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Wesley A. C. Godoy
University of São Paulo
"Luiz de Queiroz" College of Agriculture
Piracicaba, São Paulo, Brazil - [email protected]
Application of ecological models in entomology:
a view from Brazil
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Working with ecological models in different places and areas
Universidade Estadual Paulista
Medical and forensic entomology Agricultural and forest entomology
University of São Paulo - ESALQ
“Luiz de Queiroz” College of Agriculture
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Overview
Part I: blowflies as a study model to investigate intra and interspecific
interactions
• Population dynamics: a scenario involving exotic and native blowfly
species
• Population dynamics applied to forensic entomology
• Intraguild predation
• Tri-trophic interactions
Part II: combining population theory with biological control and
integrated pest management (IPM)
• Ecological basis for modelling pests and natural enemies
• Concept of economic injury level
• A preliminary model combining host-parasitoid theory and IPM
• Inserting spatial dimension into the system
• Experiments focused on potential natural enemies for mass production
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Population dynamics: a scenario involving exotic and native blowfly species
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Importance of blowflies
Myiasis
Vector of diseases
Larval therapy
Forensic entomology
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and finally, as an experimental model
to study population dynamics in laboratory
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Life cycle of blowflies
Carrion
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Modelling biology and ecology of flies
tttt NNSNFN )()(2
11
Fecundity Survival
Prout & McChesney, 1985
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Density dependence
tttt NNSNFN )()(2
11
tNfeF
* tNseS
*
F*
f
N(t)
S*
s
N(t)
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Different values for fecundity and survival produce different dynamics
0 10 20 30 40 50 600
200
400
600
800
1000
1200
1400
1600
1800
2000
Generations
Popula
tion s
ize
Exotic blowfly species
0 50 100 150 200 250 300100
200
300
400
500
600
700
800
900
Generations
Popula
tion s
ize
Native blowfly species
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Part I: blowflies as a study model to investigate intra and interspecific
interactions
• Population dynamics: a scenario involving exotic and native blowfly species
• Population dynamics applied to forensic entomology
• Intraguild predation
• Tri-trophic interactions
Part II: combining population theory with biological control and
integrated pest management (IPM)
• Ecological basis for modelling pests and natural enemies
• Concept of economic injury level
• A preliminary model combining host-parasitoid theory and IPM
• Inserting spatial dimension into the system
• Experiments focused on potential natural enemies for mass production
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Forensic applications
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How can ecological models provide useful information for forensic sciences?
Showing what factors govern diversity and abundance
of insects
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Three important ecological factors:
Diversity and abundance of blowflies
Interspecific and trophic interactions
Psychoactive drugs or medicines
and population dynamics of blowflies
Diversity and abundance influence strength
of interactions
demographic parameters depend on resources
available and influence dynamic
behaviours
Influence of drugs on demographic parameters
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Comparing demographic parameters influenced by drugs with the Prout & McChesney model
1. Amphetamine (stimulant drug)
2. Phenobarbital (anticonvulsant, sedative and hypnotic)
3. Methanol (organic solvent)
4. Oxycodone (analgesic)
tNfeF
*
tNseS
*tttt NNSNFN )()(
2
11
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Table 1. Exponential regression analysis of fecundity and survival for the control,
phenobarbital, methanol and amphetamine treatments
Control Phenobarbital Methanol Amphetamine
F S F S F S F S
Y intercepts 26.74 0.81 22.87 0.90 27.12 0.54 27.45 0.60
RC 0.0009 0.00163 0.0006 0.002 0.0009 0.001 0.0009 0.001
r2
0.66 0.80 0.54 0.90 0.65 0.90 0.61 0.89
ANOVA 445 40.60 264 94.64 414 80.59 345 81.53
P < 0.001; F = fecundity; S = survival; RC= Regression coefficient
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Fecundity
Survival
Control
Phenobarbital
Fecundity and survival influenced or not by drugs in C. albiceps
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Methanol
Fecundity Survival
Amphetamine
Fecundity and survival influenced or not by drugs in C. albiceps
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Table 2. Exponential regression analysis of fecundity and survival in oxycodone,
phenobarbital, methanol and amphetamine treatments with the addition of C.
