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Chapter 36 Population Ecology
 Individual emperor penguins face the rigors of the
Antarctic climate and have special adaptations,
including a
– downy underlayer of feathers for insulation and
– thick layer of fat for energy storage and insulation.
 The entire population of emperor penguins reflects
group characteristics, including the
– survivorship of chicks and
– growth rate of the population.
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POPULATION STRUCTURE
AND DYNAMICS
 Population ecologists study natural population
– structure and
– dynamics.
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36.1 Population ecology is the study of how and
why populations change
 A population is a group of individuals of a single
species that occupy the same general area.
 Individuals in a population
– rely on the same resources,
– are influenced by the same environmental factors, and
– are likely to interact and breed with one another.
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36.1 Population ecology is the study of how and
why populations change
 A population can be described by the number and
distribution of individuals.
 Population dynamics, the interactions between biotic
and abiotic factors, cause variations in population
sizes.
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36.1 Population ecology is the study of how and
why populations change
 Population ecology is concerned with
– the changes in population size and
– factors that regulate populations over time.
 Populations
– increase through birth and immigration to an area and
– decrease through death and emigration out of an area.
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36.2 Density and dispersion patterns are
important population variables
 Population density is the number of individuals of
a species per unit area or volume.
 Examples of population density include the
– number of oak trees per square kilometer in a forest or
– number of earthworms per cubic meter in forest soil.
 Ecologists use a variety of sampling techniques to
estimate population densities.
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36.2 Density and dispersion patterns are
important population variables
 Within a population’s geographic range, local
densities may vary greatly.
 The dispersion pattern of a population refers to the
way individuals are spaced within their area.
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36.2 Density and dispersion patterns are
important population variables
 Dispersion patterns can be clumped, uniform, or
random.
– In a clumped pattern
– resources are often unequally distributed and
– individuals are grouped in patches.
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Figure 36.2A Clumped dispersion of ochre sea stars at low tide
36.2 Density and dispersion patterns are
important population variables
 In a uniform pattern, individuals are
– most likely interacting and
– equally spaced in the environment.
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Figure 36.2B Uniform dispersion of sunbathers at Coney Island
36.2 Density and dispersion patterns are
important population variables
 In a random pattern of dispersion, the individuals in
a population are spaced in an unpredictable way.
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Figure 36.2C Random dispersion of dandelions
36.3 Life tables track survivorship in populations
 Life tables track survivorship, the chance of an
individual in a given population surviving to various
ages.
 Survivorship curves plot survivorship as the
proportion of individuals from an initial population
that are alive at each age.
 There are three main types of survivorship curves.
– Type I
– Type II
– Type III
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Table 36.3
Percentage of survivors (log scale)
Figure 36.3 Three types of survivorship curves
100
I
10
II
1
III
0.1
0
50
Percentage of maximum life span
100
36.4 Idealized models predict patterns of
population growth
 The rate of population increase under ideal
conditions is called exponential growth. It can be
calculated using the exponential growth model
equation, G = rN, in which
– G is the growth rate of the population,
– N is the population size, and
– r is the per capita rate of increase (the average
contribution of each individual to population growth).
 Eventually, one or more limiting factors will restrict
population growth.
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Figure 36.4A Exponential growth of rabbits
Population size (N)
500
450
400
350
300
250
200
150
100
50
0
0 1 2 3 4 5 6 7 8 9 10 11 12
Time (months)
Table 36.4A
36.4 Idealized models predict patterns of
population growth
 The logistic growth model is a description of
idealized population growth that is slowed by limiting
factors as the population size increases.
 To model logistic growth, the formula for exponential
growth, rN, is multiplied by an expression that
describes the effect of limiting factors on an
increasing population size.
 K stands for carrying capacity, the maximum
population size a particular environment can sustain.
(K  N)
G = rN
K
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Breeding male fur seals
(thousands)
Figure 36.4B Logistic growth of a population of fur seals
10
8
6
4
2
0
1915
1925
1935
Year
1945
Number of individuals (N)
Figure 36.4C Logistic growth and exponential growth compared
G
 rN
K
G
0
Time
(K  N)
 rN K
36.5 Multiple factors may limit population growth
 The logistic growth model predicts that population
growth will slow and eventually stop as population
density increases.
 At increasing population densities, densitydependent rates result in
– declining births and
– increases in deaths.
