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Biodiversity and Conservation: Extinctions

The gradual process of becoming extinct is known as
background extinction.

Mass extinctions: When a large percentage of all living species
become extinct in a relatively short period of time.

250 MYA: Over
90% of species
died
EXTINCTION RATES
Biodiversity and Conservation: Extinctions
ESTIMATED NUMBER OF EXTINCTIONS SINCE 1600
Group
Mainland
Island
Ocean
Total
Approximate
Number of
Species
Percent of
Group
Extinct
Mammals
30
51
4
85
4000
2.1
Birds
21
92
0
113
9000
1.3
Reptiles
1
20
0
21
6300
0.3
Amphibians
2
0
0
2
4200
0.05
Fish
22
1
0
23
19,100
0.1
Invertebrates
49
48
1
98
1,000,000+
0.01
Flowering
Plants
245
139
0
384
250,000
0.2
Biodiversity and Conservation: Extinctions
Cretaceous Period (65
MYA)
Triassic Period (200 MYA)
Permian Period (250 MYA)
FIVE MOST RECENT MASS
Devonian Period (360
MYA)
EXTINCTIONS
Ordovician Period (444
MYA)
LIMITS TO GROWTH
Copyright Pearson Prentice Hall
Population Ecology: Population Growth Rate
 Population

growth models
Limits to exponential growth

Population Density (the number of individuals per unit of land
area or water volume) increases as well

Competition follows as nutrients and resources are used up

The limit to population size that a particular environment can
support is called carrying capacity (k)
POPULATION LIMITING FACTORS
A
limiting nutrient is an example of a more general
ecological concept: a limiting factor.
 In
the context of populations, a limiting factor is a
factor that causes population growth to decrease.
LIMITING FACTORS
Copyright Pearson Prentice Hall
 Population
sizes are controlled by various
interactions among organisms that share a
community.
 Predation
and competition are two
interactions that control populations.
ORGANISM INTERACTIONS
Limiting
Factors
 The
primary productivity of an ecosystem
can be reduced when there is an
insufficient supply of a particular nutrient.
 Ecologists
nutrients.
call such substances limiting
LIMITING FACTORS
Copyright Pearson Prentice Hall
POPULATION DENSITY

Let’s say our classroom is 600 sq. ft.
In 3rd hour and fifth hour, there are 25 students in the class.
The population density for 3rd and 5fth hour is 25 students/600
ft² or .04 students/ft².
In 6th hour, there are only 19 students in
the class. Is the population density
higher or lower?
SIX NEW STUDENTS WERE ADDED TO SIXTH
HOUR. THE POPULATION DENSITIES OF ALL
THE CLASSES IS NOW THE SAME.
THE SCHOOL IS SPONSORING AN EVENT
THAT ALLOWS STUDENTS TO MISS 3RD, 5TH,
AND 6TH HOURS. WHICH CLASSES WILL BE
MOST EFFECTED?

All equally effected! The event will disrupt class regardless
of size – everyone will have the opportunity to go.
ITS FLU SEASON, AND LOTS OF SICK STUDENTS ARE
COMING TO SCHOOL. THEY ARE COUGHING,
SNEEZING, AND TOUCHING EVERYTHING. TEN
PERCENT OF MS. SONLEITNER’S STUDENTS HAVE THE
FLU, BUT ARE SO DEDICATED THEY COME TO CLASS
ANYWAY. IF MS. SONLEITNER WIPES DOWN EVERY
TABLE BEFORE EVERY CLASS, WHICH CLASS WILL BE
MOST AFFECTED BY THE FLU?
3rd and 5th hours, because they have the
greatest population density. A larger number
of students will be infected and have
opportunity to infect a larger number of
healthy students.
POPULATION CHARACTERISTICS
1.
Population Density:

2.
The number of organisms per unit
area
Spatial Distribution:

Dispersion: The pattern of spacing a
population within an area

3 main types of dispersion


Clumped

Uniform

Random
The primary cause of
dispersion is resource
availability

Population dynamics – study of how characteristics of a population
changes in response to changes in the environmental conditions

Populations differ in

Distribution

Numbers

Age structure
POPULATIONS HAVE CERTAIN
CHARACTERISTICS
 Random
 Independent
of
other organisms
 No
DISTRIBUTION PATTERNS
habitat
preference
 Uniform
 Even
spacing
 Evidence
DISTRIBUTION PATTERNS
for intraspecific competition
(among other sea
otters)
 Clumped
 Organisms
tend to
be together
 Habitat
preference
 Behavioral
DISTRIBUTION PATTERNS
preference such as
herding
 Most
common!
WHY CLUMPING?

