poster setac warschau modellierung - gaiac-eco.de€¦ · nonylphenol concentration [µg/l] 0 100...
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Nonylphenol
Concentration [µg/l]
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Ext
inct
ion
risk
[%]
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100
IRDAMTWA
Institute for Environmental Research
Thomas G. Preuss1, Tido Strauss2, Hans Toni Ratte1
1Institute for Environmental Research, RWTH Aachen University, Worringerweg 1, D-52056 Aachen, Germany2Research Institute gaiac, Mies-van-der-Rohe Str. 19, D-52074 Aachen, Germany
How detailed do we have to model populationsto predict extinction probabilities and recovery time?
IntroductionThe interest for the application of population modelling within the pesticide registration is
increasing nowadays. In 2007 the LEMTox workshop was conducted to discuss the
possibilities and obstacles of population modelling for this purpose. One major conclusion
from this workshops was that modelling for environmental risk assessment should not focus
on realism but more on protectiveness. For this poster we investigated the questions which
environmental factors have to be included to do protective population modelling.
newborn
Feeding
Ageing
growth
juvenile development
born juveniles
brood size
embryo development
�yes
yes yes
no
no
no
maximal age ?
Adult? Birthing?
Food concentration
Competition
single pond treatment compared to an isolated control pond
mesocosm facility treatment compared to an isolated untreated pond
mesocosm facility treatment compared to the mesocosm facility control ponds
Effect models
no
Calculation of current development per day
Begin of dormancy?
Molt?
Chronic or naturalmortality? Adult?
yesDeath
yesDormant
no
no
yes
Deathyes no
noyes
Newly hatched larva
Additional allochtonous seeding
Emigration
Autochtonous seeding
New eggs
Next larval orthe pupal stage
Update of the developmental stage
Calculation of the actual test item concentration in the water
Calculation of the actual food level depending on population density
yes
Female?
yes
Acute mortality?
Mesocosm Mesocosm Mesocosm Mesocosm scenarioscenarioscenarioscenario Single Single Single Single pondpondpondpond scenarioscenarioscenarioscenario
uniform distribution of emerged adults
mesocosm facility with10 treatments and 3 controls
isolated untreated pond
isolated single treatment
We used two individual-based population models, which were tested previously on measured data, to investigate
the influence of environmental factors on the extinction probability and recovery time.
Extinction probability of Daphnia magna populations (IDamP) were calculated at laboratory scale. Recovery time
within a mesocosm facility was calculated for Chaoborus crystallinus. Since chaoborids are flying insects a
metapopulation approach was used to calculate autochthonous and allochthonous recovery for a typical mesocosm
facility and a single treated pond in comparison to mesocosm controls and an isolated control pond.
∫−=t
dttCWTWAftS0
)(*_1)(
Time weighted average (TWA):Ashauer et al. 2006
Immediate response (IR):The concentration-response curve
Damage assessment model (DAM):Lee et al. 2002, Ashauer et al. 2006
BoutWinB CkCk
dt
dC ×−×=
DlkCkdt
dDlrBk ×−×=
)0,max()( tresDlth −=
Fig. 3: Extinction probability for different effect model.Three different effect models were used to describe the toxicity for individual daphnids. The IR uses the concentration response curve, the
TWA is a pseudokinetic model and the semi-mechanistic DAM describes the effect by an toxicokinetic/toxicodynamic approach.
���� Sensitivity 2 to 5 times lower compared to Immediate response
���� Sensitivity 2 to 3 times lower compared to standard food level
���� Sensitivity 2 to 3 times lower with competition
IDamP-Model
Fig. 1: Extinction probability at different food concentrationExtinction probabilities were calculated at different food concentrations. Food dependent toxicity was not taken into account. Predictions
of population dynamics at different food concentrations are shown in the right figure. At lower food concentrations extinction probabilities
increase.
Fig. 2: Extinction probability at different competition scenariosCompetition was calculated for three scenarios, the competitor was insensitive against the compound. Equal competitor means the same
population dublicated, stronger competitor had higher feeding rate, weaker competitor lower. The right figure shows the population dynamic
for the three examples.
� an appropriate effect model
� food dependency
� important interactions, like competition � This can easily be done using different scenarios. For it only a few additional data are needed.
� Metapopulation approaches for dispersed migrating species (e.g. Chaoborus) � Here immigration to the stressed population as well as emmigration from
untreated populations have to be considered.
Pesticide
Concentration [µg/l]
0 10 20 30 40 50
Ext
inct
ion
risk
[%]
0
20
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60
80
100
IRDAMTWA
The IDamP model (Preuss et al. submitted):
• calibrated on individual level
• tested on individual and population level for
• different food concentrations & scenarios
• constant exposure (3,4-Dichloroanline (3,4-DCA),
Nonylphenol (p-NP))
• variable exposure (pesticide)
Extinction probabilities were calculated for 100 days at
constant exposure under semistatic conditions.
