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Foraging Causes and Consequences of Consumer Behavior

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Title: Foraging Causes and Consequences of Consumer Behavior


1
ForagingCauses and Consequences of Consumer
Behavior
  • Peter B. McEvoy
  • Insect Ecology
  • Ent 420/520

2
Consumer Behavior
  1. Physiological ecology how organisms respond to
    food (e.g. visual, chemical cues)
  2. Behavioral ecology how natural selection has
    favored particular patterns of consumer behavior
    in particular environments (e.g. optimal
    foraging)
  3. Populations dynamics how behavior of predator
    and prey influence their population dynamics

3
Consumer Searching Behavior Contrasting Views
and Approaches
  • Contrast nonrandom laboratory view and random
    field view (Morris and Kareiva 1991)
  • Contrast phenomenological and mechanistic
    approaches (Turchin 1998)

4
Physiological Ecology of Host-plant Selection A
Catenary Process
  • Behavioral elements follow each other in fixed
    order or reaction chain
  • random movement
  • searching guided by olfactory and/or optical cues
  • contact/evaluation using visual, olfactory,
    mechanosensory, gustatory information
  • acceptance/rejection
  • What cues give reliable information at each step?

5
Generalized Sequence of Events in Host-plant
Selection
Schoonhoven et al 1998
6
Behavioral Ecology of Consumer-Resource Relations
  • Consumer Diets (specialization)
  • Individual Behavior (functional, numerical,
    aggregative responses)
  • From Individual Behavior to Population Dynamics
    (aggregation of risk in relation to resource
    density)
  • Optimal Foraging Approach (critique of the
    adaptationist program)

7
Responses of consumer to changes in resource
density
  • Behavioral response within generation
  • Functional response is a change in per capita
    consumption rate of consumer brought about by
    change in resource density
  • Congregative response is movement of consumer
    leading to concentration of consumers in areas of
    high resource density
  • Reproductive response between generations
  • Numerical response is a change in per capita
    reproductive rate of consumer in response to
    change in abundance of resource

8
Representing consumer responses in models
9
Food Preferences of Consumers
  • Food preferences. Necessary to examine both food
    in diet and availability of different food
    types in the environment. Availability must be
    seen not through the eyes of the observer but
    through the eyes of the insect itself.
  • Ranked and balanced preferences. Ranked
    preferences predominate when food items can be
    classified on a single scale (many carnivores).
  • Mixed diets. Many consumers exhibit a
    combination of ranked and balanced preferences
    (many herbivores). Performance is far better on a
    mixed diet than on a pure diet of even the best
    food.
  • Switching. In contrast to a fixed preference,
    switching involves a preference for the more
    frequent food types.

10
Concept Alert!
  • Consumer preference vs performance. Resource use
    reflects both consumer choice (preference) and
    consumer ability to convert resource into useful
    outputs like growth and reproduction (performance)

11
Host Specializationin Swallowtail butterfly
Papilio machaon
12
Host SpecializationPreference and Performance in
Papilio machaon
Larval performance Most plants are suitable food
plants, but females lay eggs on only a fraction
Hierarchy of oviposition preferences Females lay
eggs on plants that do not support growth
13
Oviposition by Papilio machaon occurs on plants
unsuitable for larvae
  • Two invasive plant species, Bifora radians and
    Levisticum officinale, both Apiaceae
    (Umbelliferae), were introduced into Scandinavia
    and are rare oviposition behavior has not yet
    evolved to avoid these species

Bifora radians
Levisticum officinale
14
Host range in taxonomically conservative
  • Plants in subfamily Apiodeae suitable for larvae,
    those in Hydrocotyloideae and Saniculoideae
    resulted in 100 mortality

Saniculoideae (Sanicula, Eryngium),
Hydrocotyloideae (Hydrocotyle).
http//biodiversity.uno.edu/delta/angio/www/umbell
if.htm
15
Host range in Lab gtgtHost Range in Field
Papilio machaon
Angelica archangelica ssp. littoralis
  • Total of 33 spp. Apiaceae used in lab, only 1 sp
    (Angelica archangelica ssp. littoralis) used in
    field

