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

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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)

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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

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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.

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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

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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)

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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

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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).

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THE END

Thames at Sonning bridge(1885)

Thames at Sonning bridge (2000)

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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