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FOOD WEB MODELLING OF RIVER
ECOSYSTEMS FOR RISK ASSESSMENT OF
DOWN THE DRAIN CHEMICALS
SETAC EU, BASELWEDNESDAY 14 MAY 2014
A. Franco 1, A. Lombardo 2, L. Grechi 2, A. Barausse 2, A. Pivato 2
1 Unilever Safety and Environmental Assurance Centre2 University of Padova, IT
R&D - SEAC
OBJECTIVES
Explore the potential of food web modelling using AQUATOX to advance ecological relevance in ERA for down-the-drain chemicals
1) assess the feasibility of setting up food web ecological scenario(s) of lowland rivers for use in RA
2) explore potential added value of food web modelling in RA, compared to conventional approaches (e.g. PEC/PNEC):
• bioaccumulation• direct and indirect effects on ecosystem’s structure and functions• multiple stressors• biodiversity
MSc projects University of Padova (Italy) - Unilever SEAC (UK):1. Andrea Lombardo (river Thames, UK)2. Laura Grechi (river Po, Italy)
R&D - SEAC
AQUATOX
• Sponsored by US EPA
• Freely available software
• Validated ecological model
• Fully documented
• Several studies published, including effects of toxicants on contaminated sites, accidents, mesocosms experiments (POPs, pesticides)
It includes algorithms (>400 equations) to describe:
- Physical and chemical variables of the aquatic ecosystem- Biological dynamics and relationships between organisms- Chemicals’ fate and effects on the whole ecosystem
R&D - SEAC
CASE STUDIES
Coversham lock
Sonning lock
RIVER THAMES (UK)
• 4 km section, downstream of Reading centre • Medium catchment size, Q = 44 m3/s, v = 0.18 m/s• Area surveyed during International Biological
Programme (1966-1972). Described as “best studied river ecosystem” available in literature (Christensen and Pauly, 1993)
• Mean annual species abundance, energy flows and diet composition from Mathews (1993 - in Christensen and Pauly, 1993)
RIVER PO (ITALY)
• 41 km section, upstream of the delta • Large river catchment, Q = 1450 m3/s, v = 1 m/s• Historical biomonitoring data (1988-1990), mostly from
“grey” literature (several uncoordinated data sources including administrative authorities and universities). Data are mostly semi-quantitative, including time-series for some organisms.
• Food web structure and diet composition needed to be derived
Pontelagoscuro
Serravalle
V.Christensen, D. Pauly. 1993. Trophic models of aquatic ecosystems. ICLARM Conf. Proc. 26, 390p.
R&D - SEAC
THAMES CASE STUDY – model setup
derived from Mathews (1993) and literature cited therein
Main species Thames Aquatox state variableAverage annual dry biomass
[ g / m2 ]
Diatom, Cyclotella Phytoplankton 4,00
Filamentous algae, Diatoms Periphyton 1,04
Acorus Calamus, Nuphar Lutea Macrophytes 2,16
Rotifer Keratella Zooplankton 0,94
Chironomidae Young chironomids 11,11
Adult chironomid 7,77
Helobdella stagnalisInvertebrate predators 0,07
Unio, Anodonta anatina Filter feeders 18,34
Viviparus vBrowsers and grazers 3,77
External insects 17,94
Alburnus A Bleak 11,11
Rutilus rutilus Roach 6,77
Leuciscus L Dace 1,04
Gobio gobio Gudgeon 4,22
Perca fluviatilis Perch 1,45
Abramis brama Bream 2,73
Selection of model organisms and annual average biomasses
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Food web diet composition
THAMES CASE STUDY – model setup
derived from Mathews (1993) and literature cited therein
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RIVER THAMES FOOD WEB MODEL
Biomass fluxes in the River Thames food web. The color of the arrows describe the percentage of the predator’s diet covered by the food source
primary production
respiration= 0.9
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THAMES CASE STUDY – model calibration
Biomass g dry / m2
(Mathews 1993)Biomass g dry /m2
(Aquatox)Difference (%)
Phytoplankton 4.00 4.01 0.3
