Chapter 52

POPULATION
ECOLOGY

LECTURES BY: VILLAMOR CYRIL, AND VICENTE NOYMI

TOPIC OUTLINE
o CHARACTERISTICS OF POPULATIONS
o LIFE HISTORIES
o POPULATION GROWTH
o POPULATION-LIMITING FACTORS
o HUMAN POPULATION GROWTH
CHARACTERISTICS OF
POPULATIONS
• Overview: Earth’s Fluctuating Populations
• To understand human population growth
– We must consider the general principles of population ecology

• Population ecology is the study of populations in relation to

environment
– Including environmental influences on population density and
distribution, age structure, and variations in population size
EXAMPLE:

• Population dynamics of moose on Isle Royale,

located in Lake Superior
- This isolated population has experienced significant
fluctuations over the years due to a combination of biotic and abiotic
factors.
• Concept 52.1: Dynamic biological processes influence
population density, dispersion, and demography
• POPULATION
– Is a group of individuals of a single species living in the same
general area
• 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
Density: A Dynamic Perspective

• Determining the density of natural populations

– Is possible, but difficult to accomplish
High density can lead to competition for resources, higher risk of disease transmission, and social interactions like mating.

Low density may result in difficulty finding mates and reduced social structures.

• In most cases
– It is impractical or impossible to count all individuals in a
population
• Density is the result of a dynamic interplay
– Between processes that add individuals to a population and those that
remove individuals from it
Births and immigration add
individuals to a population.

Birth
Immigration
s

PopuIatio
n
size

Emigration

Death
s
Deaths and emigration
remove individuals from a
population.
Patterns of Dispersion

• Environmental and social factors

– Influence the spacing of individuals in a
population
• Clumped dispersion
– Is one in which individuals aggregate in patches
– May be influenced by resource availability and
behavior

(a) Clumped. For many animals, such as these wolves,

living in groups increases the effectiveness of hunting,
spreads the work of protecting and caring for young,
and helps exclude other individuals from their territory.
Figure
52.3a
Patterns of Dispersion
• Another example of Clumped dispersion

Elephants often gather in groups or herds to

access shared resources like waterholes or
abundant feeding areas.
Patterns of Dispersion
• A uniform dispersion
– Is one in which individuals are evenly distributed
– May be influenced by social interactions such as
territoriality

(b) Uniform. Birds nesting on small islands, such as these

king penguins on South Georgia Island in the South
Atlantic Ocean, often exhibit uniform spacing, maintained
by aggressive interactions between neighbors.

Figure 52.3b
Patterns of Dispersion
• A uniform dispersion

These plants are evenly

spaced due to their
competition for scarce water
and nutrients, which leads
them to release chemicals into
the soil that inhibit the growth
of other plants nearby.
Patterns of Dispersion
• A random dispersion
– Is one in which the position of each individual
is independent of other individuals

(c) Random. Dandelions grow from windblown seeds that

land at random and later germinate.
Demography
• 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
Life Tables
• Life table
– Is an age-specific summary of the survival
pattern of a population
– Is best constructed by following the fate of a
cohort
• The life table of Belding’s
ground squirrels
– Reveals many things about
this population
Survivorship Curves
• Survivorship curve
– Is a graphic way of representing the data in a
life table
100
0

• The survivorship curve for

Number of survivors (log

Belding’s ground squirrels 10
0
– Shows that the death Female
s
rate is relatively 1
constant 0 Male

scale)
s

1 1
0 2 4 6 8
Age 0
Figure (years)
52.4
Survivorship Curves
• Survivorship curves can be
classified into three general types
– Type I, Type II, and Type III

Type I: Shows high survival rates during early and

middle life but a steep decline in survival in older age.
Type II: Indicates a constant mortality rate throughout
the individual's life, leading to a straight line when
plotted.
Type III: Features very high mortality rates early in life,
but once individuals pass this stage, they experience
lower mortality rates.
Reproductive Rates
• A reproductive table, or fertility schedule
– Is an age-specific summary of the reproductive
rates in a population
– Describes the reproductive patterns of a
population

Table
52.2
LIFE HISTORIES
• Concept 52.2: Life history traits are products of
natural selection
• Life history traits are evolutionary outcomes
– Reflected in the development, physiology, and
behavior of an organism
Life History Diversity
• Life histories are very diverse
• Species that exhibit semelparity, or “big-bang”
reproduction
– Reproduce a single time and die

Example:
Salmon and Agave
(century plants)

Figure
52.6
• Species that exhibit iteroparity, or repeated reproduction
– Produce offspring repeatedly over time

Example: Sea turtles, oak tress or humans

“Trade-offs” and Life Histories
• Organisms have finite resources
– Which may lead to
trade-offs between
survival and
reproduction
• Some plants produce a large number of
small seeds
– Ensuring that at least some of them will
grow and eventually reproduce

Orchids produce a vast number of small seeds to

increase the likelihood that at least a portion will
survive and grow into mature plants.
• Other types of plants produce a moderate number of
large seeds
– That provide a large store of energy that will help
seedlings become established
• Parental care of smaller broods
– May also facilitate survival of offspring

An excellent example of parental care of

smaller broods is seen in kestrels. When
kestrels have smaller broods, they are able to
allocate more resources and attention to
each chick, improving the chances of survival
for their offspring.
POPULATION GROWTH
• Concept 52.3: The exponential model describes
population growth in an idealized, unlimited
environment
• It is useful to study population growth in an
idealized situation
– In order to understand the capacity of species
for increase and the conditions that may
facilitate this type of growth
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
• Zero population growth
– Occurs when the birth rate equals the death rate
• The population growth equation can be expressed as
𝑑𝑁𝑑𝑡: The rate of change in
population size over time.
𝑟: The per capita growth rate,
which is the difference between
birth and death rates.
𝑁: The population size at a given
time.
Exponential Growth
• Exponential population growth
– Is population increase under idealized conditions
• Under these conditions
– The rate of reproduction is at its maximum, called the intrinsic
rate of increase
• The equation of exponential population growth
is
𝑑𝑁𝑑𝑡: The rate at which the population
changes over time.
𝑟max: The maximum per capita growth
rate of the population under ideal
conditions.
𝑁: The population size at a given time.
Exponential Growth
• Exponential population growth
– Results in a J-shaped curve
Exponential Growth

• The J-shaped curve of exponential growth

– Is characteristic of some populations that are
rebounding
• Concept 52.4: The logistic growth model includes the concept of
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
The Logistic Growth Model
• In the logistic population growth model
– The per capita rate of increase declines as
carrying capacity is reached
• We construct the logistic model by starting with the
exponential model
– And adding an expression that reduces the per
capita rate of increase as N increases
• The logistic growth equation
– Includes K, the carrying capacity
𝑑𝑁𝑑𝑡: The rate of population
growth over time.
𝑟max: Maximum per capita growth
rate under ideal conditions.
𝑁: Current population size.
𝐾: Carrying capacity.
• A hypothetical example of logistic growth
• The logistic model of population growth
– Produces a sigmoid (S-shaped) curve
The Logistic Model and Real Populations
• The growth of laboratory populations of
paramecia
– Fits an S-shaped curve
• Some populations overshoot K
– Before settling down to a relatively stable density
• Some populations
– Fluctuate greatly around K
The Logistic Model and Life Histories

• The logistic model fits few real populations

– But is useful for estimating possible growth

• Life history traits favored by natural selection

– May vary with population density and environmental
conditions
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