1. Chapter 53 Population Ecology
Lecture Presentations by Nicole Tunbridge and Kathleen Fitzpatrick
© 2017 Pearson Education, Inc. 1

2. Concept 53.1: Biotic and abiotic factors affect population density, dispersion, and demographics
A population is a group of individuals of a single species living in the same general area
Described by their boundaries and size
Density is the number of individuals per unit area or volume
Dispersion is the pattern of spacing among individuals within the boundaries of the population

3. Density: A Dynamic Perspective
Density is the result of an interplay between processes that add individuals to a population and those that remove individuals
Immigration is the influx of new individuals from other areas
Emigration is the movement of individuals out of a population

4. Population Dynamics
Figure 53.3 Population dynamics

5. Patterns of Dispersion within a Population’s Geographic Range
Clumped
Uniform
Random
Figure 53.4 Patterns of dispersion within a population’s geographic range

6. Patterns of Dispersion
Environmental and social factors influence the spacing of individuals in a population
Most common pattern of dispersion is clumped, in which individuals aggregate in patches
Influenced by resource availability
Mating behavior and group defense against predators can also influence clumped dispersions
A uniform dispersion is one in which individuals are evenly distributed
Influenced by social interactions such as territoriality

7. Demographics
Biotic and abiotic factors influence birth, death, and migration rates of populations
Demography is the study of these vital statistics of a population and how they change over time

8. Life Tables
A life table is an age-specific summary of the survival and reproductive rates within a population
It is often made by following the fate of a cohort, a group of individuals of the same age
Males are often ignored when studying sexually reproducing species because only females produce offspring
The life table of female Belding’s ground squirrels reveals many things about this population
For example, it provides data on the proportions of females alive at each age and the number of female offspring produced per female

9. Life Table for Female Belding’s Ground Squirrels (Tioga Pass, in the Sierra Nevada of California)
Age (years)
Number Alive at Start of Year
Proportion Alive at Start of Year*
Death Rate†
Average Number of Female Offspring per Female
0-1
653
1.000
0.614
0.00
1-2
252
0.386
0.496
1.07
2-3
127
0.197
0.472
1.87
3-4 67
0.106
0.478
2.21
4-5 35
0.054
0.457
2.59
5-6 19
0.029
0.526
2.08
6-7 9
0.014
0.444
1.70
7-8 5
0.008
0.200
1.93
8-9 4
0.006
0.750
9-10 1
0.002
1.00
1.58
Table 53.1 Life table for female Belding’s ground squirrels (Tioga Pass, in the Sierra Nevada of California)
Data from P. W. Sherman and M. L. Morton, Demography of Belding’s ground squirrel, Ecology 65: (1984).
*Indicates the proportion of the original cohort of 653 individuals that are still alive at the start of a time interval.
†The death rate is the proportion of individuals alive at the start of a time interval that die during that time interval.

10. Survivorship Curves
A survivorship curve is a graphic way of representing the data in a life table
The survivorship curve for Belding’s ground squirrels shows a relatively constant death rate

11. Survivorship Curve for Female Belding’s Ground Squirrels
Figure 53.5 Survivorship curve for female Belding’s ground squirrels

12. Survivorship Curves, Continued
Survivorship curves can be classified into three general types
Type I: Low death rates during early and middle life and an increase in death rates among older age groups
Type II: A constant death rate over the organism’s life span
Type III: High death rates for the young and a lower death rate for survivors

13. Idealized Survivorship Curves: Types I, II, and III
Figure 53.6 Idealized survivorship curves: Types I, II, and III

14. Reproductive Rates, Continued
Reproductive output for sexual organisms is measured as the average number of female offspring produced by the females in an age group
Age-specific reproductive rates vary considerably by species

15. Changes in Population Size
If immigration and emigration are ignored, the change in population size equals births minus deaths

16. Changes in Population Size, Continued
The population growth rate can be expressed mathematically as
where ΔN is the change in population size, Δt is the time interval, B is the number of births, and D is the number of deaths

17. Changes in Population Size, Continued-1
The population growth equation can be revised to
where R represents the difference between the number of births (B) and the number of deaths (D) that occur in the time interval

18. Changes in Population Size, Continued-2
The per capita (per individual) change in population
size
represents the contribution that an average
member of the population makes to the population size during the time interval ∆t
For example, for a population of 1,000 individuals that increases by 16 individuals per year

19. Changes in Population Size, Continued-3
The formula
can be used to calculate how
many individuals will be added to a population each year
For example, if
and the population size is
500,

20. Changes in Population Size, Continued-4
Change in population size can now be written as

21. Changes in Population Size, Continued-5
Population growth can also be expressed as a rate of change at each instant in time
where dN/dt represents very small changes in population size over short (instantaneous) time intervals

22. Exponential Growth
Exponential population growth is population increase under idealized conditions
Under such conditions, populations may increase in size by a constant proportion at each instant