Species tend to cluster where
resources are available

Protects some animals from
predators

Packs allow some to get prey

Temporary groups for mating
and caring for young
deer population dynamics
What is happening to
this population?
20
number of deer
18
16
14
12
10
8
6
4
2
0
0
Why doesn’t the
population ever go
above 18?
2
4
6
8
Year
10
12
14
deer population dynamics
20
number of deer
18
16
Why does population
increase?
14
12
10
8
6
4
2
0
0
2
4
6
8
Year
10
12
14
CROWDING
 As
populations increase in size in environments
that cannot support increased numbers,
individual animals can exhibit a variety of stress
symptoms.
• These include aggression, decrease in
parental care, decreased fertility, and
decreased resistance to disease.
• They become limiting factors for growth and
keep populations below carrying capacity.
Carrying Capacity
The number of organisms of one
species that an environment can support
indefinitely.
18 is the Carrying Capacity for our
population.
3.
Population growth rate

How fast a given population grows

Factors that influence this are:

Natality ( Birth rate)

Mortality (Death rate)

Emigration (the number of individuals moving Away
from a population)

Immigration (the number of individuals into a
population)
POPULATION LIMITING
FACTORS
POPULATION LIMITING FACTORS
 Population

growth models
Logistic Growth Model

Often called the S-shaped growth curve

Occurs when a population’s growth slows or stops following
exponential growth.

Growth stops at the population’s carrying capacity

Populations stop increasing when:
 Birth
rate is less than death rate
(Birth rate < Death rate)
 Emigration
exceeds Immigration
(Emigration > Immigration)
POPULATION GROWTH
• An increase in the number of
individuals in a population
Unlimited resources and reproduction
lead to population growth (G)
Growth = Births – Deaths
(G = B – D)

Cohort --- all the members of a population born at the same
time.

Survivorship---the probability of newborn individuals of a cohort
surviving to particular ages.

Illustrated by Survivorship Curves
MORTALITY PATTERNS
When births exceed deaths you see
population growth.
600
500
J-Shaped Curve
400
300
Series1
POPULATION GROWTH
200
100
0
0
2
4
6
8
10
12
• Exponential growth means that as a population
gets larger, it also grows at a faster rate.
600
500
J-Shaped Curve
400
300
Series1
200
EXPONENTIAL GROWTH
100
0
0
2
4
6
8
10
12
 Put
your pens down for a minute & think about
this:

An employer offers you two equal jobs for one hour
each day for fourteen days.

The first pays $10 an hour.

The second pays only 1 cent a day, but the rate doubles
each day.

Which job will you accept?
UNDERSTANDING EXPONENTIALS
Population Ecology: Population Growth Rate
Job 1
Job 2
90
80
Now, how much
would your employer
70
owe you if you
60
stayed at this job for
another 2 weeks?
50
Job 2 lags for a
long time before
40
What would happen if
exponential
this type of growth took
30
growth kicks in!
place within a
20
UNDERSTANDING
EXPONENTIALS population?
10
0
1
2
3
4
5
6
7
8
9
10 11 12 13 14

Scope of Ecology

Population Density and Distribution

Population Growth Models

Survivorship Curves

Age Distributions

Regulation of Population Size

Life History Patterns

Human Population Growth

Environmental Impact

Logistic growth—indicated by an S-shaped curve

Difference between logistic and exponential due to
environmental resistance
LOGISTIC GROWTH
LOGISTIC GROWTH
St. Paul Island
Reindeer
Population
Deaths begin to exceed births and the
population falls below carrying capacity
population growth over 20 years
600
S - Curve
population
500
400
300
200
100
0
0
2
4
6
8
10
year
12
14
16
18
20
POPULATION LIMITING FACTORS

