Chapter 53

Population Ecology

AP Biology

• Population ecology is the study of populations in relation to their environment

– It explores how biotic and abiotic factors influence:

• Density

• Distribution

• Age structure

• Population size

• In this chapter, we will examine:

– Population structure and dynamics

– Tools and models ecologists use to analyze populations

– Factors that regulate the abundance of organisms

– Recent trends in the size and makeup of the human population

Concept 53.1: Dynamic 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

– Members of a population:

• Rely on the same resources

• Are influenced by similar environmental factors

• Are likely to interact and breed with one another

– Populations can evolve as natural selection acts on heritable variations among

individuals and changes the frequencies of various traits over time

– 3 fundamental characteristics of populations are:

• Density

• Dispersion

• Demographics

Density and Dispersion

• Populations can be described in terms of its density and

dispersion

– Density is the number of individuals per unit area or

volume

• Ex) The number of E.coli bacteria per milliliter in a test

tube

– Dispersion is the pattern of spacing among individuals

within the boundaries of the population

Density: A Dynamic Perspective • In most cases, it is impractical or impossible to count all individuals in a population

– Instead, ecologists use a variety of sampling techniques to estimate densities

and total population sizes

– Population size can be estimated by:

• Extrapolation from small samples

– Ex) Count the number of oak trees in several randomly located 100 x

100 meter plots and then calculate the average density in these

samples

• This information can then be extrapolated to estimate the

population size in the entire area

• An index of population size

– Ex) Number of nests, burrows, tracks, calls, or fecal droppings

• The mark-recapture method

• Scientists typically begin the mark-recapture method by capturing a random sample

of individuals in a population

– They then tag, or “mark,” each individual and release it

• With some species, researchers can identify individuals (ex: distinctive

markings) without physically capturing them

– After a few days to weeks, once these marked individuals mix back into the

population, scientists capture and sample a second set of individuals

• Population size (N) can then be estimated using the following equation:

– N = mn/x, where:

• N = estimated population size

• m = total number of individuals marked and released in the 1st

sampling

• n = total number of animals recaptured in the 2nd sampling

• x = number of animals recaptured in the 2nd sampling

• The mark-recapture method assumes that:

– Marked and unmarked individuals have the same probability of being captured

(sampled)

– The marked organisms have mixed completely back into the population

– No individuals are born, die, immigrate, or emigrate during the resampling

interval

• Sample problem: Researchers want to determine the estimated size of an

endangered population of dolphins

– They identify 180 dolphins by photographing their distinctive dorsal fins from a

boat

– A few weeks later, the researchers

encounter 44 dolphins in this population,

7 of which had been photographed before

– What is the estimated number of dolphins

in this population?

Fig. 53-2

APPLICATION

Hector’s dolphins

• Density is not a static (unchanging) property

– It changes as individuals are added or removed from a population

• Additions occur through birth and immigration

– Immigration is the influx of new individuals from other areas

• Factors that remove individuals from a population are death and

emigration

– Emigration is the

movement of individuals

out of a population

Fig. 53-3

Births

Births and immigrationadd individuals toa population.

Immigration

Deaths and emigrationremove individualsfrom a population.

Deaths

Emigration

Patterns of Dispersion

• Spacing of individuals within a population of a specific density may vary substantially

– Patterns of dispersion within a given geographical area are influenced by

• Environmental factors

– Ex) Some patches of habitat within the geographic range of a

population are more suitable than others

• Social factors – interactions between members of the population

– There are 3 common patterns of dispersion seen in a population’s geographic

range:

• Clumped

• Uniform

• Random

• In a clumped pattern of dispersion, individuals aggregate in patches

– A clumped dispersion may be influenced by:

• Resource availability

– Ex) Plants and fungi are often clumped where soil conditions and

other environmental factors favor germination and growth

• Behavior

– Ex) A wolf pack is more likely than a single wolf to subdue a moose or

other large prey animals

– Ex) Sea stars group together in

tide pools so they may breed

successfully

Video: Flapping Geese (Clumped)

Fig. 53-4a

(a) Clumped

• A uniform dispersion is one in which individuals are evenly distributed

– Animals often exhibit uniform dispersion as a result of antagonistic social

interactions:

• Ex) Some plants secrete chemicals that inhibit growth and germination of

nearby individuals that could compete for resources

• Territoriality: the defense of a bounded physical space against

encroachment by other individuals

Video: Albatross Courtship (Uniform)

Fig. 53-4b

(b) Uniform

• In a random dispersion, the position of each individual is unpredictable and

independent of other individuals

– It occurs:

• In the absence of strong attractions or repulsions among individuals of a

population

• Where key physical or chemical factors are relatively homogeneous (the

same) across the geographical area

– Ex) Many plants that grow from windblown seeds (ex: dandelions)

have random distribution due to

the unpredictability of where their

seeds will land

Video: Prokaryotic Flagella (Salmonella typhimurium)

Fig. 53-4c

(c) Random

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

• A useful way of summarizing the vital statistics of a population is with a life table

– A life table is an age-specific summary of the survival patterns of a population Table 53-1

• The best way to construct a life table if to follow the fate of a cohort, a group of

individuals of the same age, from birth until they are all dead

– The number of individuals that die in each age group is tracked during this time

– From this, the proportion of the cohort surviving from one age to the next can

be calculated

• The life table of Belding’s ground squirrels reveals many things about this population

– Ex) A comparison

of the 5th and 10th

columns reveals

that males have a

higher death rate

than females

Table 53-1

Survivorship Curves

• A survivorship curve is a graphic way of representing the data in a life table

– This curve plots the proportion or number of individuals in a cohort still alive at

each age

• In general, a survivorship curve is constructed with a cohort of a specified

size (ex: 1,000 individuals)

• To obtain this number for a specific population, we can multiply the

proportion of individuals alive at the start of each year by 1,000

– This gives the number of

individuals within the

cohort that are still alive at

the start of each year

– These numbers can then

be plotted against age

for both males and females

Fig. 53-5

Age (years)

20 4 86

10

101

1,000

100N

um

ber

of

su

rviv

ors

(lo

g s

cale

)

Males

Females

• The survivorship curve for Belding’s ground squirrels shows a relatively

constant death rate

– It also indicates a lower overall survival rate for males as compared to

females Fig. 53-5

Age (years)

20 4 86

10

101

1,000

100

Nu

mb

er

of

su

rviv

ors

(lo

g s

cale

)

Males

Females

• Survivorship curves can be classified into three general types:

– Type I: low death rates (flat) during early and middle life, then an increase

(drops steeply) among older age groups

• Many large mammals, including humans, that produce few offspring but

with much parental care exhibit this type of curve

– Type II: the death rate is constant (straight line) over the organism’s life span

• Occurs mainly in rodents, various invertebrates, some lizards, and some

annual plants

– Type III: high death rates (sharp drop) for the young, then a slower (flattens)

death rate for survivors

• This type of curve is usually

associated with organisms that

produce very large numbers of

offspring but provide to to no

parental care

– Ex) Long-lived plants,

many fishes, and most

marine invertebrates

Fig. 53-6

1,000

100

10

10 50 100

II

III

Percentage of maximum life span

Nu

mb

er

of

su

rviv

ors

(lo

g s

cale

)

I

• Many species fall somewhere between these basic types of

survivorship or show more complex patterns

– Ex) Mortality is often high among the youngest members of

bird population (as in a Type III curve), but it becomes fairly

constant among adults (as in a Type II curve)

– Ex) Some invertebrates (crabs) may show a “stair-

stepped” curve, with brief periods of increased mortality

during molts, followed by periods of lower mortality

experienced while their exoskeleton in hard

Reproductive Rates

• In populations not experiencing immigration or emigration, survivorship is

only one of two key factors that affect population size

– The other key factor is reproductive rate

• Demographers therefore

often view populations in

terms of females giving rise

to new females, since only

they can produce offspring

– A reproductive table, or fertility

schedule, is an age-specific

summary of the reproductive rates

in a population

Table 53-2

Table 53-2

• A reproductive table is constructed by measuring the reproductive output of

a cohort from birth until death

– The average number of female offspring is calculated by multiplying the

proportion of females at each that are breeding by the average number

of females in the litters of those

females

• Reproductive tables can help identify

reproductive patterns of a population

– Ex) For Belding’s ground

squirrels, reproductive output

rises to a peak at age 4 and

then falls off in older females

Concept Check 53.1

• 1) One species of forest bird is highly territorial, while a second lives

in flocks. Predict each species’ likely pattern of dispersion, and

explain.

• 2) Each female of a particular fish species produces millions of eggs

per year. Draw and label the most likely survivorship curve for this

species, and explain your choice.

• 3) As noted in Figure 53.2 (pp. 1175), an important assumption of the

mark-recapture method is that marked individuals have the same

probability of being recaptured as unmarked individuals. Describe a

situation where this assumption might not be valid, and explain how

the estimate of population size would be affected.