Substances were selected due to different mode of action,
p-NP (narcotic), 3,4-DCA (embryogenesis), pesticide (high
toxicity)
ConclusionsWith adequate models sensitivity of populations at different environmental scenarios can be investigated. This will help to estimate safety factors which are
protective but not over protective. For this purpose population models should include:
3,4-DCA
Concentration [µg/l]
0 20 40 60 80 100 120 140
Ext
inct
ion
risk
[%]
0
20
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60
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100
2x feedingStandard 0,1x feeding0,03x feeding
Nonylphenol
Concentration [µg/l]
0 100 200 300 400 500
Ext
inct
ion
risk
[%]
0
20
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60
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100
Time [d]
0 10 20 30 40
Pop
ulat
ion
size
0
100
200
300
400
500
600
Time [d]
0 10 20 30 40
0.5 mgC pop-1 d-1 1.3 mgC pop-1 d-1
3,4-DCA
Concentration [µg/l]
0 20 40 60 80 100 120 140
Ext
inct
ion
risk
[%]
0
20
40
60
80
100
without competitionweak competitorstrong competitorequal competitor
Pesticide
Concentration [µg/l]
0 10 20 30 40
Ext
inct
ion
risk
[%]
0
20
40
60
80
100
IBM-Chaoborus
The individual-based model IBM-Chaoborus:
• calibrated on individual level and one mesocosm
• tested on mesocosm data for
• untreated populations
• variable exposure scenarios (insecticide)
Fig. 6: Recovery time for different scenarios
For different scenarios recovery time was calculated dependent on the concentration of a two peak scenario. Whereas recovery
was observed within the mesocosm treatment compared to the mesocosm control up to 0.030 µg/l within 30 days, no recovery was
observed within the same scenario compared to an external isolated control above 0.012 µg/l and recovery lasted longer. This
phenomena was even stronger for single treatment scenarios.
Fig. 4: Population dynamics for a three peak application of alpha-Cypermethrin over three years
Population dynamics were calculated over three years with a three peak application every year. Two scenarios were choosen a
typical mesocosm facility with control ponds very close to the treated ponds, and an isolated treated pond without
immigration from undisturbed populations.
Fig. 5: Extinction probability for a two peak application over three yearsCalculated extinction probablity for the two scenarios shown in figure 4.
���� Populations are at higher risk without allochtone recovery and over time
���� Extinction probability increases over time at yearly applications
Larvae 1
Larvae 3
Larvae 4
Pupae
Adult
Larvae 2
without allochtonous recovery
alpha-Cypermethrin [µg/L]
1e-4 1e-3 1e-2 1e-1 1e+0
Ext
inct
ion
risk
[%]
0
20
40
60
80
100 first yearsecond yearthird year
Isolatedpopulation
Jan Jan Jan Jan
Indi
v.
0
50
100
150
200
Jan Jan Jan Jan
Indi
v.
0
50
100
150
200
Jan Jan Jan Jan
Indi
v.0
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Jan Jan Jan Jan
Indi
v.
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200
Jan Jan Jan Jan
Indi
v.
0
50
100
150
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0,0015 µg/L
0,015 µg/L
0,15 µg/L
with allochtonous recovery without allochtonous recovery
Jan Jan Jan Jan
Indi
v.
0
50
100
150
200
0,0015 µg/L
0,015 µg/L
0,15 µg/L
alpha-Cypermethrin [µg/L]0.000 0.005 0.010 0.015 0.020 0.025 0.030
Rec
over
y tim
e [d
ays]
0
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Recovery time after the second application
*
*no recovery at higher concentrations*:
�Recovery time of treated populations increases for isolated populations
�Recovery time in mesocsm facilities includes a reduced control density
0 200100 300 0 200100 300 0 200100 300
Time [d]
Abu
ndan
ce
Control 5 µg/l 3,4-DCA 30 µg/l 3,4-DCA
equa
lw
eak
stro
ng
Population of interest Competitor
0 200100 300 0 200100 300 0 200100 300
Time [d]
Abu
ndan
ce
0 200100 3000 200100 300 0 200100 3000 200100 300 0 200100 3000 200100 300
Time [d]
Abu
ndan
ce
Control 5 µg/l 3,4-DCA 30 µg/l 3,4-DCA
equa
lw
eak
stro
ng
Population of interest Competitor
with allochtonous recovery
alpha-Cypermethrin [µg/L]
1e-4 1e-3 1e-2 1e-1 1e+0
Ext
inct
ion
risk
[%]
0
20
40
60
80
100 first yearsecond yearthird year
Mesocosm population(Metapopulation)