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Mean number of offspring per female
Figure 36.5A Declining reproductive success of song sparrows (inset) with increasing population density
6
5
4
3
2
1
0
0
10
20
30
40
50
60
70
80
Density of females
Data from P. Arcese et al., Stability, Regulation, and the Determination of Abundance
in an Insular Song Sparrow Population. Ecology 73: 805–882 (1992).
36.5 Multiple factors may limit population growth
 Intraspecific competition is
– competition between individuals of the same species for
limited resources and
– is a density-dependent factor that limits growth in natural
populations.
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36.5 Multiple factors may limit population growth
 Limiting factors may include
– food,
– nutrients,
– retreats for safety, or
– nesting or denning sites.
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36.5 Multiple factors may limit population growth
 In many natural populations, abiotic factors such as
weather may affect population size well before
density-dependent factors become important.
 Density-independent factors are unrelated to
population density. These may include
– fires,
– storms,
– habitat destruction by human activity, or
– seasonal changes in weather (for example, in aphids).
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Number of aphids
Figure 36.5C Weather change as a density-independent factor limiting aphid population growth
Exponential
growth
Apr May Jun
Sudden
decline
Jul
Aug Sep Oct Nov Dec
Month
36.6 Some populations have “boom-and-bust”
cycles
 Some populations fluctuate in density with regularity.
 Boom-and-bust cycles may be due to
– food shortages or
– predator-prey interactions.
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160
Snowshoe hare
120
9
Lynx
80
6
40
3
0
0
1850
1875
1900
Year
1925
Lynx population size
(thousands)
Hare population size
(thousands)
Figure 36.6 Population cycles of the snowshoe hare and the lynx
36.7 EVOLUTION CONNECTION: Evolution
shapes life histories
 The traits that affect an organism’s schedule of
reproduction and death make up its life history.
 Key life history traits include
– age of first reproduction,
– frequency of reproduction,
– number of offspring, and
– amount of parental care.
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36.7 EVOLUTION CONNECTION: Evolution
shapes life histories
 Populations with so-called r-selected life history
traits
– produce more offspring and
– grow rapidly in unpredictable environments.
 Populations with K-selected traits
– raise fewer offspring and
– maintain relatively stable populations.
 Most species fall between these two extremes.
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36.7 EVOLUTION CONNECTION: Evolution
shapes life histories
 A long-term project on life histories
– studied guppy populations,
– provided direct evidence that life history traits can be
shaped by natural selection, and
– demonstrated that questions about evolution can be
tested by field experiments.
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Guppies:
Larger at
sexual maturity
Experiment:
Transplant
guppies
Results
Pool 3
Pools with killifish
but no guppies
prior to transplant
Pool 2
Predator: Pikecichlid;
preys on large guppies
Guppies: Smaller at
sexual maturity
Hypothesis: Predator feeding preferences caused difference in life history
traits of guppy populations.
Mass of guppies
at maturity (mg)
Pool 1
Predator: Killifish;
preys on
small
guppies
185.6
200
161.5
160
120
80 67.5 76.1
40
Age of guppies
at maturity (days)
Figure 36.7 The effect of predation on the life history traits of guppies
100
85.7 92.3
80
60 48.5 58.2
40
20
Males
Males
Females
Females
Control:
Guppies from pools with
pike-cichlids as predators
Experimental:
Guppies transplanted to pools
with killifish as predators
36.8 Principles of population ecology have
practical applications
 Sustainable resource management involves
– harvesting crops and
– eliminating damage to the resource.
 The cod fishery off Newfoundland
– was overfished,
– collapsed in 1992, and
– still has not recovered.
 Resource managers use population ecology to
determine sustainable yields.
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Yield (thousands of metric tons)
Figure 36.8 Collapse of northern cod fishery off Newfoundland
900
800
700
600
500
400
300
200
100
0
1960
1970
1980
1990
2000
THE HUMAN POPULATION
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36.9 The human population continues to increase,
but the growth rate is slowing
 The human population
– grew rapidly during the 20th century and
– currently stands at about 7 billion.
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100
80
10
Population increase
8
60
6
40
4
Total population size
20
1500 1550 1600 1650 1700 1750 1800 1850 1900 1950 2000 2050
Year
2
0
Total population (in billions)
Annual increase (in millions)
Figure 36.9A Five centuries of human population growth, projected to 2050
36.9 The human population continues to increase,
but the growth rate is slowing
 The demographic transition
– is the shift from high birth and death rates
– to low birth and death rates, and
– has lowered the rate of growth in developed countries.