Population growth models

Logistic Growth Model
The S-curve is not as pretty as the image looks
1.
Carrying capacity can be raised or lowered. How?
Example 1: Artificial fertilizers have raised k
Example 2: Decreased habitat can lower k
2.
Populations don’t reach k as smoothly as in the logistic graph.
•
Boom-and-Bust Cycles
•
Predator-Prey Cycles
SURVIVORSHIP CURVES
SURVIVORSHIP CURVES
THE HUMAN POPULATION

doubled three times in the last three centuries

about 6.1 billion and may reach 9.3 billion by the year 2050

improved health and technology have lowered death rates

The history of human population growth
Figure 35.8A

The age structure of a population is the proportion of individuals in
different age-groups
RAPID GROWTH
SLOW GROWTH
ZERO GROWTH/DECREASE
Kenya
United States
Italy
Male
Female
Male
Female
Ages 45+
Ages 45+
Ages 15–44
Ages 15–44
Under
15
Percent of population
Male
Female
Under
15
Percent of population
Percent of population
Also reveals social conditions, status of women
Figure 35.9B
 Rapid
life-history patterns are common among
organisms from changeable or unpredictable
environments.
REPRODUCTION PATTERNS:
20
MINUTES!
RAPID LIFE-HISTORY PATTERNS

Large species that live in more stable environments
usually have slow life-history patterns.
22
MONTHS!
REPRODUCTION PATTERNS:
SLOW LIFE-HISTORY PATTERNS
• Reproduce and mature
slowly, and are longlived.
• Maintain population
sizes at or near carrying
capacity.
GROWTH LIMITATIONS
When a population overshoots the
carrying capacity, then limiting
factors may come into effect.

Resources

Disease

Organism interaction

Habitat Size/Crowding

Weather
TWO TYPES OF LIMITING FACTORS:
Density-dependent
and
Density-independent
Population density describes the number of
individuals in a given area.
DENSITY-INDEPENDENT FACTORS
Density-Independent
Factors
Density-independent
limiting factors affect all
populations in similar ways,
regardless of the population
size.
Copyright Pearson Prentice Hall
Population Ecology: Density-independent factors
 Density-independent
 These
factors
are usually abiotic factors
 They
include natural phenomena, such as weather
events

Drought, flooding, extreme
heat or cold, tornadoes,
hurricanes, fires, etc.
POPULATION LIMITING FACTORS
 Density-independent
factors can affect all
populations, regardless of their density.
 Most
density-independent factors are abiotic
factors, such as temperature, storms, floods,
drought, and major habitat disruption
DENSITY - INDEPENDENT
DENSITY-INDEPENDENT FACTORS
Examples of density-independent limiting factors include:
unusual weather
natural disasters
seasonal cycles
•Example:
Deer foraging for food in deep
snow during the winter.
certain human activities—such as damming rivers and clearcutting forests
Copyright Pearson Prentice Hall
DENSITY-DEPENDENT FACTORS
 Density-dependent

competition

predation

parasitism

disease
Copyright Pearson Prentice Hall
limiting factors include:

Density-dependent factors include disease, competition,
predators, parasites, and food.

Disease, for example, can spread more quickly in a population
with members that live close together.
DENSITY - DEPENDENT
 Density-dependent
factors exist only when
the population density reaches a certain
level. These factors exist most strongly when
a population is large and dense.
 They
do not affect small, scattered
populations as greatly.
Copyright Pearson Prentice Hall
COMPETITION
•