Concept 53.2: Life history traits are products of

natural selection

• An organism’s life history consists of the traits that affect its schedule of

reproduction and survival, from birth through death, including:

– The age at which reproduction begins

– How often the organism reproduces

– How many offspring are produced during each reproductive cycle

• With the exception of humans, organisms do not choose consciously when

to reproduce or how many offspring to have

– Instead, these traits are evolutionary outcomes reflected in the

development, physiology, and behavior of these organisms

Evolution and Life History Diversity

• Life histories are very diverse

– Species that exhibit semelparity, or big-bang reproduction, reproduce once

and die

• Ex) Spawning salmon produce 1000s of eggs in a single reproductive

opportunity before they die

• Ex) The agave (“century”) plant grows for years before sending up a single

large flowering stalk that produces seeds, and

then dies

– Species that exhibit iteroparity, or repeated

reproduction, produce offspring repeatedly

• Ex) Many animals produce annually for

many years

Fig. 53-7

• There appear to be 2 critical factors that contribute to the evolution of semelparity

versus iteroparity

– The survival rate of the offspring is low

– The likelihood that the adult will survive to reproduce again

• Highly variable or unpredictable environments tend to have low offspring survival

rates and thus generally favor big-bang reproduction,

– Dependable, more stable, environments tend to favor repeated reproduction,

since individuals are more likely to survive to reproductive age

• In these cases, competition for resources may be intense, meaning that

fewer, but larger and more well-provisioned offspring should have a better

chance of surviving to reproductive age

– Many organisms also have life histories that are intermediate between the two

extremes of semelparity and iteroparity

• Ex) Oak trees live a long time but produce relatively large numbers of

offspring

“Trade-offs” and Life Histories

• Organisms have finite resources, which may lead to trade-offs between survival and

reproduction

– Selective pressures influence the trade-off between the number and size of

offspring

• Plants and animals whose young are subject to high mortality rates often

produce large numbers of relatively small offspring

– Ex) Most weedy plants (ex: dandelions) grow quickly and produce a

large number of seeds to ensure that at

least some seeds will eventually grow

and reproduce

• In other organisms, extra investment on the

part of the parent greatly increases the

offspring’s chances of survival

– Ex) Some plants (ex: coconut palm)

produce a more moderate number of

very large seeds that contain enough

endosperm to ensure the success of

most of their offspring

Fig. 53-9

(a) Dandelion

(b) Coconut palm

Concept Check 53.2

• 1) Consider 2 rivers: one is spring fed and has a constant water volume and

temperature year-round; the other drains a desert landscape and floods and

dries out at unpredictable intervals. Which river would you predict is more

likely to support many species of iteroparous animals? Why?

• 2) In the fish called the peacock wrasse (Symphodus tinca), females

disperse some of their eggs widely and lay other eggs in a nest. Only the

latter receive parental care. Explain the trade-offs in reproduction that this

behavior illustrates.

• 3) Mice that cannot find enough food or that experience other forms of stress

will sometimes abandon their young. Explain how this behavior might have

evolved in the context of reproductive trade-offs and life history.

Concept 53.3: The exponential model describes

population growth in an idealized, unlimited environment

• Populations of all species, regardless of their life histories, have

the potential to expand greatly when resources are abundant

– Though unlimited growth does not occur for long in nature,

it is useful to study population growth in such an idealized

situation

• These situations help us understand:

– The capacity of species to increase

– The conditions that may facilitate this growth

Per Capita Rate of Increase

• Consider a population consisting of a few individuals living in an ideal, unlimited

environment:

– Under these conditions, there are no environmental restrictions on the abilities

of individuals to:

• Harvest energy

• Grow

• Reproduce

– The population will increase in size with every birth (B) and immigration event

(I)

• It will decrease in size with every death (D) and emigration event (E)

• Thus, the change in population size ( P ) during a fixed time interval can

be calculated using the formula:

– P = (B + I) – (D + E)

• If immigration and emigration are ignored, a population’s growth rate over time (t)

equals birth rate minus death rate

P/ t = B- D

• Next, this simple model can be converted to express births or deaths as an average

number per individual (per capita) during the specified time interval

– The per capita birth rate (b) is the number of offspring produced per unit time

by an average member of the population

• Ex) If there are 34 births per year in a population of 1000, the annual per

capita birth rate is 34/1,000 or 0.034

– From the annual per capita birth rate, we can then calculate the expected

number of births per year in a population of any size, using the formula:

B = bN

• Ex) For a population of 500 with an annual per capita birth rate of 0.034, B

= 0.034 x 500 = 17 births/year

• The per capita death rate (d) can be calculated in a similar fashion to determine the

expected number of deaths per unit time in a population of any size:

D = dN

– Ex) If d = 0.016 per year, then we would expect 16 deaths per year in a

population of 1000 (D = 0.016 X 1000 = 16)

• Using substitution, we can now revise the population growth equation again:

P/ t = B – D = bN – dN

• Because population ecologists are most interested in the difference between per

capita birth rate and per capita death rate, known as the per capita rate of increase

(r), we can make one more revision to the equation:

– If r = b – d, then by substitution:

P/ t = B- D = bN – dN = N(b – d) = rN

• The value of per capita rate rate of increase (r)

indicates if a population is changing size

– If r > 0, the population is growing

– If r < 0, the population is declining

– If r = 0, zero population growth (ZPG)

occurs, where the birth rate equals the death

rate

Exponential Growth

• Exponential (geometric) population growth is population increase

under idealized conditions:

– All members have access to abundant food

– All members are free to reproduce at their physiological capacity

• Under these conditions, the rate of reproduction is at its maximum

(rmax), called the intrinsic rate of increase

– Thus, the equation for

exponential growth is:

• dN/dt = rmax N

Fig. 53-10

Number of generations

0 5 10 15

0

500

1,000

1,500

2,000

1.0N=dN

dt

0.5N=dN

dt

Po

pu

lati

on

siz

e (

N)

Exponential Growth

• A graph of this equation results in a J-shaped growth curve when population size is

plotted over time

– Although the maximum rate of increase is constant, the population accumulates

more new individuals per unit of time when it is large as compared to when it is

small

• The curve therefore gets progressively steeper over time, as N increases

• The J-shaped curve of exponential growth is characteristic of some populations that

are:

– Introduced into a new environment

– Rebounding after their numbers have

been drastically reduced by a

catastrophic event

• Ex) African elephant population of

Kruger National Park in South

Africa after hunting was prohibited

Fig. 53-11

8,000

6,000

4,000

2,000

01920 1940 1960 1980

Year

Ele

ph

an

t p

op

ula

tio

n

1900

Concept Check 53.3

• 1) Explain why a constant rate of increase (rmax) for a population

produces a growth graph that is J-shaped rather than a straight line.

• 2) Where is exponential growth by a plant population more likely – on

a newly formed volcanic island or in a mature, undisturbed rain

forest? Why?

• 3) In 2006, the US had a population of about 300 million people. If

there were 14 births and 8 deaths per 1,000 people, what was the

country’s net population growth that year (ignoring immigration and

emigration, which are substantial)? Do you think the US is currently

experiencing exponential population growth? Explain.

Concept 53.4: 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 because

resources become limited as population increases

– 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 of a given environment varies with the abundance of limited

resources, including:

• Energy

• Shelter

• Refuge from predators

• Nutrient availability

• Water

• Suitable nesting sites

The Logistic Growth Model

• We can thus modify our mathematical model to incorporate changes in growth rate

as a population nears carrying capacity

– In the logistic population growth model, the per capita rate of increase

approaches zero as carrying capacity is reached

• We construct the logistic model by starting with the exponential model and

adding an expression that reduces per capita rate of increase as N

approaches K

– If the maximum sustainable population size (carrying capacity) is K,

then K-N is the number of additional individuals the environment can

support

– The expression (K-N)/N is therefore the fraction of K that is still

available for population growth

dN dt

(K N)

K rmax N

Table 53-3

• When N is small compared to K (small population), the term (K-N)/K is large, close to

1

– In this case, the per capita rate of increase (Rmax(K-N)/K) is close to the

maximum rate of increase predicted by the exponential growth model

• As N increases and resources become

limited, however, then (K-N)/K becomes

a small fraction, which in turn decreases

the per capita rate (Rmax(K-N)/K)

– When N = K, the population

stops growing

• The logistic model of population growth produces a sigmoid (S-shaped)

curve when N is plotted over time

– New individuals are added to the population most rapidly at

intermediate population sizes, during which time:

• The breeding population is of a substantial size

• There is much available

space and resources in

the environment

– Then population growth rate

then slows dramatically as

N approaches K

Fig. 53-12

2,000

1,500

1,000

500

00 5 10 15

Number of generations

Po

pu

lati

on

siz

e (

N)

Exponentialgrowth

1.0N=dN

dt

1.0N=dN

dt

K = 1,500

Logistic growth

1,500 – N

1,500

The Logistic Model and Real Populations

• The growth of laboratory populations of some small animals, such as

beetles, crustaceans, bacteria, and paramecia fits an S-shaped curve

– These organisms are grown in a constant environment lacking

predators and competitors

• However, these

conditions rarely

occur in nature

Fig. 53-13a

1,000

800

600

400

200

00 5 10 15

Time (days)