megacephala prey
Oxycodone Methanol Amphetamine
F S F S F S
Y intercepts 29.15 0.87 23.34 0.57 28.14 0.77
RC 0.0008 0.002 0.0006 0.001 0.0009 0.001
r2
0.54 0.83 0.50 0.86 0.59 0.89
ANOVA 228 48.98 216 63.31 272 70.97
P < 0.001; F = fecundity; S = survival; RC= Regression coefficient
Table 1. Exponential regression analysis of fecundity and survival for the control,
phenobarbital, methanol and amphetamine treatments
Control Phenobarbital Methanol Amphetamine
F S F S F S F S
Y intercepts 26.74 0.81 22.87 0.90 27.12 0.54 27.45 0.60
RC 0.0009 0.00163 0.0006 0.002 0.0009 0.001 0.0009 0.001
r2
0.66 0.80 0.54 0.90 0.65 0.90 0.61 0.89
ANOVA 445 40.60 264 94.64 414 80.59 345 81.53
P < 0.001; F = fecundity; S = survival; RC= Regression coefficient
Without prey
With prey
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Fecundity and survival influenced or not by prey consumption
Fecundity Survival
Without prey
With prey
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Table 3. Percentage of predation of C. albiceps on C. megacephala without choice of
prey
Predation rate on C. megacephala
Time Control Phenobarbital Oxycodone Amphetamine Methanol
30 27.5 52.5 12.5 12.5 47.15
60 17.5 8 20 7.5 12.5
90 7.5 8 32.5 12.5 5
120 7.5 2.5 7.5 17.5 15
150 2.5 7.5 12.5 2.5 5
180 5 2.5 5 17.5 0
Total 67.5 81 90 70 85
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Part I: blowflies as a study model to investigate intra and interspecific
interactions
• Population dynamics: a scenario involving exotic and native blowfly species
• Population dynamics applied to forensic entomology
• Intraguild predation
• Tri-trophic interactions
Part II: combining population theory with biological control and
integrated pest management (IPM)
• Ecological basis for modelling pests and natural enemies
• Concept of economic injury level
• A preliminary model combining host-parasitoid theory and IPM
• Inserting spatial dimension into the system
• Experiments focused on potential natural enemies for mass production
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Intraguild predation
Predator
Prey
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Intraguild predation equations
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Satiation intensity
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Attack intensity
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Part I: blowflies as a study model to investigate intra and interspecific
interactions
• Population dynamics: a scenario involving exotic and native blowfly species
• Population dynamics applied to forensic entomology
• Intraguild predation
• Tri-trophic interactions
Part II: combining population theory with biological control and
integrated pest management (IPM)
• Ecological basis for modelling pests and natural enemies
• Concept of economic injury level
• A preliminary model combining host-parasitoid theory and IPM
• Inserting spatial dimension into the system
• Experiments focused on potential natural enemies for mass production
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Tri trophic interactions investigated
IGP: Intraguild predation
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Interactions investigated with experiments
IG-prey survival in absence of IG predator
IG-prey survival in presence of IG predator
IG-predator survival in absence of IG prey
IG-predator survival in presence of IG prey
IG - Intraguild
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IG prey alone
IG predator alone IG predator and prey
IG prey and parasitoid
IG predator and parasitoid
IG predator, prey and parasitoid
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Nomenclature for the ecological model
ne = time from oviposition to hatching = 1 day nl1 = development time for 1st and 2nd larval instars nl2 = development time for o 3rd Instar nl = nl1 + nl2 = 4 days np = pupal time = 4 days na = adult time = 7 days
Species: Chrysomya megacephala (PREY): 1 Chrysomya albiceps (PREDATOR): 2 Nasonia vitripennis (PARASITOID): W
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Functions for the model
IGP (), cannibalism () and parasitism ()
f1 and f2 with values between 1 and 0.5
IGP by L2n on L1
n
Cannibalism on L2n,
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Parasitism
Number of pupae parasitized
= Maximum number of pupae parasitized for 1 day
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Model description
E, L,P ou A
Age of fly
Species
Egg
Larva
Pupa
Adult
1st day Beginning of simulation Following day 3rd Instar: beginning of interactons between flies
Natural mortality
IGP and cannibalism
Pupae
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Natural mortality
Parasitism
Interactions with parasitoids Surviving pupae reaches adult phase
Natural mortality
Oviposition by flies
New life cycle
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Natural mortality
Days since the beginning of the experiment
k = cycle length h = sex ratio (eggs) q = eggs per day
Parasitoid equation