Is Density - Dependent
When only a few individuals compete for resources, no
problem arises.
• When a population increases to the point at
which demand for resources exceeds the
supply, the population size decreases.
Positive and negative interactions
Predation
Interspecific
competition
Competition is
an interaction between individuals
of the same or of different species
membership, in which the fitness of
one is lowered by the presence of
the other.
Herbivory is a form of
parasitism
Symbiosis is any type of relationship where two individuals live together
Amensalism is a relationship
between individuals where
some individuals are inhibited
and others are unaffected.
Parasitism is
any relationship
between two
individuals in which
one member benefits
while the other is
harmed but not killed
or not allowed to
reproduce.
Parasitoidism is a relationship
between two individuals in
which one member benefits
while the other is not allowed
to reproduce or to develop
further
Commensalism
is a relationship
between two
individuals
where one
benefits and the
other is not
significantly
affected.
Mutualism is any relationship
between two individuals of
different species where both
Mutualism is the way two organisms of different species exist in a
relationship in which each individual benefits. Mutualism is the oposite to
interspecific competition.
Client– service relationships
Pollination
Mutualism is often linked to coevolutionary processes
Facilitation is a special form of
commensalism and describes a
temporal relationship between two or
more species where one species
benefits from the prior (and recent)
presence of others.
In plant succession early arriving plants
pave the way for later arrviing by
modifying soil condition.
Intraspecific competition
Canis lupus
Mytilus edulis
Scramble (exploitation,
diffuse) is a type of
competition in which
limited resources within
an habitat result in
decreased survival rates
for all competitors.
Contest (interference)
competition is a form of
competition where there is a
winner and a loser
Mate
competition
Territoriality
𝜎2 ≪ 𝜇
The variance in
distance is
much less than
the mean
distance
Territories imply a
more or less even
distribution of
individuals in space
Territoriality is a form of
avoidance of intraspecific
competition
Overlap
Territory
Home
range
Home ranges might
overlap
Home
range
Territory
 Competition
 When
populations become crowded,
organisms compete for food, water space,
sunlight, and other essential resources.
 Competition
among members of the same
species is a density-dependent limiting
factor.
Copyright Pearson Prentice Hall
 Competition
can also occur between members of
different species.
 This
type of competition can lead to evolutionary
change.
 Over
time, the species may evolve to occupy different
niches to avoid competition.
DENSITY-DEPENDENT FACTORS
Copyright Pearson Prentice Hall
Predation
 Populations
in nature are often
controlled by predation.
 The
regulation of a population by
predation takes place within a predatorprey relationship, one of the best-known
mechanisms of population control.
DENSITY-DEPENDENT FACTORS

