Population Ecology
Chapters 5 and 8
•
Ecology is studied at several
levels
Ecology and evolution are
tightly intertwined
• Biosphere = the total living
things on Earth and the
areas they inhabit
• Ecosystem = communities
and the nonliving material
and forces they interact
with
• Community = interacting
species that live in the
same area
Levels of ecological
organization
• Population ecology = investigates the quantitative
dynamics of how individuals within a species
interact
• Community ecology = focuses on interactions
among species
• Ecosystem ecology = studies living and nonliving
components of systems to reveal patterns
– Nutrient and energy flows
Some Definitions
Population Ecology – The study of
biological factors that affect the sizes of
population
Demography – The study of human
populations in numerical terms
Population – A set of potentially
interbreeding individuals in a certain
geographical location at a certain time
Some Definitions
Census – a head count of all the individuals
living in a specified area.
Growth rate – The rate of change of
population size
-birth rate – number of births per year divided
by number of people in the population
-death rate - number of deaths per year
divided by number of people in the population
Population Ecology
•
•
•
•
Population- how to measure?
Growth rates: J shaped, S shaped
K, r, and reproductive strategies
Human population
How are populations measured?
• Population density = number of
individuals in a given area or volume
• count all the individuals in a population
• estimate by sampling
• mark-recapture method depends on
likelihood of recapturing the same individual
Figure 35.2A
The dispersion pattern of a population
refers to the way individuals are spaced
in their area
(a) Clumped (elephants)
(b) Uniform (creosote
bush)
(c) Random (dandelions)
Mathematics of population growth
•Births per year = bN
(where b = per capita birth rate, N = Population Size)
•Deaths per year = dN
(where d = per capita death rate , N = Population Size)
•dN/dt = bN - dN = (b-d) N = r N
(where r = b-d, dN/dt = Change per year)
•r is called Biotic Potential or intrinsic rate of natural increase.
If immigration and emigration also occur then
r = (b + i) – (d + m)
•dN/dt = rN  Nt = Noert
Nt = Population at time “t”
No= Initial population (at time “0”)
e = Euler’s Constant
r = Biotic Potential
t = Time
Figure 35.3A
high intrinsic
rate of increase
1500
Population size
1000
low intrinsic
rate of increase
500
r=0
zero population
growth
negative intrinsic
rate of increase
r = -0.05
0
0
5
10
Time (years)
15
20
A street scene in
Quito, Ecuador
Graph showing
the growth of
world’s human
population
MALTHUS' VIEW ON
POPULATION (1798)
A population tends to increase
geometrically if its growth is unchecked
The available food supply increase only
arithmetically
Since the population increases faster than
the food supply, the increasing population
causes human misery and poverty
MALTHUS' VIEW ON POPULATION
(1798)
A new population shows rapid
exponential growth at first
Its growth rate levels off when it
approaches the carrying capacity of its
environment, a phenomenon called
logistic growth
Malthus’
View On
Population
Exponential Growth Compared With Logistic
Growth. The Steeper (more vertical) The Slope, the
More Rapid The Rate Of Growth
Limiting factors restrain growth
• declining birth rate or increasing death rate
• Limiting factors = physical, chemical and
biological characteristics that restrain
population growth
– Water, space, food, predators, wastes and
disease
• Environmental resistance = All limiting
factors taken together
Figure 9-4
Page 166
Environmental
resistance
Population size (N)
Carrying capacity (K)
Biotic
potential
Exponential
growth
Time (t)
POPULATION SIZE
Growth factors
(biotic potential)
Abiotic
Favorable light
Favorable temperature
Favorable chemical environment
(optimal level of critical nutrients)
Biotic
High reproductive rate
Generalized niche
Adequate food supply
Suitable habitat
Ability to compete for resources
Ability to hide from or defend
against predators
Ability to resist diseases and parasites
Ability to migrate and live in other
habitats
Ability to adapt to environmental
change
© 2004 Brooks/Cole – Thomson Learning
Decrease factors
(environmental resistance)
Abiotic
Too much or too little light
Temperature too high or too low
Unfavorable chemical environment
(too much or too little of critical
nutrients)
Biotic
Low reproductive rate
Specialized niche
Inadequate food supply
Unsuitable or destroyed habitat
Too many competitors
Insufficient ability to hide from or defend
against predators
Inability to resist diseases and parasites
Inability to migrate and live in other
habitats
Inability to adapt to environmental
change
2. Logistic growth is slowed by density
dependent limiting factors
K = Carrying capacity is
the maximum
population size
that an environment
can support
Figure 35.3B
Logistic Growth Equation
• logistic growth curve
– K = carrying capacity
– The term
(1-N/K)
accounts
for the
leveling
off of the
curve
Figure 35.3C
How does population density affect
population growth?
