Transcript Life history traits and tradeoffs

Tradeoffs Among Life History Traits
There are tradeoffs among different life history traits and
among the costs associated with them.
Without tradeoffs the logical direction for species to evolve
would be more of everything: more offspring, larger offspring
size, better survivorship and longer life.
The hypothesis of reproductive cost explains the tradeoffs
between increased reproduction and other aspects of the life
history. By extension, it also applies to other possible
tradeoffs.
Tradeoffs may occur in the behaviour, physiology, and
strategies of individuals, but may also involve balances
between parents and offspring, called `inter-generational', or
occur at the population level.
The idea of tradeoffs as an important life history argument
may be only 20 – 30 years old, but it is not new. From R.A.
Fisher's classic book The Genetical Theory of Natural
Selection (1930):
"It would be instructive to know not only by what
physiological mechanisms a just apportionment is made
between the nutriment devoted to the gonads and that
devoted to the rest of the parental organism, but also
what circumstances in the life-history and environment
would render profitable the diversion of a greater or
lesser share of the available resources towards
reproduction."
Compromises may occur among:
Individual traits:
a) current reproduction (measured as mx)
b) future reproduction (residual reproductive value,
Vx+1)
c) parental survival (measured by lx or px)
d) parental growth
e) parental condition
Inter-generation traits:
f) offspring growth
g) offspring condition
h) offspring survival
Population level traits:
i) number of offspring
j) size of offspring
All strategies are compromises between lx and mx. More
explicitly – the foundation of life history theory is the
hypothesis of reproductive cost. Any increase in present
reproduction (at least in an iteroparous species) is associated
with a decrease in future (or alternatively residual)
reproductive value, i.e. the expected contribution to future
generations resulting from all future bouts of reproduction.
The decrease could be either reduced fecundity in the future,
or reduced survivorship.
This can be represented in an equation for reproductive value
having two components: current reproduction and the value
of future reproduction (Vx+1) in a population which is
changing in size.
e  ra
Va  ma 
la
 rx
e
 x  a 1 lx mx

It is this negative correlation between reproductive effort in
the present and the value of future reproduction which makes
the optimization of timing and intensity of reproductive effort
possible.
If there weren't a negative correlation, then species would
maximize both current and future reproduction, as well as
beginning as early as possible and lasting as long through life
as possible.
The idea of reproductive cost is explained using the principle
of allocation:
An organism has a limited set of basic functions or needs
which must be met: these functions are usually classed as
maintenance, growth and reproduction.
1. Maintenance refers to baseline metabolism plus costs borne
to ensure survival, e.g. water regulation, resistance to
predation, competition or disease, etc. It does not include
any component of increase.
2. Growth refers to the energetic cost of increase.
3. Reproduction refers to costs of producing gametes, of
acquiring mates (including development of displays,
behaviours, etc.), of bearing the young, and of parental
care.
There are energetic costs associated with each function, and
clearly energy allocated to one function is not available for
the others. Thus there are reciprocal adjustments among
functions, and evolution should favor adjustments which
maximize fitness.
Variations in patterns of allocation among these functions
may be genetic or phenotypic, and may occur in many
factors important to fitness, including age of first
reproduction, temporal pattern of reproduction (the shape of
the mx curve; semelparity versus iteroparity, and the size of
mx.
We will explore data that examines evidence of tradeoffs
and adaptations evident in many of these variables.
Semelparity versus Iteroparity
It’s almost Shakespearean…
Whether to reproduce only once (i.e. semelparity or big-bang
reproduction), or whether to reproduce more moderately but
repeatedly (i.e. iteroparity).
Reproducing early, and using the big- bang approach, the
organism need not worry about possible effects on adult
survivorship. Caution can be “thrown to the winds”. The
generation time, G, will be considerably shortened, and R0
can be increased. This should clearly increase 'r'.
However, even if every litter were somewhat smaller, the
iteroparous species can have many such litters, and a much
larger number of offspring (R0) over a life cycle.
The answer (which is the better strategy) is not clear.