Periphyton 1.04 1.04 0.1
Macrophytes 2.16 2.17 0.2
Zooplankton 0.94 0.94 0.4
Young chironomids 11.11 11.13 0.2
Invertebrate predators 0.07 0.07 1.6
Filter feeders 18.34 18.34 0.0
Browsers and grazers 3.77 3.79 0.5
Adult chironomid 7.77 7.73 0.6
External insects 17.94 17.93 0.0
Bleak 11.11 11.11 0.1
Roach 6.77 6.76 0.1
Dace 1.04 1.03 1.2
Gudgeon 4.22 4.20 0.5
Perch 1.45 1.46 0.2
Bream 2.73 2.73 0.2
Calibrated food web: goodness of fit of control model based on mean annual biomass
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THAMES CASE STUDY - model stability
0
5
10
15
20
25
30
35
Aquatic invertebrates
periphyton
phytoplankton
macrophytes
dace
13
10.4
7.8
mg
/L2.6
5.2
30
24
18
12
6
g/m
2 d
ry
Jan Dec
bleak
perch
gudgeon
bream
roach
1 y simulation – whole food web (1967)
young chironomids
browsers and grazers
zooplankton
filter feeders
invertebrate predators
Apr OctJul
g/m
2
(mg/L)
(g/m2)
(g/m2)(g/m2)
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PO CASE STUDY – food web model
primary production
respiration= 0.27
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Animals
K1 uptake rateK2 elimination rateBCF
EC50growthEC50reprLC50
Plants
K1 uptake rateK2 elimination rateBCF
EC50photoLC50
tested species
modelled organisms
internal exposure
internal lethal/effects concentrations
ICE regressions / read across
Translation of lethal and sublethal effects on population dynamics: survival/growth.Population model usually an unstructured (total biomass) model
ECOTOX IN AQUATOX
Input data
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TEST CHEMICALS
LAS (Linear Alkylbenzene Sulfonate, C11.6)
TRICLOSAN (5-chloro-2-(2,4-dichlorophenoxy)-phenol)
Synthetic surfactant
Synthetic antimicrobial
• large ecotox dataset• monitoring exposure data available (Thames)• polar narcotic
• large ecotox dataset• monitoring exposure data available (Thames)• specific mode of action
R&D - SEAC
AQUATOX STATE VARIABLE Main species Thames LAS tox record Triclosan tox record
Phytoplankton Diatom, Cyclotella Selenastrum capricornutum Desmodesmus subspicatus
Periphyton Filamentous algae, Diatoms Microcystis aeruginosa Anabaena flos aquae
Macrophytes Acorus Calamus, Nuphar Lutea Lemna minor Lemna gibba
Chironomids Chironomidae Chironomus riparius Chironomus tentans
Browsers and Grazers Viviparus v. Limnodrilus hoffmeis Hyalella azteca
Zooplankton Rotifer Keratella Brachionus calyciflorus Paramecium caudatum
Filter Feeders Unio, anodonta anatina Curbicula Perna Perna
Inv. predators Helobdella stagnalis Limnodrilus hoffmeisteri Chironomus tentans
Dace Thames Leuciscus L Pimephales promelas Pimephales promelas
Bleak Alburnus A Pimephales promelas Pimephales promelas
Perch Perca fluviatilis Lepomis macrochirus Lepomis macrochirus
Gudgeon Gobio gobio Pimephales promelas Pimephales promelas
Roach Rutilus rutilus Tilapia mossambica Pimephales promelas
Bream Abramis brama Tilapia mossambica Pimephales promelas
Association between modelled and tested species: Thames case study
THAMES CASE STUDY – ECOTOX INPUTS
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PERTURBED SIMULATIONS
1 year of perturbed simulation at three different constant inflow concentrations of LAS and triclosan:
A. Realistic estimated environmental concentrations (LAS = 40 μg/L , TCS = 0.05 μg/L)
B. Hypothetical concentration equal to the lowest EC50 (LAS = 610 μg/L, TCS = 1.6 μg/L)
No effects predicted at the realistic concentrations (scenario A)
Results presented in the next slides for the river Thames model
vv
vv
Questions
• Do the chemicals accumulate in organisms beyond chemical equilibrium (biomagnification)? How do calculated internal concentrations compare to equilibirum BCF values?
• How big are indirect effects? Does the most impacted species correspond to the one with the lowest L(E)C50?