16
Summary Papilio machaon study
  1. Invasive plant species. Oviposition on hosts
    unsuitable for larvae. Bifora radians and
    Levisticum officinale, both Apiaceae
    (Umbelliferae), were introduced into Scandinavia
    and are rare oviposition behavior not yet
    evolved to avoid these species
  2. Host Range Taxonomically Conservative Plants in
    Apiodeae suitable for larvae, those in
    Hydrocotyloideae and Saniculoideae resulted in
    100 mortality
  3. Host range in Lab gtgtHost Range in Field. Total
    of 33 spp. Apiaceae used in lab, only 1 sp
    (Angelica archangelica ssp. littoralis) used in
    field
  4. Unsettled points. Preference and performance in
    larvae, abiotic and biotic factors in wild may be
    absent from the lab, host a habitat as well as
    food

17
Pattern of Movement Behavior
  • Key behavioral characteristics
  • Frequency, the proportion of time spent moving
  • Rate, the rate of movement when actually in
    motion
  • Orientation, the direction of movement
  • Three forms of movement
  • Nonrandom settlement, to move or not to move,
    that is the question rate and orientation while
    moving are random
  • Area restricted search refers to change in
    consumer searching behavior (increase in turning
    frequency and/or decrease in velocity) following
    feeding
  • Orientation, consumer uses cues regarding
    neighboring plants (odors or visual cues) to
    alter direction of movement

18
Insect Movement in Heterogeneous Space (Turchin
and Omland 1999)
  • Distribution of food (directed movement or taxis,
    undirected movement or kinesis)
  • Tracking abiotic factors
  • Distribution of conspecifics (DD congregation,
    dispersal, mate finding)
  • Avoiding predation
  • Dealing with multiple factors

19
How Herbivores Use Odors to Orient Toward Host
Plants Experimental Setup
20
Orientation to Upwind Odor (External Stimuli)
Mediated by Satiation (Internal State)
Male
Female
Orientation when Starved
Random when Satiated
Ragwort flea beetle Longitarsus jacobaeae
21
Taxis Directed Movement in Response to
OdorColorado Potato Beetle
(B) Pure tomato
(A) Clean air
(D) Mix tomato potato Associational resistance
(C) Pure potato
Note wind direction, mean vector length and
upwind component
22
Analysis of Movement Pathsstep length/time
(velocity), turning rate, turning angle
23
House Flies Tend to Remain Where Resources Are
Concentrated
Large turning angle, small step length
immediately after feeding, then return to ground
state
24
Bumblebees Use Area Restricted Search
Low nectar, longer moves, lower turning angle
Bumblebees use Area Restricted Search
High nectar, shorter moves, higher turning angle
25
Patch Residence Time in Colias Regulated by
Changing Step Length
Median percent cover
Median step length
Median step length
26
Aphis varians Congregate by Increasing
Probability of Settling With Increasing Aphid
Density
27
Functional Responses Consumption Rate X Food
Density
  • Type 2 functional responses and handling time
  • Parasitoid Pleolophus basizonus attacking cocoons
    of the European pine sawfly Neodiprion sertifer
  • Type 2 response can be defined by handling time
    and searching efficiency. Hollings disc
    equation
  • Alternative reasons for a type 2 functional
    response
  • Type 1 functional response
  • Type 3 functional response will arise whenever an
    increase in food density leads to an increase in
    the consumers searching efficiency or decrease
    its handling time

28
Consequences of Functional Responses for the
Dynamics of Populations
Does functional response translate into direct
density dependence in mortality rate?
Prey killed per predator
Mortality Rate
Prey density
Prey density
29
Effects of Consumer Density Mutual Interference
Leads to Reduction in Consumption Rate
  • Coefficient of interference plotting log10
    searching efficiency as a function of consumer
    density. Slope takes the value of m and m is
    known as the coefficient of interference
  • The reverse of interference is facilitation
  • Mutual interference tends to stabilize
    predator-prey dynamics

30
Consumers, Food Patches, and Aggregative Responses
  • Eye of the beholder. Patch must be defined with a
    particular consumer in mind
  • Definition. Patch is area within which
    homogeneity can be assumed
  • Food value. Patches can vary in the density of
    food or prey they contain
  • Predation risk. Risk of predation often varies
    among patches differing in density