A comparison of strategies is part of Cole's (1954) classic
paper, and comes to what, at the outset, seems to be a shocking
conclusion. Here are the parameters of Cole’s comparison:
1) Assume that the semelparous species has perfect
survivorship to age 1 year, then reproduces, producing a
litter of size b.
2) Assume that the iteroparous species has perfect
survivorship, not only until it begins reproducing at age 1,
but also thereafter; it produces a litter of size b annually.
Now compare the population growth...
First the semelparous species. The exponential growth model:
Nt = N0 ert
if t = 1 year, and each female has a litter of size b, then the
growth equation can be re-written:
Nt/N0 = er = b
or
rs = ln (b)
The calculations for the iteroparous species involve another
infinite sum, with the approximate result that:
ri = ln (b+1)
Cole's way of stating this comparative result is clear and
concise:
“for an annual species, the absolute gain in intrinsic
population growth which could be achieved by
changing to the perennial reproductive habit
would be exactly equivalent to adding one
individual to the average litter size.”
Not only that, but the gain, logically, is a function of litter size
and the age of first reproduction, which aren't considered in
this basic comparison. The gain from changing to iteroparity
(when the litter size of the semelparous species is equal)
increases both with delay in first reproduction (i.e. increasing
) and with decreasing litter size.
Consider why…
If it takes one extra in the litter for a semelparous species to
keep up, that represents a bigger proportional increase in
reproductive effort when litter size is small than when it's
large.
Now consider the effects of changing . The general idea can
best be seen by comparing population size over time in
semelparous and iteroparous populations.
First in the comparison that produced the original result:
Time
0
1
2
3
4
Semelparity 1
b
b2
b3
b4
Iteroparity 1
b+1
b2 +2b+1
b3+3b2+3b+1 (b+1)4
Now, what happens if  were 2…
Time
0
1
2
Semelparity 1
b
Iteroparity 1
b+1
3
4
b2
2b+1
b2+4b+1
If alpha increased from 1 to 5 for both the iteroparous and
semelparous species being compared, then by the time
grandchildren are born in the semelparous species, the
iteroparous parent will have produced offspring at ages 6,7,8
and 9, each time with a litter of size b. That's clearly a bigger
advantage than accrued when alpha was 1. Cole showed the
general result in a graph:
Most semelparous species tend to have short pre-reproductive
periods. That minimizes the advantage that might be gained
by becoming iteroparous. A few examples make the basic
point. Annual plants (many weeds) and almost all insects
complete their life cycles in a single year, and most which do
not complete life cycles in 2 years instead (e.g. biennial plants
such as weedy thistles, teasel, onions, garlic).
Semelparous species also typically have very large litter sizes.
Many produce 106 eggs or more, e.g. Musca domestica, the
common housefly, oysters, or the salmon.
The problem can also be approached from the opposite point
of view. It is clearly advantageous, from an evolutionary view,
to increase the intrinsic rate of increase 'r', 'all else being
equal'. A change in 'r' could result from becoming iteroparous
while maintaining litter size, or from an increase in the
semelparous litter size.
Since either change could be equally effective, we can look at
the change in semelparous litter size required to achieve the
same 'r' as would be reached by switching to iteroparity while
just maintaining litter size.
Since Cole worked it out so nicely, I’ll use it even though it is
an animal example…
The change in litter size required can be dramatic. Take the
lowly tapeworm as an example:
The approximate daily litter size of the mature tapeworm is
100,000 eggs.
Including larval development time, the maturation time, or
alpha, is approximately 100 days.
If the tapeworm were to become indefinitely iteroparous, we
find that the equivalent semelparous litter size to achieve the
same growth rate would be about 800,000 (or an increase in
litter size by a factor of 8). The species is not, of course,
indefinitely iteroparous, and the required semelparous litter (or
litter size factor) size is not quite so large.
There are real situations which suggest a considerable
advantage (in an evolutionary sense) to iteroparity.
Effects of age of first reproduction
There is an approximately inverse relationship between
rmax and generation time (see the table below), which, if
perfect, would have indicated a constant R0 over a wide
variety of taxa. Generation time is also related to body size,
both in the maturation time and in the interval between births.
Both of these relationships are demonstrated in plots in the
text and below.
