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53

Population Ecology

Lecture Presentation by �Nicole Tunbridge and

Kathleen Fitzpatrick

CAMPBELL

BIOLOGY

Reece • Urry • Cain • Wasserman • Minorsky • Jackson

TENTH

EDITION

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Turtle Tracks

Population ecology explores how biotic and abiotic factors influence density, distribution, size, and age structure of populations

For example, the number of loggerhead turtle hatchlings that survive their first journey to the ocean is affected by both biotic and abiotic factors

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Figure 53.1

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Figure 53.1a

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Concept 53.1: Biological processes influence population density, dispersion, and demographics

A population is a group of individuals of a single species living in the same general area
Populations are 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

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Density: A Dynamic Perspective

In most cases, it is impractical or impossible to count all individuals in a population
Sampling techniques can be used to estimate densities and total population sizes
Population size can be estimated by either extrapolation from small samples, an index of population size (e.g., number of nests), or the mark-recapture method

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Determining Population Size Using the Mark-recapture method

Scientists capture, tag, and release a random sample of individuals (s) in a population
Marked individuals are given time to mix back into the population
Scientists capture a second sample of individuals (n), and note how many of them are marked (x)
Population size (N) is estimated by

sn

x

N =

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Figure 53.2

Hector’s dolphins

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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

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Figure 53.3

Births

Births and immigration�add individuals to�a population.

Immigration

Deaths

Deaths and emigration�remove individuals�from a population.

Emigration

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Patterns of Dispersion

Environmental and social factors influence the spacing of individuals in a population
In a clumped dispersion, individuals aggregate in patches
A clumped dispersion may be influenced by resource availability and behavior

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Figure 53.4

(a) Clumped

(b) Uniform

(c) Random

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Figure 53.4a

(a) Clumped

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Figure 53.4b

(b) Uniform

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Figure 53.4c

(c) Random

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Video: Flapping Geese

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Video: Albatross Courtship Ritual

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Video: Prokaryotic Flagella

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A uniform dispersion is one in which individuals are evenly distributed
It may be influenced by social interactions such as territoriality, the defense of a bounded space against other individuals

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In a random dispersion, the position of each individual is independent of other individuals
It occurs in the absence of strong attractions or repulsions

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Demographics

Demography is the study of the vital statistics of a population and how they change over time
Death rates and birth rates are of particular interest to demographers

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Life Tables

A life table is an age-specific summary of the survival pattern of a population
It is best made by following the fate of a cohort, a group of individuals of the same age
The life table of Belding’s ground squirrels reveals many things about this population

For example, it provides data on the proportions of males and females alive at each age

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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

Many species are intermediate to these curves

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Concept 53.2: The exponential model describes population growth in an idealized, unlimited environment

It is useful to study population growth in an idealized situation
Idealized situations help us understand the capacity of species to increase and the conditions that may facilitate this growth

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Per Capita Rate of Increase

If immigration and emigration are ignored, a population’s growth rate (per capita increase) equals birth rate minus death rate

Change in

population

size

Births

Immigrants

entering

population

Deaths

Emigrants

leaving

population

=

+

–

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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

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Births and deaths can be expressed as the average number of births and deaths per individual during the specified time interval��where b is the annual per capita birth rate, m �(for mortality) is the per capita death rate, and �N is population size

B = bN

D = mN

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The population growth equation can be revised

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The per capita rate of increase (r) is given by

Zero population growth (ZPG) occurs when the birth rate equals the death rate (r = 0)

r = b – m

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Change in population size can now be written as

ΔN

Δt

=

rN

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Instantaneous growth rate can be expressed as

where r_inst is the instantaneous per capita rate of increase

dN

dt

=

r_instN

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Exponential Growth

Exponential population growth is population increase under idealized conditions
Under these conditions, the rate of increase is at its maximum, denoted as r_max
The equation of exponential population growth is

dN

dt

=

r_instN

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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

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Figure 53.8

Number of generations

Population size (N)

dN

dt

= 1.0N

dN

dt

= 0.5N

0 5 10 15

2,000

1,500

1,000

500

0

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The J-shaped curve of exponential growth characterizes some rebounding populations

For example, the elephant population in Kruger National Park, South Africa, grew exponentially after hunting was banned

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Figure 53.9

Year

Elephant population

8,000

6,000

4,000

2,000

0

1900 1910 1920 1930 1940 1950 1960 1970

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Figure 53.9a

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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
Carrying capacity varies with the abundance of limiting resources

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The Logistic Growth Model

In the logistic population growth model, the per capita rate of increase declines as carrying capacity is reached
The logistic model starts with the exponential model and adds an expression that reduces per capita rate of increase as N approaches K

dN

dt

=

(K – N)

K

r_inst

N

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When N is small compared to K, the term (K–N)/K is close to 1 and the per capita rate of increase approaches the maximum
When N is large compared to K, the term (K–N)/K is close to 0 and the per capita rate of increase is small
When N equals K, the population stops growing

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Table 53.3

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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

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Figure 53.10

Exponential�growth

Logistic growth

Population growth�begins slowing here.