31
Aggregation of Risk Traditional View
  • Some simple expectations
  • Allocation of time. Consumers generally spend
    more time in patches containing high densities
    (because these are the most profitable patches)
  • Distribution of consumers. Most consumers are
    therefore found in such patches
  • Risk of being consumed. Prey in those patches
    are therefore more vulnerable to predation
    whereas those in low density-patches are
    relatively protected and more likely to survive
  • Often contradicted by observations responses may
    be directly or inversely density dependent,
    domed, or density independent
  • For herbivores (Cromartie 1975 Kareiva 1983)
  • For parasitoids (Lessells 1985, Stiling 1987,
    Walde Murdoch 1988, Pacala Hassell 1991)

32
Aggregation of Risk Modern View
  • Causes of clumping. Herbivores often aggregate
    without this being an aggregative response
  • Aggregation of risk. Heterogeneity in the risk of
    being consumed may reflect individual variation
    in resistance, timing, or spatial location

33
How Flea Beetles Forage Among Patches Differing
in Plant Density
  • Organisms. Flea beetle Longitarsus jacobaeae
    foraging among patches of its host plant ragwort
    Senecio jacobaea
  • Methods. Employed mass mark-recapture methods
    because it is difficult to follow individuals
  • Processes. Study includes colonization, birth,
    death, and interaction components
  • Time scale assumptions. Assume colonization and
    redistribution process occurs on faster time
    scale than birth, death, and population
    interactions. Organisms move, then interact.
  • Aggregation mechanisms. Diffusive, kinetic, and
    taxis mechanisms allow individual foragers to
    regulate their residence time in resource patches
    according to the quality of the patch

34
Ragwort Biocontrol
35
Life Cycle of Ragwort Flea Beetle
36
Driving Forces
  • Disturbance removes organisms, recycles
    limiting resources, sets the stage for
    colonization and occupancy
  • Colonization movement to the resource mediated
    by random and nonrandom elements
  • Local Interactions plant (insect) competition
    and insect herbivory

37
Equilibrium Density of Foragers
Evaluated at equilibrium, proportional increase
in hosts causes lt proportional increase in
beetles (slope lt 1)
Beetle population reached equilibrium day 7
38
Colonizing Abilities of 3 Insects Introduced for
Ragwort ControlProportion of patches occupied x
distance from source
Flea Beetle lt
Cinnabar moth lt
Seed-head fly
Proportion
Distance from Source
D50 Distance with probability of 50
infestation rate at origin
39
Year to Year Variation in ColonizationProportion
of Plants Occupied X Distance From Source
D50 148 m
D50 119 m
Proportion declines with distance in one year
Proportion independent of distance the next year
D50 Distance with probability of 50
infestation rate at origin
40
Factors Influencing ColonizationRagwort Flea
Beetle
  • Temperature Cold snap (lt 5oC)
  • Season Rise and fall of beetle numbers during
    colonizing phase
  • Hosts per patch Amplitude of colonization curve
    increases with the number of hosts per patch
    (host area)
  • Distance from source Amplitude of colonization
    curve grows weaker with distance from source

41
Flea Beetles Emerging the Following Year
  • Amplitude of beetle emergence curve increases
    with number of hosts per patch
  • Cumulative number of beetles emerging increases
    with number of hosts per patch

42
Growth Rate of Beetle Population
Allee Effect Decrease in growth rate at low
density
N(t1) / N(t)
Male-bias sex ratio in 1-plant patch, female
bias in larger patches
Males/Females
43
Growth Rate of Plant PopulationHerbivore Effect
Independent of Plant Density
Beetles excluded
Beetles present
44
Summary of Flea Beetle Study
  • Evidence of consumer/resource equilibrium
    encourages focus on equilibrium rather than
    transient states
  • Causes of aggregation highlight mix of random and
    nonrandom behavior (diffusion, kinesis, taxis)
  • Consequences of aggregation for growth rates of
    consumer and plant populations, dynamics of
    interaction. No refuge from parasitism due to
    heterogeneity of risk.