It's clear that instantaneous rates of increase would increase in
organisms with shorter generation times among whom R0 is
constant (and, thus, inversely related to body mass).
Even though the simple formula (ln R0/G) calculates only an
approximate r, it is apparent that a smaller generation time G
would increase the rate of increase.
Values for rmax, the generation time G, and their product as
an indication of potential growth rate
.
Taxon
Species
rmax
G
rxG
Bacteria E. coli
60.
.014
.84
Protazoa Paramecium aurelia 1.24
P. caudatum
.94
.40
.30
.508
.282
Insecta
Tribolium confusum 12
Calandra oryzae
.11
Eurostis hilleri
.01
Magicicada septendecim .001
80.
58.
110.
6050.
9.60
6.38
1.1
6.05
Mammalia Rattus norvegicus .015
Microsus agrestis
.013
Canis domesticus
.009
Homo sapiens
.0003
150.
171.
1000.
7000.
2.25
2.22
9.0
2.1
There are allometric relationships between many physical
and life history variables that have been measured. If we
take body mass, M, as the base variable, these relationships
seem to take the form of power laws. The general form,
taking Y as the dummy variable standing in for the many
others, is:
Y = Y0Mb
Normally these relationships are plotted after a log
transform, since they are then linear:
log Y = log Y0 + b log M
The b values seem always to be multiples of 0.25.
For heart rate versus mass, b = -0.25
For mass and basal metabolic rate b = 0.75
For mass and resource use b = 0.75
In birds, mass and both life span and reproductive maturity
scale with a b = 0.25.
There are many more examples, and in sum they have led to
an attempt to formulate a general theory: It is called the
Metabolic Theory of Ecology, and begins with the scaling
ideas you’ve just seen, then adds well-recognized
temperature-dependence of biological processes. The theory
then claims that life history characteristics are determined
by metabolic processes whose rates are determined by
scaling and absolute temperature.
These ideas are the subject of ongoing controversy.
Whatever the bases, you should now recognize that largebodied plants and animals will have low r values, slow
development, and different life history compromises than
small ones.
Example 1:
The California condor
Tradeoff between Reproductive Effort and Survivorship in
the California Condor
The California Condor is an endangered species very close
to extinction. Recent release of captive-raised condors
suggests there may be hope for the species.
In 1985 there were less than 10 breeding pairs remaining in
the wild; four years later (1989) this condor had gone extinct
in the wild. In 1987, anticipating this, the San Diego Zoo
initiated a captive breeding program.
Almost two decades before extinction in the wild, David
Mertz (1971) predicted that the species would be virtually
impossible to save, based both on the disappearance of its
native habitat as southern California became increasingly
urbanized, and on its demography.
The condor does not exhibit the demographic pattern usually
associated with birds, i.e. type II diagonal survivorship curve.
Instead,
1. it is very long-lived and has a very low reproductive rate.
2. The condor does not become reproductively mature until
at least 5 years old, and may not mature for twice that time.
3. California condors produce only a single egg every other
year, though most condors produce annual broods of 2 eggs
and some produce only a single egg each year.
4. While the mean lifespan is high, there is significant prereproductive mortality, somewhat concentrated in the first
year.
From these basic facts, we can construct a hypothetical life
table for the condor, and look for factors in it which may
explain the decline of the population.
1. We can, for purposes of calculations using this life table,
lump all pre-reproductive mortality and call survivorship
from birth to age  b.
2. Given the long lifespan, we can reasonably assume that
adult proportional survivorship is uniform through the
reproductive span. That proportional survivorship we'll
call p.
3. Since only a single egg is produced every other year, if
=5, we assign these eggs to the odd years. Since only half
of these eggs will be female, the mx we put in the life table
for years with reproduction is 1/2.
Now we can construct the life table…
Age x
lx
mx
lxmx
0...