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Gray bars = larvae and pupae of blowflies, White bars = dead individuals, Black lines = parasitoids
Density of blowfly species long to generation
Prey + 1 parasitoid Prey + 10 parasitoids
Predator + 1 parasitoid Predator + 10 parasitoids
Initial population Size = 300
Initial population Size = 100
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Only IG prey and predator Prey: bars Predator: black line
high IGP and low cannibalism high IGP and high cannibalism
low IGP and low cannibalism low IGP and high cannibalism
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IG prey, predator and parasitoids
parasitoid
parasitoid
Pre
y P
red
ato
r
high IGP and low cannibalism high IGP and high cannibalism
low IGP and low cannibalism low IGP and high cannibalism
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Part I: blowflies as a study model to investigate intra and interspecific
interactions
• Population dynamics: a scenario involving exotic and native blowfly species
• Population dynamics applied to forensic entomology
• Intraguild predation
• Tri-trophic interactions
Part II: combining population theory with biological control and
integrated pest management (IPM)
• Ecological basis for modelling pests and natural enemies
• Concept of economic injury level
• A preliminary model combining host-parasitoid theory and IPM
• Inserting spatial dimension into the system
• Experiments focused on potential natural enemies for mass production
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Starting from a host parasitoid model with functional response type II
0
200
400
600
800
1000
1200
1 11 21 31 41
density-independent survival of parasitoid propagules at generation t
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If N(t+1) < threshold (L)
If N(t+1) threshold (L)
q1 = reduction of host population by other methods q2 = parasitoid release rate = number of released parasitoids L = economic threshold
Tang & Cheke, 2008
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Introducing integrated pest management (IPM) strategies into the model
0
200
400
600
800
1000
1200
1 11 21 31 41
+
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Population dynamics without IPM strategies
0
5
10
15
20
25
30
1 11 21 31 41 51 61 71 81 91
H
P
N,P
0
5
10
15
20
25
1 6 11 16 21 26 31 36
H
P
Tempo
N,P
Population dynamics taking into account IPM strategies
L = 15
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Now including migration by using coupled lattice model
Diffusion type II Host Density dependent
Diffusion type I Host Density independent
H < Economic threshold: white; H Economy threshold: gray; H Injury level: black
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with IPM
with IPM and migration
without IPM and migration
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Part I: blowflies as a study model to investigate intra and interspecific
interactions
• Population dynamics: a scenario involving exotic and native blowfly species
• Population dynamics applied to forensic entomology
• Intraguild predation
• Tri-trophic interactions
Part II: combining population theory with biological control and
integrated pest management (IPM)
• Ecological basis for modelling pests and natural enemies
• Concept of economic injury level
• A preliminary model combining host-parasitoid theory and IPM
• Inserting spatial dimension into the system
• Experiments focused on potential natural enemies for mass
production
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Relationships between pest and potential predators
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Experiments to compare the best diet for natural enemies
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Experiments focused on potential natural enemies
for mass production
M =
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Population dynamics of Podisus nigrispinus structured in life stages maintained in artificial diet
N
Life cycle stages
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Population dynamics of P. nigrispinus structured in life stages maintained in Drosophila melanogaster
Life cycle stages
N
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Population dynamics of P. nigrispinus structured in life stages maintained in Chrysomya putoria
Life cycle stages
N
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Current projects by graduate students
• Fennel and cotton with colored fibers intercropping,
pest and natural enemies (Master thesis)
• Trophic interactions between Spodoptera frugiperda (corn caterpillar) and natural
enemies (Master thesis)
• Trophic interactions between soybean bug and their parasitoids (phD thesis)
• Intraguild predation in Diaphorina citri and their natural enemies:
citrus and sorghum intercropping (phD thesis)
• Population dynamics of forest pest and natural enemies (phD thesis)
• Trophic interactions between predator stink bugs and crop pests (phD thesis)
• Functional response and predator prey dynamics in coccinelids and aphids (posdoc)
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Thank you