• Density-Independent Factors
– Affect a population’s size regardless of its
population density
– Floods, hurricanes, drought, weather, fire,
habitat destruction, and pesticide spraying
• Density-Dependent Factors
– As density of population increases, these
factors have a greater effect
• Competition, predation, parasitism, and disease
• Bubonic plague—urban hell batman…
Exceeding K
• Some species do not make a smooth transition
from exponential and logistic growth
– Instead temporarily overshoots K because of
reproductive time lag (the period needed for birth rate
to fall and death rate to rise in response to resource
overconsumption)
– Dieback or population crash
• Reindeer introduced onto island
• Technological, social, and other cultural changes
have extended earth’s K for humans
2.0
Overshoot
Number of sheep (millions)
Carrying capacity
1.5
1.0
.5
1800
1825
1850
1875
Year
1900
1925
Population
overshoots
carrying
capacity
Number of reindeer
2,000
Population
crashes
1,500
1,000
500
Carrying
capacity
1910
1920
1930
Year
1940
1950
Taking Age into Account
• The best answer is simple, but no simpler
Albert Einstein
• Seek simplicity, then distrust it
Lord Alfred North Whitehead
• The Exponential and Logistic Models Make
Some Simplifying Assumptions
– All individuals are equally likely to die (mortality)
– All individuals are reproductively active (natality)
• Age structure models take age specific mortality
and natality into account
Survivorship Curves
• Type I
– Late loss; death usually due to old age
– High survivorship to certain age—then high mortality
– Mammals
• Type II
– Environment causes death independent of age
– Birds/reptiles
• Type III
– Survivorship lowest in juvenile stages
– Most common; insects, cane toads, bony fish, plants
Reproductive Curves
Lifespan
Life Tables
0
1.000
0.000
1
0.845
0.045
2
0.824
0.391
3
0.795
0.472
4
0.755
0.484
5
0.699
0.546
6
0.626
0.543
7
0.532
0.502
8
0.418
0.468
9
0.289
0.459
10
0.162
0.433
11
0.060
0.421
Age,
years
(x)
x
x
Survivorship
1
% Surviving
No. of female
offspring
born to a mother
of age x
(m )
0.1
0.01
0
2
4
6
8
10
12
8
10
12
Age (Years)
Reproduction
0.6
Age Specific Natality
Probability
of
surviving to
age x
(l )
0.5
0.4
0.3
0.2
0.1
0
0
2
4
6
Age (Years)
Source: http://www.gypsymoth.ento.vt.edu/~sharov/PopEcol/lec6/agedep.html
Turkey Trouble!
The Lewis-Leslie Matrix
Nx,t = number of organisms in age x at time t
sx = survival of organisms in age interval from x to x+1.
mx = number of offspring produced in the age interval from x to x+1
Source: http://www.gypsymoth.ento.vt.edu/~sharov/PopEcol/lec7/leslie.html
Age Structure Diagram
Green - Pre-reproductive years
Dark Blue- Reproductive years
Light blue - Post- reproductive years
Figure 9-9
Page 169
Number of individuals
Carrying capacity
G = rN (1-N/K)
K
K species;
experience
K selection
Life History Strategies
r species;
experience
r selection
Time
r-Selected Species
Dandelion
Cockroach
Many small offspring
Little or no parental care and protection of offspring
Early reproductive age
Most offspring die before reaching reproductive age
Small adults
Adapted to unstable climate and environmental
conditions
High population growth rate (r)
Population size fluctuates wildly above and below
carrying capacity (K)
Generalist niche
Low ability to compete
Early successional species
K-Selected Species
Saguaro
Elephant
Fewer, larger offspring
High parental care and protection of offspring
Later reproductive age
Most offspring survive to reproductive age
Larger adults
Adapted to stable climate and environmental conditions
Lower population growth rate (r)
Population size fairly stable and usually close to
carrying capacity (K)
Specialist niche
High ability to compete
Late successional species
Human Survivorship Curves
Population Age Structures
• Even if global RLF level were magically lowered
to 2.1, the population would continue to grow for
at least 50 yrs because there are so many who
have yet to reach child bearing years
• Population age structure diagrams help
demographers understand future trends
• Any country with many people below age 15 has
a powerful built in momentum to increase
– In 2003, 30% of the people were aged 15 or less!!