23. Exponential Growth, Continued
The equation of exponential population growth is
where r is the intrinsic rate of increase, the per capita rate at which an exponentially growing population increases in size at each instant in time

24. Exponential Growth, Continued
Exponential population growth results in a J-shaped curve
The rate of increase is constant, but the population accumulates more new individuals per unit time when it is large than when it is small

25. Population Growth Predicted by the Exponential Model
Figure 53.8 Population growth predicted by the exponential model

26. Exponential Growth in the African Elephant Population of Kruger National Park, South Africa
Figure 53.9 Exponential growth in the African elephant population of Kruger National Park, South Africa

27. Concept 53.3: The logistic model describes how a population grows more slowly as it nears its carrying capacity
Exponential growth cannot be sustained for long in any population
A more realistic population model limits growth by incorporating carrying capacity
Carrying capacity (K) is the maximum population size the environment can support
varies with the abundance of limiting resources

28. The Logistic Growth Model
In the logistic population growth model, the per capita rate of population growth approaches zero as the population size nears carrying capacity (K)
The logistic model starts with the exponential model and adds an expression that reduces per capita rate of population growth as N increases

29. The Logistic Growth Model, Continued
When N is small compared to K, the term (K – N)/K is close to 1, and the per capita rate of population growth will be close to r
When N is large compared to K, the term (K – N)/K is close to 0, and the per capita rate of population growth is small
When N equals K, the population stops growing

30. Logistic Growth of a Hypothetical Population (K = 1,500)
Per Capita Population Growth Rate
Population Growth Rate
Intrinsic Rate of Increase (r)
Population Size (N) 25
1.0
0.983
0.983
+25
100
1.0
0.933
0.933
+93
250
1.0
0.833
0.833
+208
Table 53.2 Logistic growth of a hypothetical population (K = 1,500)
500
1.0
0.667
0.667
+333
750
1.0
0.500
0.500
+375
1,000
1.0
0.333
0.333
+333
1,500
1.0
0.000
0.000

31. The Logistic Growth Model, Continued
The logistic model of population growth produces a sigmoid (S-shaped) curve
New individuals are added to the population most rapidly at intermediate population sizes
The population growth rate decreases as N approaches K

32. Population Growth Predicted by the Logistic Model
Figure Population growth predicted by the logistic model

33. The Logistic Model and Real Populations
The growth of laboratory populations of paramecium fits an S-shaped curve because they grown in a constant environment lacking predators and competitors
Some populations overshoot K before settling down to a relatively stable density
Other populations fluctuate greatly and make it difficult to define K

34. How Well do these Populations Fit the Logistic Growth Model?
Figure 53.11a How well do these populations fit the logistic growth model? (part 1: Paramecium)
A Paramecium population in the lab

35. How Well do these Populations Fit the Logistic Growth Model?
Figure 53.11b How well do these populations fit the logistic growth model? (part 2: Daphnia)
A Daphnia population in the lab

36. Concept 53.4: Life history traits are products of natural selection
An organism’s life history comprises the traits that affect its schedule of reproduction and survival
They are evolutionary outcomes reflected in the development, physiology, and behavior of an organism
Entails three key components:
The age at first reproduction (maturity)
How often the organism reproduces
How many offspring are produced per reproductive episode

37. Diversity of Life Histories, Continued
Species that exhibit semelparity, or big-bang reproduction, reproduce once and die
Species that exhibit iteroparity, or repeated reproduction, produce offspring repeatedly
Organisms vary widely in the number of offspring they produce when they reproduce
Species that produce one or few offspring may provision them better than species that produce many offspring

38. Figure 53.13 Semelparity and Iteroparity
Semelparity, one-time reproducer
Iteroparity, repeat reproducer

39. “Trade-offs” and Life Histories
Organisms have finite resources, which may lead to trade-offs between survival and reproduction
For example, there is a trade-off between survival and paternal care in European kestrels
Selective pressures influence trade-offs between the number and size of offspring
For example, some plants produce a large number of small seeds, ensuring that at least some of them will grow and eventually reproduce
Other types of plants produce a moderate number of large seeds that provide a large store of energy that will help seedlings become established

40. Inquiry: How does Caring for Offspring Affect Parental Survival in Kestrels?
Figure Inquiry: How does caring for offspring affect parental survival in kestrels?

41. Variation in the Number and Size of Seeds in Plants
Dandelion
Figure 53.15a Variation in the number and size of seeds in plants (part 1: dandelion)
Seeds in pod

42. “Trade-offs” and Life Histories, Continued
K-selection is selection for life history traits that are advantageous at high population densities
r-selection is selection for life history traits that maximize reproductive success at low density
These concepts represent two extremes in a range of actual life histories

43. Concept 53.5: Density-dependent factors regulate population growth
There are two important questions about regulation of population growth
What environmental factors stop a population from growing indefinitely?
Why are some populations fairly stable in size, while others are not?