Nu

mb

er

of

Para

meciu

m/m

L

(a) A Paramecium population in the lab

• Some of the basic assumptions built into the logistic model clearly do not apply to all

populations

– There is often a lag time before the negative effects of an increasing population

are realized

• Some populations will thus actually overshoot K before settling down to a

relatively stable density

– Ex) As food becomes limited in a population, females may call on

their energy reserves

to continue reproducing

for a short time

• If the population then drops

below carrying capacity,

there will be a delay in

population growth until new

offspring are actually born

Fig. 53-13b

Nu

mb

er

of

Dap

hn

ia/5

0 m

L

0

30

60

90

180

150

120

0 20 40 60 80 100 120 140 160

Time (days)

(b) A Daphnia population in the lab

• Still other populations fluctuate greatly and make it difficult to define K

– Some populations show an Allee effect, in which individuals have a

more difficult time surviving or reproducing if the population size is

too small

• Ex) A single plant may be damaged by excessive wind if it is

standing alone, but it would be protected in a clump of

individuals

– This is contrary to the logistical model of population growth, which

incorporates the idea that, regardless of population density, each

individual added to a population has the same negative effect on

population growth rate

The Logistic Model and Life Histories

• Different life history traits are favored by natural selection under the different

per capita growth rates predicted for low and high density populations,

relative to their carrying capacity

– At low population densities, selection favorsadaptations that promote

rapid reproduction should be favored

• Ex) Production of numerous, small offspring

– At high population densities, selection favors adaptations that allow

organisms to survive and reproduce with few resources

• Ex) Competitive ability and efficient use of resources should be

favored

The Logistic Model and Life Histories

• Ecologists have attempted to connect these differences in favored traits at different

population densities with the logistic growth model:

– K-selection, or density-dependent selection, selects for life history traits that

are sensitive to population density

• K-selection is said to operate in populations living at a density near

carrying capacity, where competition among individuals is relatively strong

– r-selection, or density-independent selection, selects for life history traits that

maximize reproduction

• R-selection is said to maximize the per capita rate of increase (r) and

occurs in environments in which population densities are well below

carrying capacity or where individuals face little competition

– These names follow from the variables of the logistic equation

Concept Check 53.4

• 1) Explain why a population that fits the logistic growth model

increases more rapidly at intermediate size than at relatively small or

large sizes.

• 2) When a farmer abandons a field, it is quickly colonized by fast-

growing weeds. Are these species more likely to be K-selected or R-

selected species? Explain.

• 3) Add rows to Table 53.3 (pp. 1184) for three cases where N > K:N

= 1,600, 1,750, and 2,000. What is the population growth rate in

each case? In which portion of Figure 53.13b (pp. 1185) is the

Daphnia population changing in a way that corresponds to the values

you calculated?

Concept 53.5: Many factors that regulate

population growth are density dependent

• There are two general questions about regulation

of population growth:

– What environmental factors stop a population from

growing indefinitely?

– Why do some populations show radical

fluctuations in size over time, while others remain

stable?

Population Change and Population Density

• To understand why a population stops growing, it is helpful to first examine the

effects of population density on birth and death rates

– Populations can be affected by population density in one of 2 ways

• 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

– As a result of various combinations of density-dependent and density-

independent regulation, populations may stop growing and reach equilibrium Fig. 53-15

(a) Both birth rate and death rate vary.

Population density

Density-dependentbirth rate

Equilibriumdensity

Density-dependentdeath rate

Bir

th o

r d

eath

rate

pe

r c

ap

ita

(b) Birth rate varies; death rate is constant.

Population density

Density-dependentbirth rate

Equilibriumdensity

Density-independentdeath rate

(c) Death rate varies; birth rate is constant.

Population density

Density-dependentdeath rate

Equilibriumdensity

Density-independentbirth rate

Bir

th o

r d

eath

rate

pe

r c

ap

ita

Fig. 53-15

(a) Both birth rate and death rate vary.

Population density

Density-dependentbirth rate

Equilibriumdensity

Density-dependentdeath rate

Bir

th o

r d

eath

rate

per

cap

ita

(b) Birth rate varies; death rate is constant.

Population density

Density-dependentbirth rate

Equilibriumdensity

Density-independentdeath rate

(c) Death rate varies; birth rate is constant.

