Application of ecological models in entomology: a view ... · Application of ecological models in entomology: a view from Brazil . Working with ecological models ... • A preliminary

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

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

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

Population dynamics: a scenario involving exotic and native blowfly species

Importance of blowflies

Myiasis

Vector of diseases

Larval therapy

Forensic entomology

and finally, as an experimental model

to study population dynamics in laboratory

Life cycle of blowflies

Carrion

Modelling biology and ecology of flies

tttt NNSNFN )()(2

11

Fecundity Survival

Prout & McChesney, 1985

Density dependence

tttt NNSNFN )()(2

11

tNfeF

* tNseS

*

F*

f

N(t)

S*

s

N(t)

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


interactions

• Population dynamics: a scenario involving exotic and native blowfly species











Forensic applications

How can ecological models provide useful information for forensic sciences?

Showing what factors govern diversity and abundance

of insects

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

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

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

Fecundity

Survival

Control

Phenobarbital

Fecundity and survival influenced or not by drugs in C. albiceps

Methanol

Fecundity Survival

Amphetamine

Fecundity and survival influenced or not by drugs in C. albiceps

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


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


Without prey

With prey

Fecundity and survival influenced or not by prey consumption

Fecundity Survival

Without prey

With prey

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


interactions












Intraguild predation

Predator

Prey

Intraguild predation equations

Satiation intensity

Attack intensity


interactions












Tri trophic interactions investigated

IGP: Intraguild predation

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

IG prey alone

IG predator alone IG predator and prey

IG prey and parasitoid

IG predator and parasitoid

IG predator, prey and parasitoid

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

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,

Parasitism

Number of pupae parasitized

= Maximum number of pupae parasitized for 1 day

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

Natural mortality

Parasitism

Interactions with parasitoids Surviving pupae reaches adult phase

Natural mortality

Oviposition by flies

New life cycle

Natural mortality

Days since the beginning of the experiment

k = cycle length h = sex ratio (eggs) q = eggs per day

Parasitoid equation

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

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

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


interactions












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

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

Introducing integrated pest management (IPM) strategies into the model

0

200

400

600

800

1000

1200

1 11 21 31 41

+

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

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

with IPM

with IPM and migration

without IPM and migration


interactions











• Experiments focused on potential natural enemies for mass

production

Relationships between pest and potential predators

Experiments to compare the best diet for natural enemies

Experiments focused on potential natural enemies

for mass production

M =

Population dynamics of Podisus nigrispinus structured in life stages maintained in artificial diet

N

Life cycle stages

Population dynamics of P. nigrispinus structured in life stages maintained in Drosophila melanogaster

Life cycle stages

N

Population dynamics of P. nigrispinus structured in life stages maintained in Chrysomya putoria

Life cycle stages

N

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)

Thank you

Documents

Application of ecological models in entomology: a view ... · Application of ecological models in entomology: a view from Brazil . Working with ecological models ... • A preliminary