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RESULTS- Bioaccumulation
Triclosan
Log KOW = 4.76
Inherently biodegradable
BCF range (L/kgdry): 476 (macrophyte) – 18315 (minnow)
LAS
Log KOW = 3.32
Readily biodegradable
BCF exp range (L/kgdry): 100 (mussel)- 5450 (algae)
BAFmax/BCF = 1.99 (August)
Riv
er
Th
am
es
Riv
er
Po
BAFmax/BCF = 2.02 (June)
R&D - SEAC
RESULTS (Thames)LAS perturbed simulation
-100
-80
-60
-40
-20
0
20
40
60
80
Pe
rce
nta
ge
vari
ati
on
PERTURBED vs CONTROL biomass
(LAS = 610 μg/L)
PERIPHYTON
INV. PREDATORS
ZOOPLANKTON
PHYTOPLANKTON
BROWSERS AND GRAZERS
FILTER FEEDERS
Jan Jul Oct DecApr
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-100
-80
-60
-40
-20
0
20
40
60
Pe
rce
nta
ge
vari
ati
on
PERTURBED vs CONTROL biomass
(TCS C= 1.6 μg/L)
PHYTOPLANKTON
PERIPHYTON
ZOOPLANKTON
FILTERFEEDERS
ROACH
GUDGEON
RESULTS (Thames)Triclosan perturbed simulation
Jan Jul Oct DecApr
R&D - SEAC
0%
20%
40%
60%
80%
100%
120%
10 100 1000 10000
ǀ Bpert-Bcont ǀ
Bcont (%)
Log LC50 [μg/L]
Objective Perturbation vs LC50 C = 1.6 μg/L
16.1 16 625 400 200 1544 1260
400 260 260 370 260 260 260
PHYTOPLANKTON ZOOPLANKTON
FILTER FEEDERSCHIRONOMID
LC50 values of modelled organisms
RESULTS (Thames)Triclosan perturbed simulation
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CONCLUSIONS
The limited availability of biomonitoring data to develop food web models of river ecosystems remains a challenge.
Two food web scenarios were developed for a medium (Thames) and a large (Po) lowland river ecosystem. The models were successfully stabilised and calibrated for the mean annual biomass.
All data available were used for calibration. The attempt to calibrate on time series (river Po) was not successful. A robust external validation with time-dependent data could not be achieved
Objective 1) Assess the feasibility and uncertainty of setting up food web ecological scenario(s) of lowland rivers for use in RA
Objective 2) Explore potential added value of food web modelling in ecological risk assessment
Bioaccumulation: two realistic scenarios of lowland rivers’ food webs were developed and could be used to refine the bioaccumulation assessment
Direct and indirect effects on structure and functions of ecosystems at community level could be modelled and may be useful to inform RA. However, validation is very difficult, without a modern automatic calibration algorithm. Attempts exist in literature on simple, controlled systems (e.g. artificial streams).
R&D - SEAC
THE END
Thames at Sonning bridge(1885)
Thames at Sonning bridge (2000)
R&D - SEAC
R&D - SEAC
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
1 10 100 1000 10000 100000 1000000
ǀ B pert-B cont ǀ
Bcont
Log LC50 [μg/L]
Objective perturbation vs LC50 C= 610 μg/L
290000 9100 36000 8600 2400 3357 1024
2400 3200 3200 1670 3200 1695 1695
BROWSERS AND GRAZERS
ROACH
BREAM
PERCH
INV. PREDATORS
RESULTS (Thames)LAS perturbed simulation
LC50 values of modelled organisms
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OrganismAnnual
obs. biomass(mg dry/L)
Annualsimulated biomass
(mg dry/L)
Difference
(%)
Pearson
coeff.
Cyclotella 1.04 1.042 0.02 0.396
Chromulina 0.04 0.042 0.08 0.642
Brachionus 0.05 0.047 2.3 -0.0132
Amphipoda 0.004 0.0038 1.00 0.205
Chironomus 0.15 0.153 2.9 -0.082
Trichoptera 0.05 0.047 0.63 -0.0695
Oligochaeta 0.15 0.153 4.4 0.145
Gastropoda 0.002 0.0016 0.98 0.263
Odonata 0.07 0.066 0.76 -0.036
Bleak 0.56 0.559 0.2 0.159
Chub 2.52 2.523 0.04 0.425
Young wels catfish 5.77 5.73 0.6 0.21
Adult wels catfish 5.58 5.582 0.02 0.475
0
0.05
0.1
0.15
Chromulina (Phytoplankton)
Simulated (mg dry/L)Observed (mg/L dry)
Jan JulApr Oct Dec
Calibrated food web: goodness of fit of control model for mean annual biomass and time series (Pearson coeff.)
x
PO CASE STUDY – model calibration