45
Quantitative Analysis of Foraging Movement
(Morris and Kareiva 1991, Turchin 1998, Turchin
and Omland 1999)
  • Represent random and nonrandom components of
    searching behavior in a mathematical model
    (diffusion, kinesis, taxis)

46
They Find Empirical Studies Are Not Measuring
the Right Things
  • Current state of our knowledge. Empirical studies
    provide quantitative measurements of all three
    components of movement (diffusion, kinesis,
    taxis) in only 2 of 45 species (i.e. mite
    Tetranychus urticae and butterfly Pieris rapae)
  • Consequences of our ignorance Failure to
    understand how insects locate superior food
    plants hampers investigation of
  • Host race formation and evolution of diets
  • Plant-herbivore coevolution
  • Implications of different cropping patterns
  • Safety and effectiveness of biocontrol organisms
  • Consequences of changing food quality of
    herbivore populations for population dynamics

47
Key Questions for Empirical StudiesMorris and
Kareiva
  • Should I distinguish mobile and sedentary
    subpopulations? Should the foraging population be
    divided into mobile and sedentary subpopulations,
    and can it be treated as one pool of mobile
    individuals?
  • How do I assess sensitivity to variation in host
    quality? Does the herbivore alter its rate of
    movement in accord with spatial variation in the
    quality of its potential host plants?
  • How do I screen for orientation? Do individuals
    orient and move in a directed manner toward
    plants whose quality stands above the quality of
    surrounding vegetation?

48
Discussion
  1. What processes besides movement can lead to
    aggregation of consumers?
  2. How might proponents of foraging theory respond
    to criticisms leveled by Lewontin and Gould?
  3. Why are phenomenological models so difficult to
    relate to actual movement behavior?
  4. Now that we have have mechanistically-grounded
    models, is there any need to employ
    phenomenological models lacking such a basis?

49
Refuge Theory Now the Outcome of Biocontrol
(Y) Can Be Predicted From a Single, Easily
Measured Parameter (X) (Hold the hype)
Hawkins et al 1994
50
Study System
Tachinid parasitoid, Tachinomyia similis of
western tussock moth (Orgyia vetusta Bdv.
Lymantriidae)
Bush lupine (Lupinus arboreus)
51
Mechanisms leading to inverse-density dependence
in parasitism
  • Leaving patches at a constant rate to avoid
    self-superparasitism
  • Decelerating functional responses caused by
    behaviors such as handling time or group defenses
  • Interference among parasitoids

52
Alternative Models of Parasitism
  1. No effect of host density on parasitism.
  2. Weekly variability in parasitoid aggregation, no
    decelerating functional response.
  3. Decelerating (type 2) functional response
  4. Decelerating functional response and weekly
    variability in parasitoid aggregation

53
Maximum Likelihood Method
  • Used to fit a regression line to bivariate or
    multivariate data rather than the least-squares
    method
  • Will result in values for the parameters that
    make the observed values in our data set seem
    most probable
  • Solution is carried out iteratively on computer

54
Akaike information criterion
  • Criterion for selecting among models
  • Best model is one with lowest AIC
  • Compromise between minimizing the number of
    parameters and minimizing the residual variance
  • The AIC is a number associated with each model
  • AICln (sm2) 2m/T
  • where m is the number of parameters in the model,
    and sm2 is (in an AR(m) example) the estimated
    residual variance sm2 (sum of squared
    residuals for model m)/T, and T the number of
    observations.

http//economics.about.com/cs/economicsglossary/g/
akaikes.htm
55
Fig. 1.  Foraging Tachinomyia similis (fly)
population response to variation in Orgyia
vetusta (host) density.
56
Fig. 2.  Attack rates by T. similis in relation
to experimentally manipulated density of O.
vetusta and T. similis.
  • Host treatment effect (plt0.001)
  • No Fly treatment effect (P0.73)

57
Fig. 3.  Observed parasitism rates by T. similis
(fly) throughout the season in relation to
densities of larval O. vetusta (host).
  • Model 2 (dashed) includes an effect of parasitoid
    aggregation
  • Model 4 (solid) includes effect of both
    parasitoid aggregation and saturating functional
    response
  • ß the increase in fly density expected with
    increases in host density
  • s the strength of saturation in the functional
    response

58
General Application
  • maximizing Eq. 5 where the expected percent
    parasitism, pj, is described by the general form
    1expF(H,P)A(H,P)t where F(H,P) is the
    functional response of the predator in units of
    (parasitoid density time)-1 and A(H,P) is the
    aggregative response of the predator in units of
    parasitoid density and t is the length of the
    experiment.
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