic plasticity 1: Inducible defenses
Colonies of a marine animal called a bryozoan grow spines
when they smell a predatory sea slug nearby
colony
smells a
sea slug
1-2 days later
Phenotypic plasticity 1: Inducible defenses
Example: mosquito larvae normally eat the single-celled
protozoan Lambornella
- Protozoans that smell nearby
mosquito larvae in time can
turn into “death spheres”
- burrow into the larvae,
explode them from within!
Lambornella
Life-history evolution: Why do we age?
The optimal life history might be immortality, but everything
shows less reproduction and higher mortality over time (age)
- so why don’t we evolve a “solution” to aging?
Two possibilities:
1) Constraint – we lack any remaining genetic variation to
respond to selection against aging
2) Trade-off – we trade off getting old and dying in exchange
for a reproductive advantage in our youth
Life-history evolution: Why do we age?
Hypothesis 1: Rate-of-living
- says DNA + tissue damage is caused by metabolism
- faster you metabolize, faster you age
- lifespan of some animals is doubled on a starvation diet
Thus, this hypothesis predicts we age because we lack additive
genetic variation to evolve better repair systems
- however, this hypothesis was not supported by:
- comparisons of metabolic rate across mammals
(no connection between life span and metabolic rate)
- artificial selection expts showing lifespan can double in
Drosophila in response to selection for late reproduction
Life-history evolution: Why do we age?
Hypothesis 1: Rate-of-living
May instead be due to # of cell divisions that can be completed
proposed that the progressive loss of telomeres from end of
chromosomes limits # of possible cell divisions, hence lifespan
- again, not supported by experimental studies
 most research indicates organisms can evolve longer lives
than what they normally express
- this implies a long life is not necessarily favored by
natural selection
Life-history evolution: Why do we age?
Hypothesis 2: Trade-off between reproduction & repair
Proposes that damage could be perfectly repaired, but at too
great a cost to early reproduction
- selection favors investment in reproduction over repair
- too costly to invest in fixing problems when young, even
though it would lead to a much longer life
Mutations that increase early reproduction at a cost of shorter
life are favored under natural conditions in flies and worms
Life-history evolution: Why do we age?
% survival
Flies homozygous for the methuselah allele live 35% longer
than wild-type flies
However, double-mutants lay fewer eggs early in life, leading to
reduction in total lifetime reproduction
 thus, methuselah allele trades off early reproduction for
long life and resistance to environmental stress