Number of generations

Population size (N)

= 1.0N

K = 1,500

dN

dt

1,500 − N

1,500

2,000

1,500

1,000

500

0

10

15

5

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The Logistic Model and Real Populations

The growth of laboratory populations of paramecia fits an S-shaped curve
These organisms are grown in a constant environment lacking predators and competitors

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Figure 53.11

1,000

800

600

400

200

0

5

10

15

Time (days)

(a) A Paramecium population in the lab

(b) A Daphnia population in the lab

0

20

40

60

80

100

120

140

160

180

150

120

90

60

30

0

Time (days)

Number of Daphnia/50 mL

Number of Paramecium/mL

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Figure 53.12

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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
Life history traits are evolutionary outcomes reflected in the development, physiology, and behavior of an organism

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Evolution and Life History Diversity

A life history entails three main variables

The age at which reproduction begins
How often the organism reproduces
How many offspring are produced per reproductive episode

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Figure 53.13

Semelparity, one-time

reproducer

(b) Iteroparity, repeat reproducer

(a)

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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 rates rise with population density

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Figure 53.16

Population density

Density-dependent

birth rate (b)

Density-independent

death rate (m)

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

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Competition for Resources

In crowded populations, increasing population density intensifies competition for resources and results in a lower birth rate

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Figure 53.18

Competition for resources

Territoriality

Intrinsic factors

Disease

Predation

Toxic wastes

5 µm

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BioFlix: Population Ecology

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Disease

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

Predation

As a prey population builds up, predators may feed preferentially on that species

Territoriality

In many vertebrates and some invertebrates, competition for territory may limit density

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Intrinsic Factors

For some populations, intrinsic (physiological) factors appear to regulate population size

Toxic Wastes

Accumulation of toxic wastes can contribute to density-dependent regulation of population size

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Population Dynamics

The study of population dynamics focuses on the complex interactions between biotic and abiotic factors that cause variation in population size

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Stability and Fluctuation

Long-term population studies have challenged the hypothesis that populations of large mammals are relatively stable over time
Both weather and predator population can affect population size over time

For example, the moose population on Isle Royale collapsed during a harsh winter, and when wolf numbers peaked

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Figure 53.19

Wolves

Moose

2,500

2,000

1,500

1,000

500

0

2005

1995

1985

1975

1965

1955

Year

Number of moose

Number of wolves

50

40

30

20

10

0

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Population Cycles: Scientific Inquiry

Some populations undergo regular boom-and-bust cycles
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

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Figure 53.20

Snowshoe hare

Lynx

160

120

80

40

0

1850

1875

1900

Year

1925

9

6

3

0

Number of lynx

(thousands)

Number of hares

(thousands)

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The availability of prey is a major factor influencing predator population dynamics
When prey become scarce, predator species begin to prey on one another, accelerating the collapse of predator populations

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Immigration, Emigration, and Metapopulations

When a population becomes crowded and resource competition increases, emigration often increases

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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

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The Global Human Population

The human population increased relatively slowly until about 1650 and then began to grow exponentially

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Figure 53.22

8000

BCE

4000

BCE

3000

BCE

2000

BCE

1000

BCE

0

1000

CE

2000

CE

0

1

2

3

4

5

6

7

Human population (billions)

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The global population is now more than 7 billion people
Though the global population is still growing, the rate of growth began to slow during the 1960s

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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

0

1950

1975

2000

2025

Year

Annual percent increase

2050

Projected

data

2011

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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

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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

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Age Structure

One important demographic factor in present and future growth trends is a country’s age structure
Age structure is the relative number of individuals at each age

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Figure 53.24

Rapid growth

Slow growth

No growth

Afghanistan

United States

Italy

Female

Male

Female

Male

Female

Male

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

10

8

6

4

2

0

2

4

6

8

10

Percent of population

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

5

4

3

2

1

0

1

2

3

4

5

4

3

2

1

0

1

2

3

4

5

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Figure 53.24a

Rapid growth

Afghanistan

Female

Male

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

Percent of population

10

8

6

4

2

0

2

4

6

8

10

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Figure 53.24b

Slow growth

United States

Female

Male

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

Percent of population

5

4

3

2

1

0

1

2

3

4

5

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Figure 53.24c

No growth

Italy

Female

Male

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

Percent of population

5

4

3

2

1

0

1

2

3

4

5

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Age structure diagrams can predict a population’s growth trends
They can illuminate social conditions and help us plan for the future

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Infant Mortality and Life Expectancy

Infant mortality and life expectancy at birth vary greatly among developed and developing countries but do not capture the wide range of the human condition

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Global Carrying Capacity

How many humans can the biosphere support?
Population ecologists predict a global population of 8.1–10.6 billion people in 2050

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Estimates of Carrying Capacity

The carrying capacity of Earth for humans is uncertain
Scientists have based estimates on logistic growth models, area of habitable land, and food availability

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Limits on Human Population Size

The ecological footprint concept summarizes the aggregate land and water area needed to sustain the people of a nation
It is one measure of how close we are to the carrying capacity of Earth
Countries vary greatly in footprint size and available ecological capacity

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Figure 53.25

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Ecological footprints can also be calculated using energy use
Average per capita energy use differs greatly between developed and developing nations

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Figure 53.26

Energy use (GJ):

> 300

< 10

150–300

50–150

10–50

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Our carrying capacity could potentially be limited by food, space, nonrenewable resources, or buildup of wastes
Unlike other organisms, we can regulate our population growth through social changes

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Figure 53.UN01

Daphnia

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Figure 53.UN02

Patterns of dispersion

Clumped

Uniform

Random

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Figure 53.UN03

dN

dt

= r_inst N

Number of generations

Population size (N)

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Figure 53.UN04

Number of generations

Population size (N)

dN

dt

= r_inst N

(K − N)

K

K = carrying capacity

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Figure 53.UN05