1. Overview: Counting Sheep
Soay sheep were introduced to Hirta Island in 1932
Opportunity to study changes in population on isolated island with abundant food and no predators
Population ecology: study of populations in relation to environment; influences on density, distribution, age structure, population size
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2. Population Ecology
Chapter 53

3. Population density, dispersion, and demographics
Population: group of individuals of one species, living in an area
Density: number of individuals per unit area or vol.
Immigration and emigration
Impractical to count all individuals
Sampling techniques, as mark-recapture method
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4. Deaths and emigration remove individuals from a population.
Figure 53.3
Births
Deaths
Deaths and emigration remove individuals from a population.
Births and immigration add individuals to a population.
Figure 53.3 Population dynamics.
Immigration
Emigration 4

5. Patterns of Dispersion
Dispersion: pattern of spacing among individuals
Environmental and social factors influence spacing
Clumped: resource availability, behavior
Uniform: social interactions such as territoriality, defense of a space against other individuals
Random: absence of strong attractions or repulsions
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6. (a) Clumped (b) Uniform (c) Random
Figure 53.4
(a) Clumped
(b) Uniform
Figure 53.4 Patterns of dispersion within a population’s geographic range.
(c) Random 6

7. Demographics Demography: study of vital statistics of a population
Death rates and birth rates
Life table: age-specific summary of survival pattern; follows fate of a cohort (individual)
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8. Example of a Life Table

9. Survivorship Curve for Belding’s ground squirrels
Figure 53.5
Survivorship Curve for Belding’s ground squirrels
1,000
100
Number of survivors (log scale)
Females 10
Males
Figure 53.5 Survivorship curves for male and female Belding’s ground squirrels. 1 2 4 6 8 10
Age (years) 9

10. Survivorship Curves Type II – constant death rate over lifespan
Type I – low death rates early, middle; death rates increase among old age
Large mammals,
Produce few offspring but give good care
Type III – high death rate for young; few survive early dieoff
Large numbers of offspring, little or no care of young
Plants, fish, marine invertebrates
Type II – constant death rate over lifespan
Rodents, invertebrates, some lizards
Many species don’t fall into any of these categories
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11. Survivorship Curves are of three types
Figure 53.6
Survivorship Curves are of three types
1,000 I
100 II
Number of survivors (log scale) 10
Figure 53.6 Idealized survivorship curves: Types I, II, and III.
III 1 50
100
Percentage of maximum life span 11

12. Reproductive Rates
For species with sexual reproduction, demographers often concentrate on females
Reproductive table or fertility schedule = age-specific summary of reproductive rates
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13. Exponential model of population growth
Useful to study population growth in an idealized situation
Per capita rate of increase
Often, migration is ignored
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14. Expected number of births/deaths per year
B  bN
D  mN
b = annual per capita birth rate
m = per capita death rate
N = population size
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15. r = per capita rate of increase
r  b  m
Zero population growth (ZPG) when r  0
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16. Exponential Population Growth
Population increase under ideal conditions
Rate of increase at maximum – rmax
Exponential population growth is
Exponential growth results in J-shaped curve dN dt 
rmaxN
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17. 2,000 dN dt = 1.0N 1,500 dN dt = 0.5N Population size (N) 1,000 500 5
Figure 53.7
Population growth predicted by the exponential model.
2,000
dN dt
= 1.0N
1,500
dN dt
= 0.5N
Population size (N)
1,000
500
Figure 53.7 5 10 15
Number of generations 17

18. Exponential growth in the African elephant population
Figure 53.8
Exponential growth in the African elephant population
8,000
6,000
Elephant population
4,000
2,000
Figure 53.8 of Kruger National Park, South Africa.
1900
1910
1920
1930
1940
1950
1960
1970
Year 18

19. Logistic model
Describes how a population grows more slowly as it reaches its Carrying Capacity
Exponential growth cannot be sustained
More realistic model incorporates carrying capacity (K); produces sigmoid (S-shaped) curve
Carrying capacity varies with abundance of resources
Per capita rate of increase declines as carrying capacity reached (as N approaches K)
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20. Table 53.3 Logistic Growth of a Hypothetical Population (K = 1,500)20