Population density

Density-dependentdeath rate

Equilibriumdensity

Density-independentbirth rate

Bir

th o

r d

eath

rate

per

cap

ita

Density-Dependent Population Regulation

• Density-dependent birth and death rates are an example of

negative feedback that regulates population growth

– They are affected by many factors, such as:

• Competition for resources

• Territoriality

• Disease, predation

• Toxic wastes

• Intrinsic factors

Fig. 53-16

Population size

100

80

60

40

20

0200 400 500 600300P

erc

en

tag

e o

f ju

ven

iles

pro

du

cin

g lam

bs

Competition for Resources

• In crowded populations, increasing population density:

– Intensifies competition for resources

– Thus results in a lower birth rate

• Ex) Reproduction by juvenille Soay sheep on Hirta Island drops

dramatically as population size

increases

Fig. 53-17

(a) Cheetah marking its territory

(b) Gannets

Territoriality

• In many vertebrates and some invertebrates, competition for territory may

limit population density

– Maintaining a territory increases

the likelihood of capturing enough

food to reproduce and provides more

opportunity to locate nesting sites

• Ex) Cheetahs are highly

territorial, using chemical

communication to warn other

cheetahs of their boundaries

• Ex) Gannets that cannot obtain a

nesting site do not reproduce

Disease

• Population density can influence the health and

survival of organisms

– In dense populations, pathogens can spread

more rapidly

• Ex) In humans, the air-borne lung disease

tuberculosis strikes a greater percentage of people

living in densely populated cities

Predation

• Predation may be an important cause of density-dependent

mortality in prey species

– As a prey population builds up, predators may feed

preferentially on that species

• Ex) Trout may concentrate on a particular species of insect that

is emerging from its aquatic larval stage for a few days and

then switch to eating another insect species that is more

abundant

Toxic Wastes

• Accumulation of toxic wastes can contribute to density-

dependent regulation of population size

– In lab cultures of microorganisms, metabolic by-products

accumulate as populations grow, poisoning the organisms

• Ex) The alcohol content of wine is usually less than

13% because this is the maximum concentration of

ethanol that most wine-producing yeast cells can

tolerate

Intrinsic Factors

• For some populations, intrinsic (physiological)

factors appear to regulate population size

– Ex) High population densities in mice can

induce a stress syndrome in which hormonal

changes delay sexual maturation, cause

reproductive organs to shrink, and depress

the immune system

Population Dynamics

• We will now examine why some populations fluctuate

dramatically while others remain relatively stable

– The study of population dynamics focuses on the

complex interactions between biotic and abiotic factors

that cause variation in population size from:

• Year to year

• Place to place

• Season to season

Stability and Fluctuation

• Long-term population studies have challenged the hypothesis that

populations of large mammals are relatively stable over time

– Weather can affect population size over time

• Harsh weather, particularly cold, wet winters weakens Soay sheep

and decreases food availability, leading to decreased population

size

• Conversely, when sheep

numbers are low and

weather is mild, food is readily

available and the

population grows quickly

Fig. 53-18

2,100

1,900

1,700

1,500

1,300

1,100

900

700

500

01955 1965 1975 1985 1995 2005

Year

Nu

mb

er

of

sh

eep

• Changes in predation pressure can also drive population

fluctuations

– The moose population on Isle Royale in Lake Superior

fluctuates along with that of its main predator, the wolf Fig. 53-19

Wolves Moose

2,500

2,000

1,500

1,000

500

Nu

mb

er

of

mo

os

e

0

Nu

mb

er

of

wo

lve

s

50

40

30

20

10

01955 1965 1975 1985 1995 2005

Year

Population Cycles: Scientific Inquiry

• While many populations fluctuate at unpredictable intervals, some populations

undergo regular boom-and-bust cycles

– Ex) Lynx populations follow the 10 year boom-and-bust cycle of hare

populations, their main food source

• Three hypotheses have been proposed to explain the hare’s 10-year interval

– 1) These cycles may be caused by food shortage during winter

– 2) These cycles may be due to predator-prey interaction

– 3) The size of the hare populations may vary with

sunspot activity, which also undergoes cyclic

changes

• When sunspot activity is low, slightly less

atmospheric ozone is produced, resulting in

more UV radiation reaching Earth’s surface

• In response, plants produce more UV-

blocking chemicals and thus fewer chemicals

that deter herbivores, increasing to quality of

the hares’ food

Fig. 53-20

Snowshoe hare

Lynx

Nu

mb

er

of

lyn

x(t

ho

usan

ds)

Nu

mb

er

of

hare

s(t

ho

usan

ds)

160

120

80

40

01850 1875 1900 1925

Year

9

6

3

0

• 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 in the

Yukon for 20 years

• The whole population increased in size by ~3X but continued to

cycle

• No hares appeared to have died of starvation

– Thus, food supplies alone do not cause the hare cycles observed, and

this hypothesis is rejected

• Hypothesis 2 : The hare’s population cycle is driven by pressure from other predators