Predators may capture prey by:
 Walking
 Swimming
 Flying
 Pursuit
and ambush
 Camouflage
 Chemical
warfare
MOST CONSUMER SPECIES FEED ON
LIVE ORGANISMS OF OTHER SPECIES
PREDATION
Populations of predators and their prey experience cycles
or changes in their numbers over periods of time.
Lynx and Hare pelts sold to the Hudson’s Bay
Company
Wolf and Moose Populations on Isle Royale
DENSITY-DEPENDENT FACTORS
Moose
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Wolves
Predation
Erigone
atra
Canada lynx and snowshoe
hare
Specialist predator
Generalist predator
Oligophages
Polyphages
Monophages
Prey quality
Stoppin
g point
Starvation
Maximu
m yield
Trade-offs in
foraging
Animals should adopt a strategy to
maximuze yield
Optimal
foraging
theoryforaging
Holling’s
optimal
theory
𝐹𝑜𝑜𝑑 𝑖𝑛𝑡𝑎𝑘𝑒 ∝
𝐷𝑒𝑛𝑠𝑖𝑡𝑦𝑓𝑜𝑜𝑑 𝑡𝑡𝑟𝑎𝑣𝑒𝑙
1 + 𝑎𝐷𝑒𝑛𝑠𝑖𝑡𝑦𝑓𝑜𝑜𝑑 𝑡ℎ𝑎𝑛𝑑𝑙𝑖𝑛𝑔
Searching time
Great tits forage at site of different
quality
How
long should a bird visit each site to
have optimal yield?
1
0
2
0
1
5
3
1
8
1
1
4
1
7
Parus
major
8
9
Predicted
energy intake
from travel and
handling time
Predicted
energy intake
from travel
time
Cowie 1977
Specialist predators and the respective prey often show cyclic
population variability
12 year
Cycles of the
cycle
predator follow
that of the prey
Canada lynx
and snowshoe
hare
Hudson’s Bay
Company
Data from MacLulick
1937, Univ. Toronto
Studies, Biol. Series 43
Data from
Yoshida et
al. 2003,
Nature 424
Bracyonus
calyciflorus
Chlorell
a
vulgaris
Cycles might be
triggered by the
internal dynamics
of the predator –
prey interactions or
by external clocks
that is
environmental
factors of regular
appeareance
Most important
are regular
climatic
variations like El
Nino, La Nina,
NAO.
The Lotka Volterra approach to specialist
predators
e: mortality rate of the predator
𝑑𝑃
𝑑𝑁
𝑑𝑃
= −𝑒𝑁
= 𝑟𝑁 − 𝑎𝑃𝑁
= 𝑓𝑎𝑁𝑃 − 𝑒𝑃 r: reproductive rate of the prey
𝑑𝑡
𝑑𝑡
𝑑𝑡
faN: reproductive rate of the predator
𝑑𝑁
𝑟
𝑑𝑃
𝑒
f: predator efficieny
=0→𝑃=
=0→𝑁=
𝑑𝑡
𝑎
𝑑𝑡
𝑓𝑎
aP: mortality rate of the prey
The equilibrium abundances of prey and a: attack rate
predator
In nature most predator prey
relationships are more or less
stable.
The Lotka Volterra models predicts
unstable delayed density dependent
cycling of populations
Any deviation from the
assumption of the Lotka
Volterra model tends to stabilize
population:
• Prey aggregration
• Density dependent
consumption
• Functional responses
Variability, chaos and predator prey
fluctuations
𝑑𝑁
𝑑𝑃
= 𝑟𝑁 − 𝑎𝑃𝑁
= 𝑓𝑎𝑁𝑃 − 𝑒𝑃
𝑑𝑡
𝑑𝑡
Lotka Volterra cycles with
fixed parameters a, e, f, r.
Lotka Volterra cycles with
randomly fluctuating
parameters tends
a, e, f,tor.
Stochasticity
stabilize populations
Dynamic equilibrium
Any factor that provides not too extreme variability into parameters of
the predator prey interaction tends to stabilize populations.
Fixed parameter values cause fast extinction.
Herbivory
Feeding Strategy
Diet
Example
Frugivores
Fruit
Ruffed lemurs
Folivores
Leaves
Koalas
Nectarivores
Nectar
Hummingbirds
Granivores
Seeds
Hawaiian
Honeycreepers
Palynivores
Pollen
Bees
Mucivores
Plant fluids, i.e.
sap
Aphids
Xylophages Plant defenses
Wood against herbivors
Termites
Many plants produce secondary metabolites, known as allelochemicals,
that influence the behavior, growth, or survival of herbivores. These chemical
defenses can act as repellents or toxins to herbivores, or reduce plant
digestibility.
Alcaloide (amino acid derivatives):
nicotine, caffeine, morphine, colchicine, ergolines, strych
nine, and quinine
Terpenoide, Flavonoids, Tannins
Mechanical defenses: thorns, trichomes…
Mimicry
Mutualism: Ant attendance, spider attendance
Digitalis
Negative feedback loops
occur when grazing is too
low
Reduced
structural
complexit
y
Low
coral
cover
Decreasing
coral
recruitment
Hay
and
Rasher
(2010)
Decreasin
g fish
recruitme
nt
Low
grazing
intensity
Increasing
algal cover
Functions of
herbivores in
coral reefs
Herbivorous fish
(Diadema)
Positive feedback loops
occur when grazing is high
Increased
structural
complexity
High
coral
cover
Overfishing of
Increasing
herbivorous fish
coral
might cause a shift
recruitment
to algal dominated
low divesity
Increasin
g fish
recruitme
nt
High
grazing
intensity
Decreasing
algal cover
 Parasitism
and Disease

Parasites can limit the growth of a population.

