Download Lecture #K5 – Population Ecology, continued – Dr

Lecture #K5 – Population Ecology, continued – Dr. Kopeny
4/22 lecture
No population can continue to
increase exponentially indefinitely
Environmental resistance:
•Environment imposes limits on population
growth
•Food; water; disease; shelter from
elements, predators…...
Carrying capacity (K):
•Theoretical maximum population size that
can be maintained indefinitely (assumes
unchanging environment)
•In reality, K changes with changes in
environmental conditions
Logistic population growth:
•Populations can be modeled taking
carrying capacity of environment into
account using the “logistic growth equation”
The term (K-N)/K causes growth
in the simulated population to
respond to environmental
resistance
•When N is small compared to K,
[(K-N)/K] is close to 1 and growth is
nearly exponential
•When N is large compared to K,
[(K-N)/K] approaches 0, as does
population growth
Number of Individuals (N)
•dN/dt = rN [(K-N)/K]
Time
Some assumptions and simplifications
of the logistic model are either not true
for most populations or do not apply
equally to all populations
•Each individual added to a population at a low
level (N) has the same negative effect on
population growth rate at low population at a
high level (N)
•Each individual exerts its negative effects
immediately at birth
•All individuals have equal effect on the
population
•Populations approach carrying capacity
smoothly – don’t overshoot it
•Carrying capacity is constant
How well does the logistic growth model fit the growth of real populations?
Experimental populations (bacteria, yeast, Paramecia…)
•Some show sigmoidal growth fairly well, but conditions do not approximate nature
(predators, competitors lacking).
•Some, not all, experimental populations stabilize at some carrying capacity, and
most experimental populations deviate unpredictably from a smooth sigmoidal
curve
Natural populations
•Introduced populations and decimated, recovering populations show growth
patterns that generally support the concept of carrying capacity that underlies
logistic population growth
Logistic Population Growth
http://www.pinnipeds.fsnet.co.uk/species/species.htm
Raven & Johnson 1999
Raven & Johnson 1999
Logistic Population Growth
– Overshooting K
•Lag time in many populations before
negative effects of increasing
population are realized
•Hypothetical example: food becomes
limiting, but birthrate not immediately
affected because females use energy
reserves to continue producing eggs
for a period; population may then
overshoot carrying capacity
•Real life: In many of the populations
that show sigmoidal-type growth, they
oscillate around K, or at least
overshoot it the first time
Number of sheep (in thousands)
A fur seal population on St. Paul Island, Alaska The numbers of male fur seals with
harems were reduced to very low numbers due to hunting until 1911. After hunting was
banned, the population increased dramatically and now oscillates around an equilibrium
number, presumably the islands carrying capacity for this species
(Campbell 2000)
(Keeton & Gould 1993)
Growth curve of the sheep population of Australia.
Smooth curve is the hypothetical curve about which real
curve fluctuates
Population Growth & Life Histories*
•Conditions of high population density may favor
life history traits different from those favored at low
population density
•High population size and life history
•High population size; limited resources, slow
or zero population growth
•Traits favored may be those that enable
organisms to survive and reproduce with few
resources
•Competitive ability and high efficiency at
resource use may be favored in populations
that tend to remain at or near their carrying
capacity
•Low population size and life history
*
Life history
•Low population size; abundant resources,
rapid population growth
•Life history of an organism includes
birth, growth to reproductive
maturity, reproduction, and death
•Traits favored may be those that promote
rapid reproduction; ie high fecundity, early
maturity; efficiency of resource use not as
important
•“Life history traits” are
characteristics that affect an
organisms schedule of reproduction
and death.
Life History
•Life history of an organism includes birth,
growth to reproductive maturity, reproduction,
and death
•“Life history traits” are characteristics that affect
an organisms schedule of reproduction and
death.
•Life history of any individual will include these
traits;
-size & energy supply at birth
-rate and pattern of growth and
development
-number and timing of dispersal events
-number and timing of reproductive events
-number, size and sex ratio of offspring
-age at death
Flowering stalks of century plants (Agave
shawii). Copyright G. J. James/BPS.
•Life History varies among organisms, lineages,
based on variation in the allocation of time,
effort, energy, etc, to activities and stages from
birth, growth to maturity, reproduction, death
•Consider the importance of life history traits in
explaining demographic populations
statistics…age-specific fecundity, mortality…
Salmon spawning. Chugack National Forest,
AK. Copyright J. Robert Stottlemyer/BPS.