– During the same 20-year study of hares in the Yukon field ecologists tracked

individual hares using radio collars to determine why they died

• 90% of the hares were killed by predators

• These data support this second hypothesis

– Ecologists also excluded predators from one area with electric fences and

provided the hares with extra food in another area within in the first

• They found that the hare cycle is largely driven by excessive predation and

that food availability also plays an important role

– Perhaps better-fed hares are more likely to escape from predators

• Hypothesis 3: The hare’s population cycle is linked to sunspot cycles

– There is good correlation between sunspot activity and hare population

size

• Periods of low sunspot activity were followed by peaks in the hare

population

– The results of all these experiments suggest that:

• Both predation and sunspot activity may regulate the cycling of

hare numbers

• Food availability plays a less important role

Immigration, Emigration, and Metapopulations • Immigration and emigration also influence populations, especially when many local

populations are linked

– Metapopulations are groups of populations linked by immigration and

emigration

• High levels of immigration combined with higher survival can result in greater stability

in populations

– Ex) On the Aland Islands of Finland, local populations of butterflies (filled

circles) are found in only a fraction of the

suitable habitat patches (open circles) at

any given time

• Individuals can move between local

populations and colonize unoccupied

patches

• New populations of butterflies thus

regularly reappear as existing populations

become extinct

Fig. 53-21

AlandIslands

EUROPE

Occupied patch

Unoccupied patch5 km

?

Concept Check 53.5

• 1) Identify 3 density-dependent factors that limit population

size, and explain how each exerts negative feedback.

• 2) Describe 3 attributes of habitat patches that could affect

population density and rates of immigration and emigration.

• 3) If you were studying an endangered species that, like the

snowshoe hare, has a 10-year population cycle, how long

would you need to study the species to determine if its

population size is declining? Explain.

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

• In only the two centuries following 1650, the population doubled from 500

million to 1 billion people

• The population doubled again to 2 billion between 1850 and 1930

• The population doubled a 3rd time by 1975 to > 4 billion

– The global population in now

more than 6.6 billion people and

is increasing by ~75 million each

year (200,000 people/day)

• Population ecologists predict

a population of 7.8-10.8

billion people on Earth by the

year 2050

Fig. 53-22

8000B.C.E.

4000B.C.E.

3000B.C.E.

2000B.C.E.

1000B.C.E.

0 1000C.E.

2000C.E.

0

1

2

3

4

5

6

The Plague

Hu

man

po

pu

lati

on

(b

illi

on

s)

7

• Though the global population is still growing, the rate of growth began to slow during

the 1960s

– The annual rate of increase in the global population peaked at 2.2% in 1962

– By 2005, it declined to 1.15%

– Current models predict a continued decline in annual growth rate to just over

0.4% by 2050

• The reduction in growth rate over the past

4 decades shows that the human

population has departed from true

exponential growth

– This is the result of fundamental

changes in population dynamics due

to diseases and voluntary

population control

Fig. 53-23

2005

Projecteddata

An

nu

al

pe

rce

nt

inc

rea

se

Year

1950 1975 2000 2025 2050

2.2

2.0

1.8

1.6

1.4

1.2

1.0

0.8

0.6

0.4

0.2

0

Regional Patterns of Population Change • To maintain population stability in a specific region, a human population’s birth rate

must equal its death rate

– This can occur can in one of two configurations:

• Zero population growth = High birth rate – High death rate

• Zero population growth = Low birth rate – Low death rate

• Demographic transition is the move

from the first state toward the second

state

– It is associated with:

• An increase in the quality

of health care and sanitation

• Improved access to

education, especially for

women

Fig. 53-24

1750 1800 1900 1950 2000 2050

Year

1850

Sweden Mexico

Birth rate Birth rateDeath rateDeath rate

0

10

20

30

40

50

Bir

th o

r d

eath

rate

per

1,0

00 p

eo

ple

• Most of the current global population growth is concentrated in developing countries

– Because death rates have declined rapidly in countries since 1950, variability in

birth rate is the main factor affecting local population growth

• In developing countries, though birth rates are declining, they still remain

high compared to those of developed countries

• In industrialized nations, populations are actually near equilibrium, with

reproductive rates near replacement level

– In some of these countries, total reproductive rates are even below

replacement, meaning these populations will decline over time at the

current birth rate

• Ex) Canada, Japan, Germany, UK

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 in a population

– Age structure is commonly graphed as “pyramids”

• Some are bottom-heavy (Afghanistan), with a large majority of young

individuals

• Some are relatively even, showing little (U.S.) to no (Italy) growth

– The U.S. is still growing slowly due to:

• Many “baby boomers” and their offspring still being of

reproductive age

• Immigration from

other countries

Fig. 53-25

Rapid growthAfghanistan

Male Female Age AgeMale Female

Slow growthUnited States

Male Female

No growthItaly

85+80–8475–7970–74

60–6465–69

55–5950–5445–4940–4435–3930–3425–2920–2415–19

0–45–9

10–14

85+80–8475–7970–74

60–6465–69

55–5950–5445–4940–4435–3930–3425–2920–2415–19

0–45–9

10–14

10 108 866 4 422 0

Percent of population Percent of population Percent of population

66 4 422 08 8 66 4 422 08 8

• Age structure diagrams can predict a population’s growth trends

– They can also illuminate social conditions and help us plan for the

future

• Ex) Employment and education opportunities will continue to be a

significant problem for Afghanistan, due to their large young

population

• Ex) In Italy and the U.S., a decreasing proportion of younger

working-age people will soon be supporting an increasing

population of retired “boomers”

– This demographic feature has made the future of Social

Security and Medicare a major political issue in the U.S.