Age Structure Diagram
Green - Pre-reproductive years
Dark Blue- Reproductive years
Light blue - Post- reproductive years
US Trends
•Baby Boom
•From 1946 to 1964, the US pop
increased by 79 million
•Baby boomers now make up 50%
of all adult Americans
•Dominate demand for goods and
services
•Important political group
•Baby Bust Generation (GenX)
•People born between 1965-1976
•Retired baby boomers will likely
use their political clout to force the
GenXers to pay higher income,
health care, and social security
taxes
•Echo-Boom (born
1977 to 2003)
The Population Debate
• Can the world provide an adequate standard of living for
3 billion more people without causing widespread
environmental damage?
• Is the earth already overpopulated?
– What measures should be taken to slow growth?
• Instead of asking what is the carrying capacity, some
believe we should be asking what the optimum
sustainable population of the earth might be
• Should people be allowed to have as many children as
they want?
• What is your opinion on this issue?
Population growth affects the
environment
• The IPAT model: I = P x A x T x S
– Our total impact (I) on the environment results from
the interaction of population (P), affluence (A) and
technology (T), with an added sensitivity (S) factor
– Population = individuals need space and resources
– Affluence = greater per capita resource use
– Technology = increased exploitation of resources
– Sensitivity = how sensitive an area is to human
pressure
– Further model refinements include education, laws,
ethics
Humanity uses 1/3 of all the Earth’s net primary production
Causes and consequences of population growth
Computer simulations predict
the future
• Simulations project trends in
population, food, pollution,
and resource availability
• If the world does not change,
population and production will
suddenly decrease
• In a sustainable world,
population levels off,
production and resources
stabilize, and pollution
declines
How is Population Affected by
Birth and Death Rates?
• Pop Change = (B + I)- (D + E)
• Demographers use
– crude birth rate (# of live births per 1000 people per
year) and
– crude death rate (# of deaths per 1000 per year)
• Birth and death rates are coming down
worldwide but death rates have fallen more
sharply than birth rates
– 216K people added every day (mostly where?)
Annual Population Growth Rate
Annual world
population growth
<1%
1-1.9%
2-2.9%
3+%
Data not
available
Ave Crude Birth and Death Rates
Average crude birth rate
Average crude death rate
World
22
9
All developed
countries
11
10
All developing
countries
25
9
Developing
countries
(w/o China)
29
9
Rate of natural increase = (crude birth rate - crude death rate)
10
Rate per 1,000 people
50
Crude
birth rate
40
30
Rate of
natural
increase
20
Crude
death rate
Rate per 1,000 people
Developing
Developed Countries
50
Rate of
natural increase
40
Crude
birth rate
30
20
10
10
Year
Year
0
Developed Countries
0
Crude
death rate
Comparing 3 Countries
Fertility and Survivorship
Pakistan Fert
Ecuador Fert
USA Fert
Pakistan Surv
Ecuador Surv
USA Surv
250
100
90
80
70
150
60
50
100
40
30
50
20
10
0
0
0- 4
5- 9
10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 70-74 75-79 80-84 85+
Age Class
Percent Surviving
Age Specific Fertility Rate
(per 1000)
200
Changes in Global Fertility Rates
• Replacement Level Fertility (RLF)
– # of children a couple must bear to replace
themselves
– Slightly higher than 2 per couple (2.1 in developed
and ~2.5 in developing) WHY?
– Does reaching RLF mean an immediate halt in
pop growth?
• No b/c so many future parents are alive
• Total Fertility Rate (TFR)
– An estimate of the average # of children a woman
will have during child bearing years if between the
ages of 15 and 49 she bears children at the same
rate as women did this year
What factors affect TFR?
•
•
•
•
•
Importance of children in labor force
Cost of raising and educating children
Availability of public/private pension
Urbanization (access to birth control)
Educational/employment opportunities for
women
• Infant mortality rate
• Ave age at which women start having children
• Availability of birth control and legal abortions
Fertility Rates and Poverty
• 97% of the future population growth is
expected to take place in developing
countries
– Acute poverty is a way of life for 1.4 B
– Between 2003 and 2050, the population of
developing countries is projected to increase
to 8 billion from 5.2 billion
– Why would poor women have more
children???