A parasite lives in or on another organism (the host) and
consequently harms it.
Copyright Pearson Prentice Hall
A limiting factor that depends on
population size is called a densitydependent limiting factor
.
Density-Dependent
Factors
Copyright Pearson Prentice Hall
Population of New Orleans, La 1970-2006
650000
population
550000
450000
350000
250000
150000
50000
-500001968
1973
1978
1983
1988
1993
1998
year
1. What are the independent
and
dependent variables?
2. What is the population trend?
3. Why did this happen? Is this densitydependent or independent?
2003
2008
Global population 1900 - 2046
Population in Billions
10
9
8
7
6
recorded population
5
projected population
4
3
2
1
0
1850
1900
1950
2000
2050
2100
Years
4. What type of growth is this?
5. When does growth increase? What might
have happened to cause this?
PREDATOR-PREY INTERACTIONS:
LECTURE CONTENT
 Predator-prey interactions often
dramatic, illustrated by
snowshoe hare-lynx population fluctuations
 Simple
Lotka-Volterra predator-prey model generates
fluctuations of prey, predator
 Graphical models
identify factors that stabilize,
destabilize predator-prey interaction
 Importance
of predation in nature attested to by various
lines of evidence

Diversity, ubiquity of anti-predator adaptations

Evidence that predators control prey, under particular conditions

Impact of interacting predators and prey in population cycles
PREDATOR-PREY INTERACTIONS ARE OFTEN
DRAMATIC-- “NATURE RED IN TOOTH AND
CLAW”--AS ILLUSTRATED BY THIS LION ABOUT
TO SNAG A HYENA
ONE OF THE MOST FAMOUS EXAMPLES OF
PREDATOR-PREY INTERACTIONS
ILLUSTRATED BY CANADA LYNX AND
SNOWSHOE HARE, IN CANADIAN TAIGA
(FOREST) BIOME
DRAMATIC FLUCTUATIONS OF HARE AND
LYNX POPULATIONS
Note regular periodicity, and lag by lynx
population peaks just after hare peaks
HARE-LYNX EXAMPLE
 Charles
Elton’s paper (1924), “Periodic
fluctuations In the numbers of animals: their
causes and effects”, British Journal of
Experimental Biology, was first (of MANY)
publications to analyze this data set
 Are
these cycles regular, i.e., with constant
periodicity?
 What
causes these cycles?
 Interaction
of predator and prey?
 Hare-resource
interaction? (hares feed on fir tree
needles, and other vegetation)
 Sunspot
 Humans
cycles?
(as hunters) interacting with both predator
and prey?
MODELING IS ONE WAY ECOLOGISTS
HAVE STUDIED PREDATOR-PREY
POPULATION DYNAMICS
 Lotka-Volterra
Predator-Prey model is the classic
model (see “Summary: Lotka-Volterra PredatorPrey Model”, lecture notes on web page)
 This
model generates highly regular oscillations of both
prey and predator population fluctuations, as seen in
hare-lynx data (see next slide)
 However,
this model results in “neutral stability”, a very
fragile kind of stability that does not explain the factors
that tend either to stabilize or destabilize population
dynamics of predator-prey interactions
 To
appreciate stabilizing, destabilizing influences on
predator-prey systems, we will use graphical analysis
PREDATOR-PREY POPULATION FLUCTUATIONS
(NEUTRAL STABILITY) IN LOTKA-VOLTERRA
MODEL
GRAPHICAL ANALYSES AND
STABILITY OF PREDATOR-PREY
SYSTEMS

Modifications of prey isocline (see lecture, text)




Humped prey isocline

Why is it often hump-shaped? (Recall slope of logistic model)

Allee effect at low prey densities

Stability depends on relative position of predator isocline
Prey refuge from predator
Modifications of predator isocline

Predator carrying capacity

Predator interference (e.g., territoriality)
Factors that destabilize predator-prey interactions

Time lags, predator efficiency

Monophagous predator (inability to switch prey)
WHAT EVIDENCE THAT PREDATORS ARE AN
IMPORTANT FACTOR IN NATURE?
 Diversity,
ubiquity of antipredator adaptations in many
kinds of prey
 Impact
of predators on prey
populations
 Reviews
 Role
of literature
of predators in oscillating
populations of prey and
predators
SOME ANTI-PREDATOR ADAPTATIONS
IN INSECTS (AND A FEW VERTEBRATES)