21. ( ) Exponential growth 2,000 dN dt = 1.0N 1,500 K = 1,500
Figure 53.9
Exponential growth
Population growth predicted by the logistic model.
2,000 dN dt
= 1.0N
1,500
K = 1,500
Logistic growth dN dt (
1,500 – N
1,500 )
Population size (N)
= 1.0N
1,000
Figure 53.9
Population growth begins slowing here.
500 5 10 15
Number of generations 21

22. Figure 53.10
In a constant environment lacking competitors and predators, how well do these populations fit the logistic growth model?
1,000
180
150
800
Number of Daphnia/50 mL
120
Number of Paramecium/mL
600 90
400 60
200 30 5 10 15 20 40 60 80
100
120
140
160
Figure 53.10
Time (days)
Time (days)
(a) A Paramecium population in the lab
(b) A Daphnia population in the lab 22

23. Logistic Model and Real Populations
Some populations overshoot K
Some populations fluctuate greatly; difficult to define K
Logistic model assumes instant adjustment to growth
Logistic model can be used to estimate possible growth
Conservation biologists use model to estimate critical size below which populations may become extinct
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24. Life history traits are products of natural selection
Life history comprises traits that affect schedule of reproduction and survival
Age at which reproduction begins
How often organism reproduces
How many offspring are produced during each reproductive cycle
Life history traits – evolutionary outcomes reflected in development, physiology, behavior
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25. Evolution and Life History Diversity
Species that exhibit semelparity, or big-bang reproduction, reproduce once and die
Highly variable environments favor semelparity
Century plant or Agave
Other species show iteroparity (repeated reproduction)
Dependable environments favor iteroparity
Some Lizards
Organisms have finite resources – may lead to trade-offs
Trade-off between survival & paternal care in kestrels
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26. Parents surviving the following winter (%)
Figure 53.13
How does caring for offspring affect parental
survival in kestrels?
RESULTS
100
Male
Female 80 60
Parents surviving the following winter (%) 40
Figure Inquiry: 20
Reduced brood size
Normal brood size
Enlarged brood size 26

27. Trade offs between reproduction and survival
Some plants produce large number of small seeds, ensuring that some will grow & eventually reproduce
Other plants produce moderate number of large seeds that provide large store of energy that will help seedlings become established
r-selection (density-independent) – selects for life history traits that maximize reproduction
K-selection (density-dependent) – selects for life history traits sensitive to population density
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28. (b) Brazil nut tree (right) and seeds in pod (above)
Figure 53.14
(a) Dandelion
Figure Variation in the size of seed crops in plants.
(b) Brazil nut tree (right) and seeds in pod (above) 28

29. Density-dependent factors
Density-independent = birth and death rates do not change with population density
Density- dependent = birth and death rates do change with population density
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30. Density-dependent factors
Density-dependent birth and death rates
Negative feedback between population density and birth/death rates
Affected by competition for resources, territoriality, disease, predation, toxic wastes
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31. Birth or death rate per capita
Figure 53.15
When population density is low, b > m. As a result, the population grows until the density reaches Q.
When population density is high, m > b, and the population shrinks until the density reaches Q.
Equilibrium density (Q)
Birth or death rate per capita
Density-independent death rate (m)
Figure 53.15
Density-dependent birth rate (b)
Determining equilibrium for
population density.
Population density 31

32. Decreased reproduction at high population densities.
Figure 53.16
Decreased reproduction at high
population densities.
100 80 60
% of young sheep producing lambs 40
Figure 53.16 20
200
300
400
500
600
Population size 32

33. Population Dynamics
Focuses on complex interactions between biotic and abiotic factors that cause variation in population size
Long-term studies have challenged hypothesis that populations of large mammals are relatively stable
Weather and predators can affect population size
Moose population on Isle Royale
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34. Fluctuations in moose and wolf populations on Isle Royale, 1959–2008.
Figure 53.18 50 40 30 20 10
2,500
2,000
1,500
1,000
500
Wolves
Moose
Number of wolves
Number of moose
Figure 53.18
1955
1965
1975
1985
1995
2005
Year
Fluctuations in moose and wolf populations on Isle Royale, 1959–2008. 34