Fertility Rates
• In 2003:
– Ave global TFR was 2.8 per woman
• 1.5 in developed (down from 2.5 in 1950)
• 3.1 in developing (down from 6.5 in 1950)
– Still far above global replacement level!
• UN population projections to 2050 vary
depending upon world’s projected average
TFR
Decline in Total Fertility Rates
World
5 children per women
2.9
Developed
countries
2.5
1.5
Developing
countries
6.5
3.2
Africa
6.6
5.3
Latin
America
5.9
2.8
Asia
5.9
2.8
Oceania
3.8
2.4
North
America
3.5
Fig 11-5
2.0
Europe
2.6
1.4
1950
2000
TFR
Births per woman
<2
4-4.9
2-2.9
5+
3-3.9
Data not
available
Fig. 11.8, p. 242
Falling growth rates do not
mean fewer people
Falling rates of
growth do not mean
a decreasing
population, but only
that rates of
increase are slowing
Projected Population as of 2050
12
11
Population (billion)
10
9
8
High
High
10.7
Medium
TFR
Low
Medium
8.9
High=2.6
Med=2.1
7
6
Low
7.3
5
Low=1.7
4
3
2
1950 1960 1970 1980 1990 2000 2010 2020 2030 2040 2050
Year
Fig. 11.6, p. 225
What factors affect death rates?
• Rapid increase in world’s pop due to
decline in crude death rates (not births)
• More people started living longer b/c:
– Increased food supplies and distribution
– Better nutrition
– Improved public heath (immunizations etc)
– Improved sanitation and hygiene)
– Safer water supplies
Two Indicators of Overall Health
of People in a Country
• Life Expectancy
– Ave # of years an infant can expect to live
– Global LE increased from 48 to 67 (76 in
developed; 65 in developing) 1955-2003
– In world’s poorest =55 yrs or less
• Infant Mortality Rate
– # of babies out of 1000 that die before 1yr
– Usually indicates lack of food, poor nutrition, poor
health care, and high incidence of disease
– From 1965 to 2003, IMR dropped from 20 to 7 in
developed; and 118 to 61 in developing
– Still means 8M infants die of preventable causes
each year (=22,000 per day)
Human Life
Expectancy
(1999)
Mathematics of population growth
(practice worksheet)
•Births per year = bN
(where b = per capita birth rate, N = Population Size)
•Deaths per year = dN
(where d = per capita death rate , N = Population Size)
•dN/dt = bN - dN = (b-d) N = r N
(where r = b-d, dN/dt = Change per year)
•r is called Biotic Potential or intrinsic rate of natural increase.
•If immigration and emigration also occur then
r = (b + i) – (d + m)
•dN/dt = rN  Nt = Noert
•Annual rate of change =Birth rate-Death rate x 100
1,000 persons
OR
(Birth rate-Death rate)/10
•Doubling Time = 70/Annual Rate
Mathematical Population Relationships
Converting Rates
Per Capita
(per individual)
Percent
(per Hundred)
Crude
(per thousand)
r % R CGR


1 100 1000
Use with
Nt = Noert
Use with
%R*T2 = 70
Use with
Demographic Data
Ave Crude Birth and Death Rates
Average crude birth rate
Average crude death rate
World
22
9
All developed
countries
11
10
All developing
countries
25
9
Developing
countries
(w/o China)
29
9
Demographic Transition Model
• DTM is a hypothesis involving population
changes over time
• As countries become more industrialized,
first their death rates and then their birth
rates decline
• According to the hypothesis, this transition
occurs over 4 phases
Demographic Transition
Stage 2
Transitional
Stage 3
Industrial
Stage 4
Postindustrial
High
80
70
Relative population size
Birth rate and death rate
(number per 1,000 per year)
Stage 1
Preindustrial
60
50
Birth rate
40
30
Death rate
20
10
0
Total population
Low
Increasing Growth Very high
growth rate
growth rate
growth rate
Decreasing
growth rate
Low
Low
growth rate
Zero
growth rate
Negative
growth rate
Time
Fig. 11.18, p. 233
Demographic Transition
• 1st:
• 3rd:
– Preindustrial Phase
• Little pop growth b/c harsh
living conditions lead to
high birth and high death
rate
• 2nd:
– Transitional Phase
• Industrialization begins,
food supply increases,
and health care improves
• Death rate drops and birth
rate stays high
• Pop grows dramatically
– Industrial Stage
• Birth rate drops and
approaches death rate
• Industrialization and
modernization become
widespread
• Pop growth slows
• 4th: Postindustrial
– BR=DR (ZPG)
– 38 countries accounting for
13% are in this stage
Factors Affecting Birth and Death Rates in
the Demographic Transition
• Death Rates Decrease
– Improved Medicine
• Maternity Care
–
–
–
–
Improved Sanitation
Improved Hygiene
Improved Water supply
Improved Food/Nutrition
• Agriculture
• Food preservation
– Improved Transportation
– Cessation of Military
Conflict
• Birth Rates Remain High
– Compensate for high infant
mortality
– Assure care for elders
– Provide labor
– Cultural/Religious practices
• Prohibit Birth Control
• Favor large families
– Lack of contraceptives
– Lack of education @ family
planning
– Lack of women’s rights
Why is the Birth Rate Slow to Decrease?