Infant Mortality and Life Expectancy

• Infant mortality and life expectancy at birth vary greatly among developed and

developing countries

– Infant mortality is the number of infant deaths per 1,000 live births

– Life expectancy at birth is the predicted average length of life at birth

• In industrialized countries,

infant mortality is low while

life expectancy is high

– The reverse is true of

less industrialized countries

Fig. 53-26

Less indus-trialized

countries

Indus-trialized

countries

60

50

40

30

20

10

0 0

20

40

80

Lif

e e

xp

ec

tan

cy (

ye

ars

)

Infa

nt

mo

rta

lity

(d

ea

ths

pe

r 1

,000

bir

ths

)

Less indus-trialized

countries

Indus-trialized

countries

60

Global Carrying Capacity

• How many humans can the biosphere support?

– The carrying capacity of Earth for humans is uncertain

• The average estimate is 10–15 billion

– Ecologists use different methods to estimate carrying capacity

• Some use curves like that produced by the logistic equation to predict the

future maximum of the human population

• Others generalize from existing “maximum” population densities in

overpopulated regions and multiply this number by the area of habitable

land

• Still others base their estimates on single limiting factors, including the

amount of available farmland or the average yield of crops

Limits on Human Population Size

• A more comprehensive approach to estimating carrying capacity is to

recognize that humans have multiple constraints:

– Food and water

– Fuel

– Building materials

– Clothing

• 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

Limits on Human Population Size

• One way to estimate the ecological footprint of the entire human population

is to add up all the ecologically productive land on the planet and divide by

the population

– This calculation yields ~2 hectares (ha) per person

• Reserving some land for parks and conservation means reducing

this allotment to 10.7 ha/person

• Therefore, anyone who consumes resources that require more than

1.7 ha to produce is said to be using an unsustainable share of

Earth’s resources

– A typical ecological footprint for a person in the U.S. is ~10 ha

Limits on Human Population Size • Ecologists sometimes calculate ecological footprints using other currencies besides

land areas

– Ex) The amount of photosynthesis that occurs on Earth is finite, since it is

constrained by the amount of land and sea area, as well as by the sun’s

radiation

• Scientists have studied the extent to which people around the world

consume 7 types of photosynthetic products:

– Plant foods

– Wood for building and fuel

– Paper

– Fiber

– Meat

– Milk

– Eggs

Limits on Human Population Size

• Areas with higher population densities (China, India) have higher consumption rates

– However, areas of much lower population (Europe, U.S.) density have higher

per capita (average/person) consumption, leading to equally high consumption

rates

• These areas have consumption rates as much as 400X greater the rate at

which photosynthetic products are produced in those areas

Fig. 53-27

Log (g carbon/year)

13.4

9.8

5.8

Not analyzed

• Our carrying capacity could potentially be limited by:

– Food

– Space

– Nonrenewable resources: metals, fossil fuels

– Fresh water

– Buildup of wastes

• Technology has undoubtedly increased Earth’s carrying

capacity for humans

– However, no population can continue to grow

indefinitely

Concept 53.6

• 1) How does a human population’s age structure

affect its growth rate?

• 2) How has the growth of Earth’s human population

changed in recent decades? Give your answer in

terms of growth rate and the number of people added

each year.

• 3) What choices can you make that influence your

own ecological footprint?

You should now be able to: 1. Define and distinguish between the following sets of terms: density and

dispersion; clumped dispersion, uniform dispersion, and random

dispersion; life table and reproductive table; Type I, Type II, and Type III

survivorship curves; semelparity and iteroparity; r-selected populations and

K-selected populations

2. Explain how ecologists may estimate the density of a species

3. Explain how limited resources and trade-offs may affect life histories

4. Compare the exponential and logistic models of population growth

5. Explain how density-dependent and density-independent factors may

affect population growth

6. Explain how biotic and abiotic factors may work together to control a

population’s growth

7. Describe the problems associated with estimating Earth’s carrying capacity

for the human species

8. Define the demographic transition