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Figure 36.9B Demographic transition in Mexico
Birth or death rate
per 1,000 population
50
40
30
Rate of
increase
20
10
Birth rate
Death rate
0
1900 1925 1950 1975 2000 2025 2050
Year
36.9 The human population continues to increase,
but the growth rate is slowing
 In the developing nations
– death rates have dropped,
– birth rates are still high, and
– these populations are growing rapidly.
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Table 36.9
36.9 The human population continues to increase,
but the growth rate is slowing
 The age structure of a population
– is the proportion of individuals in different age groups and
– affects the future growth of the population.
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36.9 The human population continues to increase,
but the growth rate is slowing
 Population momentum is the continued growth that
occurs
– despite reduced fertility and
– as a result of girls in the 0–14 age group of a previously
expanding population reaching their childbearing years.
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Age
Figure 36.9C Population momentum in Mexico due to increased proportion of women of childbearing age
80+
75–79
70–74
65–69
60–64
55–59
50–54
45–49
40–44
35–39
30–34
25–29
20–24
15–19
10–14
5–9
0–4
2012
1989
Male
6
5
4
3
Male
Female
2
1
0
1
2
3
4
5 6
Population in millions
Total population size = 83,366,836
Adapted from International Data Base, U.S. Census Bureau (2013).
2035
5
4
3
Male
Female
2
1
0
1
2
3
4
5
Estimated population in millions
Total population size = 114,975,406
5
4
Female
3
2
1
0
1
2
3
4
5
Projected population in millions
Total population size = 139,457,070
36.10 Age structures reveal social and economic
trends
 Age-structure diagrams reveal
– a population’s growth trends and
– social conditions.
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Figure 36.10 Age structures for the United States in 1985, 2010 (estimated), and 2035 (projected). Baby boom after war (tan)
will result in older population structure with stress on social security and medicaid.
Age
Birth years
1989
Male Female
85+
before 1905
80–84
1905–1909
75–79
1910–14
70–74
1915–19
65–69
1920–24
60–64
1925–29
55–59
1930–34
50–54
1935–39
45–49
1940–44
40–44
1945–49
35–39
1950–54
30–34 1955–59
25–29 1960–64
20–24 1965–69
15–19
1970–74
1975–79
10–14
1980–84
5–9
0–4
1985–89
Birth years
2012
Male Female
before 1928
1928–32
1933–37
1938–42
1943–47
1948–52
1953–57
1958–62
1963–67
1968–72
1973–77
1978–82
1983–87
1988–92
1993–97
1998–2002
2003–2007
2008–2012
Birth years
2035
Male Female
before 1951
1951–55
1956–60
1961–65
1966–70
1971–75
1976–80
1981–85
1986–90
1991–95
1996–2000
2001–05
2006–10
2011–15
2016–20
2021–25
2026–30
2031–35
12 10 8 6 4 2 0 2 4 6 8 10 12
12 10 8 6 4 2 0 2 4 6 8 10 12
12 10 8 6 4 2 0 2 4 6 8 10 12
Population in millions
Total population size = 246,819,230
Estimated population in millions
Total population size = 313,847,465
Projected population in millions
Total population size = 389,531,156
Data from International Data Base, U.S. Census Bureau website, (2013).
36.11 An ecological footprint is a measure of
resource consumption
 The U.S. Census Bureau projects a global
population of
– 8 billion people within the next 20 years and
– 9.5 billion by mid-21st century.
 Do we have sufficient resources to sustain 8 or 9
billion people?
 To accommodate all the people expected to live on
our planet by 2025, the world will have to double
food production.
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36.11 CONNECTION: An ecological footprint is a
measure of resource consumption
 An ecological footprint is an estimate of the
amount of land required to provide the raw materials
an individual or a nation consumes, including
– food,
– fuel,
– water,
– housing, and
– waste disposal.
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36.11 CONNECTION: An ecological footprint is a
measure of resource consumption
 The United States
– has a very large ecological footprint, much greater than
its own land, and
– is running on a large ecological deficit.
 Some researchers estimate that
– if everyone on Earth had the same standard of living as
people living in the United States,
– we would need the resources of 4.5 planet Earths.
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Figure 36.11B
Ecological Footprint
(global hectares per person)
8
7
6
5
4
3
2
1
World
average
Earth’s
biocapacity
0
Adapted from Living Planet Report 2012: Biodiversity, Biocapacity, and Better Choices, World Wildlife Fund (2012).