• Cultural or Religious practices take time to
change
• Immigration of women of child-bearing age
• Slow acceptance of changes in women’s status
• Educational and employment opportunities for
women slow to appear
• Slow advances in the production and distribution
of birth control
• Government slow to provide support for elderly
Role of Family Planning
• FP has been responsible for at least half of the
drop in TFR’s in developing countries
• Reduces the number of legal and illegal
abortions each year
• Decreased risk of death from pregnancy
• Dev’ing: 10% in 1960s to 51% use
• But, still 250-350M women want access but
don’t yet have it
– UN says it would cost $17B/yr (8 days of military
expenditures) (about $5 per person) to do this!
Control of Pregnancy
• Behavioral methods
– Abstinence
– Coitus interruptus
– Rhythm method
• Barrier methods
– Condom
• Male and female
– Diaphragm
– Cervical cap
– Spermicidal agents
• Lactation
• Chemical methods
– Oral contraceptives
– Injections as DepoProvera
– Implants
– Morning-after pills
• Surgical methods
– Vasectomy
– Tubal ligation
– Abortions
Role of the Status of Women
• Studies show that women tend to have fewer
and healthier children and live longer when
they have access to education and to paying
jobs and live in societies where they are not
oppressed
• Make up 50% of population but…
–
–
–
–
Do almost all domestic and child rearing
60-80% of work growing food, getting H2O
66% of all hours worked; 10% of world’s income
Own less than 2% of world’s land
• Many do not have right to own land, inherit
estates, or borrow money
Education of women
reduces the average
number of children
per family
Economic Rewards and Penalties
• Some believe we need to go beyond
family planning and offer economic
rewards and penalties to help slow
population growth
– $ for those who are sterilized or use
contraceptives
• Usually only those done having a family will do
this!
– China penalizes couples who have more than
one or two via taxes, fees, etc
A Poster
Promoting
Birth Control
in China
CHINA’S POPULATION CONTROL
•The Chinese government has used several methods
to control population growth
•In 1979, China started the "one child per family
policy"
•This policy stated that citizens must obtain a birth
certificate before the birth of their children
CHINA”S POPULATION CONTROL
•The citizens would be offered special benefits if they
agreed to have only one child
•Citizens who did have more than one child would
either be taxed an amount up to fifty percent of their
income, or punished by loss of employment or other
benefits
India's population has passed the one billion
mark, according to the country's census
commission
Reference:
http://news.bbc.co.uk/1/hi/world/south_asia/744507.stm
India
Cultural factors like pressure to have male
children, the economic importance of child
labor and religious restrictions on sexual
education are just some of the factors
influencing this high population growth rate.
Reference:
(http://www.asiasource.org/asip/ngos_health2.cfm)
Role of Predators in Controlling Population
 Predator-prey cycles
Population size (thousands)
160
140
Hare
120
Lynx
100
80
60
40
20
0
1845
1855
1865
1875
1885
1895
Year
1905
1915
1925
1935
Role of Predators in Controlling
Population
• Cyclic increases followed by crashes
• Snowshoe hare and lynx exemplify argument:
• Top Down Control
–
–
–
–
Lynx preying on hares reduce population
Shortage of hares reduces lynx population
Allows hare population to build up again
Other examples inc. wolves/deer; sharks/fish
• Bottom Up Control
– Hares consuming plants is real issue
– Changing hare population effects lynx population
Mathematical Population Relationships

Crude Growth
Rate
(CGR)
Per 1000
Percent Rate
(R)
Decimal Rate
(r)
Per 100
Per Capita
CBR- CDR
R * 10
Demographic
Data
CGR/10
r * 100
Use with
T2 = 70/R
R/100
r
Use with
Nt = N0ert