5
6
7
8
9
...
b
bp
bp2
bp3
bp4
0
.5
0
.5
0
.5
0
b/2
0
bp2/2
0
bp4/2
Calculations for this life table:
The net replacement rate turns out to be the sum of a power
series, which, when p < 1, can be simplified to a formula:
R0 = lxmx = b/2 (1 + p2 + p4 + ...) = b/[2(1-p2)]
Now, to maintain the population, R0 must equal 1 (we'll
assume, given the low mx and observation of declining
numbers that we don't need to consider the potential for
growth). Then:
1 = b/[2(1-p2)]
b = 2(1-p2)
or
1-b/2 = p2
If b ~ 0 (very severe pre-reproductive mortality) then adult
mortality cannot be tolerated, p = 1 (adults must remain
immortal).
If juvenile survivorship is extremely high, b = 1, note that
adult survivorship must still be high, with a p = .7071.
If about half of juveniles survive to reproductive maturity,
then adult proportional survivorship must be .86.
The solid lines are the
observed demography of the
condor, and the dashed lines
represent the demography if
condors re-nest the year after a
nesting failure.
In actuality, the re-nesting rate
is only about 50% of nestling
mortality.
Since we're interested only in the narrow range 0 < b,
p < 1, we can closely approximate the mathematical parabola
by a straight line over that range. That isocline for R0 = 1
divides the plot into two regions.
Below that line R0 < 1, and the population declines; above the
isocline R0 > 1, and the population grows. Increase is possible
only with very high adult survivorship, and even with perfect
survivorship the population grows by only 15% per year due
to the extremely low reproductive rate.
Realistically the survivorship of mature adults must almost
certainly be higher than that for inexperienced juveniles, i.e.
p > b. Insert a diagonal line where p = b; only points
to the left of the diagonal are now realistic values for
survivorships. With this assumption the minimum adult
survivorship to maintain the population is p = .78.
The isocline for R0 = 1 is relatively 'shallow'. R0 is relatively
insensitive to changes in prereproductive survivorship; only
slight changes occur with relatively large shifts in b.
However, R0 is exquisitely sensitive to changes in p.
Mertz (1971) made two key points based on these
observations:
1) Even slight hunting or poaching of adult birds, could
take a tenuously stable population into a relatively rapid
decline.
2) The differing sensitivity also suggests an explanation for a
key management difficulty. Any disturbance of nesting
females will cause the nesting female to leave her eggs
for a period sufficient to frequently allow cooling and
mortality of the embryos. That behaviour - taking off
rather than defending the nest - is what might be expected
when juvenile (or egg) mortality can be tolerated (in a
quantitative sense) more than adult mortality. This is the
first indication of a tradeoff .
3) It might seem that this strategy is based solely on
maintenance of a high lx, but there is also pressure on mx.
The rate of egg production must remain very close to one
egg every other year; it is not tolerable to miss producing
an egg. Any decline in mx must be made up by an increase
in lx to maintain R0 = 1. With the already extreme demands
on survivorship, there is no room left in the demographic
pattern to enhance adult survivorship.
4) What about long maturation time? It might seem that if
birds simply started laying eggs earlier, that net
replacement rates would climb, and reduce the pressure on
survivorship. The condor is altricial; most altricial birds
have an alpha of approximately 2, far lower than the
minimum of 5 for the California condor.
There is little effect from changing  when the population is
stable or growing.
However, when the population is in decline (due to an
insufficient p) a decrease in  only accelerates the decline,
because the survivorship schedule shifts from b (low
sensitivity) to that insufficient p earlier.
The dashed lines are what would happen if the condor shifted
 to age 4. For growing populations the dashed lines lie below
the solid ones; equal growth (R0) could be achieved with
slightly lower p and b.
However, when the population is declining the dashed lines
lie above the solid ones.
All these facts make it apparent that game managers
attempting to protect the endangered California condor were
fighting a losing battle from the start. All they could do was
attempt to prevent as much non-natural mortality as possible
to protect p, and exert what little influence such managers
have over the expanding destruction of native habitat in
southern California.
It seems likely that only continuing release of birds from the
remaining zoo-raised population will keep the California
condor present in the natural world over the long term.
However, there are now (April 2009) 172 free condors in
California and Arizona (data retrieved from Wikipedia, so
open to question). The conservation goal is a total of at least
150 birds in each of two disjunct populations, with at least 15
breeding pairs in each. That would lead to the species being
downgraded to “threatened” from “endangered”.