Warning = aposematic coloration
 Batesian mimicry--palatable mimic
 Mullerian mimicry--both
 Camouflage,
model and mimic unpalatable
crypsis--match background, unpalatable object
 Catalepsis--frozen posture
 Aggression,
of unpalatable model
with appendages retracted
counter-attack (bombadier beetle)
 Aggression--e.g., stinging, biting such
 Armor--spines,
as wasps & bees
thorns, anti-swallowing devices, large size, bluffing
 Masting--synchronous reproduction (e.g.,
 Escape
13- ,17-year cicadas)
behaviors--e.g., jumping Homoptera

Prey may avoid capture by
 Camouflage
 Chemical
 Warning
warfare
coloration
 Mimicry
 Deceptive
looks
 Deceptive
behavior
MOST CONSUMER SPECIES FEED ON
LIVE ORGANISMS OF OTHER SPECIES
PREY DEFENSES

Predation usually results in
the evolution of defensive
adaptations in prey.

These can include:


Chemical defenses (toxins,
poison, acrid sprays)

Behavior (living in groups,
scouts, alarm calls)

Morphological features
(spines, color, structures
that allow you to run fast or
detect predators), and
other traits
Photo Credit: Rhett A. Butler @ mongabay.com
Caterpillar with Venomous Spines

Caterpillar Video: http://www.youtube.com/watch?v=oWOC8trquFo
BEHAVIORAL DEFENSE EXAMPLE
APOSEMATIC
COLORATION IN
POISON-ARROW FROG,
MONTEVERDE, COSTA
RICA (PHOTO BY T.W.
SHERRY & T.K. WERNER)
BATESIAN MIMICRY OF
WASP (UNPALATABLE
MODEL, UPPER LEFT) BY
(1) MANTISPID
(NEUROPTERA, PALATABLE
MIMIC, UPPER RIGHT),
AND (2) MOTH
(PALATABLE MIMIC,
LOWER); (RICKLEFS 2001)
MULLERIAN MIMICRY IN TWO PAIRS OF
BUTTERFLIES (RICKLEFS 2001) (HELICONIINAE)
CRYPTIC COLORATION
IN COSTA RICAN MOTH
(CENTER OF PHOTO)
RESTING ON GROUND
DURING DAY (PHOTO BY
T.W. SHERRY)
CRYPTIC (LEAF-LIKE)
COLORATION IN
CHOERADODIS
RHOMBICOLIS
MANTID, COSTA
RICA
VENTRAL VIEW OF
CHOERADODIS
RHOMBICOLIS MANTID,
COSTA RICA:
PROTHORACIC FLAP
(SHIELD-LIKE STRUCTURE
JUST BEHIND HEAD)
CAUSES 10-FOLD
INCREASE IN HANDLING
TIME BY COSTA RICAN
NUNBIRDS (LARGEINSECT PREDATOR),
BASED ON EXPERIMENT
BY T. SHERRY (PHOTO BY T.
CATALEPSIS IN COSTA RICAN
KATYDIDS: SEE TWO INSECTS
ALONG LEAF VEINS
(ARROWS), WITH ONLY ONE
PAIR OF LEGS PROTRUDING
OUT OF ALLIGNMENT WITH
REST OF BODY (PHOTO BY
T.W. SHERRY)
BOMBADIER BEETLE (BRADINUS CREPITANS)
SPRAYING BOILING HOT ACID AT PREDATOR;
NOTE ALSO APOSEMATIC COLORATION (PHOTO
BY THOMAS EISNER, CORNELL UNIVERSITY)
ACTIVE DEFENSE--URTICATING (STINGING)
CATERPILLAR IN COSTA RICA (PHOTO BY T.W.
SHERRY & T.K. WERNER)
PINNED SPECIMENS OF JUMPING
HOMOPTERA FROM COSTA RICA
(SUPERFAMILY FULGOROIDEA)--NOTE
LARGE HIND-LEGS (PHOTO BY T.W. SHERRY)
SOME CONCLUSIONS FROM EXAMPLES
OF ANTI-PREDATOR ADAPTATIONS

Diversity, ubiquity of anti-predator adaptations attests to intense
selection pressure by predators