•“r-Selected populations”
likely to be found in variable
environments in which
population densities
fluctuate, or in “open”
habitats where individuals
likely to face little
competition
•“K-selected populations”
likely to be living at a
density near the limit
imposed by their resources
•Life history traits do often
vary in ways shown in table
•No demonstration of direct
relationship between
population growth rate and
specific life history traits;
concepts of r and K
selection are mainly useful
as hypothetical models
Population ecology and the evolution
of life history traits
•Because of the varying pressures of natural
selection, life histories show high variability
•among species and higher taxa
•among populations within species
•among individuals within a population
•within individuals, depending on
environmental conditions, availability of
mates; consider the adaptiveness of
plasticity in life history traits
•Patterns exist in the way in which life history
traits vary
•Life histories often vary in parallel with
environmental patterns
•Life histories often vary with respect to
each other (eg, delayed maturity & high
parental investment tend to correlate with
low fecundity and low mortality); such
relationships between life history traits
often reflect “trade-offs”…
Relationship between adult mortality and annual
fecundity in 14 bird species Birds with high
probability of dying during any given year usually
raise more offspring each year than those with a low
probability of dying. Wandering albatross; lowest
fecundity (~.2 offspring/yr – single surviving offspring
every 5 yrs) & lowest mortality. Tree sparrow; >50%
chance of dying from one breeding season to
another, produces average of 6 offspring per year
Organisms have finite resources to invest in
components of their life history; Trade-offs
between investments in reproduction and
survival are a consequence
•Selection favors (heritable) life history traits that
allow individuals to maximize lifetime
reproductive success; these traits will become
more common in a population
•Natural selection can not simultaneously
“maximize” all the life history traits that can
potentially contribute to the greatest lifetime
reproductive output, because organisms have
finite resources to invest; this mandates tradeoffs.
•Trade-offs occur between:
-number & size of young;
-number of young & parental care per young;
-reproduction and growth;
-reproduction and survival;
-current reproduction and future reproduction
--between investing in current reproduction and
future reproduction
Experimental manipulation demonstrates
trade-off between investing in current
reproduction and survival Manipulating
fecundity of female seed beetles by denying
access to males or egg-laying sites causes a
trade off in adult longevity and fecundity
Experimental manipulation
demonstrates trade-off between
investing in current reproduction and
survival Manipulating clutch size in
collared flycatchers (add or remove eggs)
results in direct trade off between number
of chicks raised that year and the next
year’s fecundity (no effect of current
fecundity on adult survival in this study)
Populations dynamics may be influenced by factors operating independent of
population density, or in a manner that is dependent on population density.
Density-independent factors Factors that affect per capita birth rate (b) or per capita death
rate (d), with the degree of the effect not influenced by (dependent on), population density
•Typically abiotic, often weather-related; e.g. in insects, winters kill off all individuals except
eggs and dormant larvae
•Often random (unpredictable) e.g., blizzard, flood, fire
•Effects may be indirectly related to density; e.g., social animals often able to endure weather
by collective behavior -- sheep huddling in snow storm
Density-dependent factors Factors that affect the per capita birth rate (b) or per capita death
rate (d), with the degree of the effect influenced by (dependent on), population density
•Important density dependent factors; Competition,
predation, disease
(Solomon et. al. 1999)
-increasing density may attract predators (more
successful, efficient, hunting prey at high density)
-increasing density may increase foster spread of
contagious disease
-increasing density may lead to depleted food
supplies
Effects are proportional to population density; Densitydependent factors exert stronger effect as population
increases
Fire may constitute a densityindependent factor for some populations
•12 Bahamian islands; all
islands have native spider
populations, 4 have lizards, 8
do not have lizards
•Lizards introduced in
enclosures on 4 islands
without native lizard
populations.
•After 7 years, spider densities
were higher in lizard-free
islands (enclosures).
Effect of lizard presence on spider density.
Tropical islands with lizards typically have few
spiders. Spiller and Schoener (UC-Davis) tested
the effect of presence of lizards on spider
population density on Bahamian Islands
•Species diversity of spiders
was also greater on lizard free
islands.
•Due to predation (lizards eat
spiders), or competition
(lizards and spiders compete
for insect food)?
Solomon et. al. 1999
Hypothetical population
dynamics in regulated
population. In these
models, if birth or death rates
or both are density
dependent, population
responds to increases or
decreases in density by
returning toward equilbrium
density (zero positive or
negative growth
Population “Regulation” and Reality
A regulated population is one whose dynamics are influenced primarily
by density-dependent factors
Regulated populations experience interactions between density and
carrying capacity
In reality, many populations are probably affected by both densitydependent and density-independent factors
Number of song sparrows
on Mandarte Island (B.C.)
is a consequence of
density-independent
(winter weather) and
density dependent factors