44. Population Change and Population Density
In density-independent populations, birth rate and death rate do not change with population density
In density-dependent populations, birth rates fall and death increase with rising population density
Only density-dependent factors can regulate population size

45. Determining Equilibrium for Population Density
Figure Determining equilibrium for population density

46. Mechanisms of Density-Dependent Population Regulation
Density-dependent birth and death rates are an example of negative feedback that regulates population growth
Density-dependent birth and death rates are affected by many factors, such as competition for resources, disease, predation, territoriality, toxic wastes, and intrinsic factors

47. Density-dependent Regulation by Predation
Figure Density-dependent regulation by predation

48. Exploring Mechanisms of Density-dependent Regulation
1. Competition for resources
4. Territoriality
Figure Exploring mechanisms of density-dependent regulation
6. Toxic wastes
3. Predation
5. Intrinsic factors
2. Disease

49. 1. Competition for Resources
In crowded populations, increasing population density intensifies competition for resources and results in a lower birth rate

50. 2. Disease
Population density can influence the health and survival of organisms
In dense populations, pathogens can spread more rapidly

51. 3. Predation
As a prey population builds up, predators may feed preferentially on that species

52. 4. Territoriality
Territoriality can limit population density when individuals compete for limited space

53. 5. Intrinsic Factors
For some populations, intrinsic (physiological) factors appear to regulate population size

54. 6. Toxic Wastes
Accumulation of toxic wastes can contribute to density-dependent regulation of population size

55. Population Dynamics
The study of population dynamics focuses on the complex interactions between biotic and abiotic factors that cause variation in population size
Both abiotic and biotic factors can affect population size of large mammals over time
For example, major collapses in the moose population on Isle Royale occurred in response to harsh winter conditions in one year and in response to increasing predator populations in other years

56. Fluctuations in Moose and Wolf Populations on Isle Royale, 1959–2011
Figure Fluctuations in moose and wolf populations on Isle Royale, 1959–2011

57. Population Cycles: Scientific Inquiry
Some populations undergo regular boom-and-bust cycles
For example, lynx populations follow the 10-year boom-and-bust cycle of hare populations
Two main hypotheses have been proposed to explain the hare’s 10-year interval

58. Population Cycles in the Snowshoe Hare and Lynx
Figure Population cycles in the snowshoe hare and lynx

59. Population Cycles: Scientific Inquiry, Continued
Hypothesis 1: The hare’s population cycle follows a cycle of winter food supply
If this hypothesis is correct, then the cycles should stop if the food supply is increased
Additional food was provided experimentally to a hare population, and the whole population increased in size but continued to cycle
These data do not support the first hypothesis

60. Population Cycles: Scientific Inquiry, Continued-1
Hypothesis 2: The hare’s population cycle is driven by pressure from other predators
In a study conducted by field ecologists, 95% of the hares were killed by predators, including lynx, coyotes, hawks, and owls
These data support the second hypothesis

61. Concept 53.6: The human population is no longer growing exponentially but is still increasing rapidly
No population can grow indefinitely, and humans are no exception
The human population increased relatively slowly until about 1650 and then began to grow exponentially

62. Human Population Growth (Data as of Now!)
Figure Human population growth (data as of 2015)

63. The Global Human Population, Continued
The global population is now more than 7.2 billion people
Though the global population is still growing, the rate of growth began to slow during the 1960s

64. Annual Percent Increase in the Global Human Population (Data as of 2014)
Figure Annual percent increase in the global human population (data as of 2014)

65. Regional Patterns of Population Change
To maintain population stability, a regional human population can exist in one of two configurations
Zero population growth = High birth rate  High death rate
Zero population growth = Low birth rate  Low death rate
The demographic transition is the move from the first state to the second state

66. Regional Patterns of Population Change, Continued
The demographic transition is associated with an increase in the quality of health care and improved access to education, especially for women
Most of the current global population growth is concentrated in developing countries
Age-structure diagrams (pyramids) can help predict a population’s growth trends
They also illuminate social conditions and help us plan for the future

67. Age Structure
One important factor affecting population growth is a country’s age structure
Age structure is the relative number of individuals of each age in a population

68. Age-structure Pyramids for the Human Population of Three Countries (Data as of 2010)
Figure Age-structure pyramids for the human population of three countries (data as of 2010)

69. Infant Mortality and Life Expectancy
Infant mortality and life expectancy at birth vary widely among different countries
The quality of life faced by children at birth can influence reproductive choices by parents
Global life expectancy has increased since about
Social upheaval, decaying infrastructure, and disease have reduced life expectancy in some countries

70. Global Carrying Capacity
How many humans can the biosphere support?
Population ecologists predict a global population of billion people in 2050
The carrying capacity of Earth for humans is uncertain
Scientists have based estimates on logistic growth models, area of habitable land, and food availability