Some adaptations are subtle, poorly studied to date (e.g., large
body size as a refuge, anti-predator flaps)

Many prey have multiple adaptations, weapons

Tropics (and deep oceans) are arenas for intense predator-prey coevolution (long time periods of stable environments, specialized
adaptations in relatively constant environments, yearlong activity,
diverse predators, prey)

Anti-predator adaptations are one form of evidence for the impact
of predators in ecological systems
IMPACT OF PREDATION ON BULLFROG
TADPOLE BEHAVIOR AND GROWTH RATE
(FROM RICKLEFS 2001)
BIRDS AS
PREDATORS ON
CATERPILLARS IN
THE HUBBARD
BROOK
EXPERIMENTAL
FOREST, NH
(HOLMES,
SCHULTZ, AND
NOTHNAGLE,
1972); ASTERISKS
INDICATE
SIGNIFICANT
DIFFERENCES
OTHER EXAMPLES OF PREY
CONTROL BY PREDATOR

Dingo (wild dog) introduced into Australia has huge impact on
several herbivores there: kangaroos, emus, feral pigs

Populations of all these animals significantly reduced where dingos
live (prey eliminated in some areas)

Feral pigs have different population age-structure where dingos
present versus absent (see text)
Sea otters control abundance of sea urchins, sea
urchins of kelp beds (& orcas of sea otters!)

Review by Andrew Sih (1985): 95% of studies
showed some effect of predation; 85% large effect


Introduced predators have disproportionate effect
WHAT IS ROLE OF PREDATORS IN CAUSING
OSCILLATIONS OF PREDATOR, PREY?
 Look
at case study, of lynx-hare system
 Krebs
et al. (1996) study in arctic Canada

Winter food known to be important: Food quality declines when
heavily grazed at high hare density

Study attempted to get at both factors by reducing predators (using
exclosures) & supplementing food (rabbit chow) during a
population peak and subsequent decline

Next three slides present some of results of their study
ABUNDANCE OF HARE POPULATIONS IN
RESPONSE TO TREATMENTS AND CONTROLS,
DURING POPULATION PEAK, & SUBSEQUENT
DECLINE (KREBS ET AL.)
RATIO OF DENSITY OF HARES
IN TREATMENT VERSUS
CONTROLS FOR SEPARATE
AND COMBINED TREATMENT
EFFECTS; NOTE BY FAR THE
GREATEST EFFECT OF
COMBINED TREATMENTS (C)
SURVIVAL RATES OF HARES ALSO SHOW
MUCH GREATER IMPACT OF COMBINED
TREATMENTS
CONCLUSIONS FROM KREBS ET AL.
EXPERIMENT ON LYNX-HARE POPULATION
OSCILLATIONS:

It was possible to prolong peak of population abundance of
hares, but difficult!

Both food additions and predator reductions affected hare
populations separately

Effect of both food and predators had greatest overall effect,
indicating an interaction of food and predators on prolonging
hare population at high level
SOME HUMAN APPLICATIONS OF
PREDATOR-PREY MODELS


Humans as super-efficient predator that destabilizes predator-prey
interactions (e.g., fisheries)

Humped catch-yield versus fishing effort curve in some fisheries

How does increased predator efficiency destabilize?

Interaction with natural environmental instability (e.g., El Niño-La Niña
climate fluctuations)
Introductions of predators often tend to destabilize predator-prey
systems….why?
CONCLUSIONS:
 Predator-prey
conspicuous
ecological interactions often dramatic,
 Models
help identify factors that stabilize and destabilize
predator-prey interactions

Classic Lotka-Volterra model leads to oscillations, but neutral
stability

Stabilizing factors--prey self-limitation, prey refuge, spatial
heterogeneity, predator territoriality

De-stabilizing factors--predator more efficient, time-lags
 Importance
of predators in nature supported by
experiments on predator-impacts, anti-predator
adaptations, impact of predators on population
oscillations, activities of humans
HERBIVORE-PLANT INTERACTIONS
 An
herbivore
grazing on a
plant is another
example of
predation.
 Usually,
only
part of the prey
is eaten by the
predator.

Photo Credit: Rhett A. Butler @
mongabay.com