35. Population Cycles Some populations undergo regular boom-and-bust
Lynx populations follow 10-year boom-and-bust cycle of hare populations
Three hypotheses have been proposed
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36. Number of hares (thousands) Number of lynx (thousands)
Figure 53.19
Snowshoe hare
160
120 80 40 9 6 3
Number of hares (thousands)
Lynx
Number of lynx (thousands)
Figure Population cycles in the snowshoe hare and lynx.
1850
1875
1900
1925
Year 36

37. Hypothesis 1 Hare’s cycle follows cycle of winter food supply
If hypothesis correct, then cycles should stop if food supply is increased
Additional food was provided experimentally; whole population increased, but continued to cycle
Rejected!
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38. Hypothesis 2 Hare’s cycle driven by pressure from other predators
In study by field ecologists, 90% of hares were killed by predators
Second hypothesis supported!
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39. Hypothesis 3 Hare’s cycle linked to sunspot cycles
Sunspot activity affects light quality, which in turn affects quality of hares’ food
Good correlation between sunspot activity & population size
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40. How does food availability affect emigration and
Figure 53.20
How does food availability affect emigration and
foraging in a cellular slime mold?`
Immigration / Emigration – Dictyostelium amoebas can emigrate and forage better than individual amoebas
EXPERIMENT
Dictyostelium amoebas
Topsoil
Bacteria
200 m
Figure Inquiry:
Dictyostelium discoideum slug
Dictyostelium movement 40

41. Figure 53.21
Metapopulations – groups of populations linked by immigration and emigration
Aland
Islands ˚
EUROPE
Figure The Glanville fritillary: a metapopulation.
Glanville fritillary
Occupied patch
Unoccupied patch
5 km 41

42. Human population
Human population increased relatively slowly until about 1650, then began to grow exponentially
Global population now ~7 billion people
Though global population still growing, rate of growth began to slow during 1960s
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43. Human population (billions)
Figure 53.22 7 6 5 4 3 2 1
Human population (billions)
The Plague
Figure Human population growth (data as of 2009).
8000
BCE
4000
BCE
3000
BCE
2000
BCE
1000
BCE
1000 CE
2000 CE 43

44. Annual percent increase in the global human population (as of 2009).
Figure 53.23
2.2
2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
Annual percent increase in the global human population (as of 2009).
2009
Annual percent increase
Projected data
Figure 53.23
1950
1975
2000
2025
2050
Year 44

45. Regional Patterns of Population Change
To maintain stability, regional human population can exist in one of two configurations
ZPG = High birth rate – High death rate or
ZPG = Low birth rate – Low death rate
Demographic transition = move from first state to second state
Associated with increase in quality of health care and improved access to education
Most of current population growth concentrated in developing countries
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46. Age Structure
Important demographic factor in present and future growth trends
Relative number of individuals at each age
Diagrams can predict growth trends & help future planning
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47. Figure 53.24
Age-structure pyramids for the human population of three countries (2009).
Rapid growth
Afghanistan
Slow growth
United States
No growth
Italy
Male
Female
Age
85+
80–84
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
Male
Female
Age
85+
80–84
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
Male
Female
Figure 53.24 10 8 6 4 2 2 4 6 8 10 8 6 4 2 2 4 6 8 8 6 4 2 2 4 6 8
Percent of population
Percent of population
Percent of population 47

48. Infant Mortality and Life Expectancy
Figure 53.25
Infant Mortality and Life Expectancy 60 50 40 30 20 10 80 60 40 20
Infant mortality (deaths per 1,000 births)
Life expectancy (years)
Figure Infant mortality and life expectancy at birth in industrialized and less industrialized countries (data as of 2008).
Indus- trialized countries
Less indus- trialized countries
Indus- trialized countries
Less indus- trialized countries 48

49. Global Carrying Capacity
Predicted population of 7.810.8 billion in 2050
Carrying capacity of Earth for humans is uncertain
Average estimate is 10–15 billion
Ecological footprint – aggregate land and water area needed to sustain people
Countries vary greatly in footprint size and available ecological capacity
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50. Average per capita energy use
Figure 53.26
Average per capita energy use
Gigajoules
Figure Annual per capita energy use around the world.
> 300
150–300
50–150
10–50
< 10 50