Making Sense of Ecotoxicological Test Results: Towards Application of Process-based Models
The environmental risk of chemicals is routinely assessed by comparing predicted exposure levels to predicted no-effect levels for ecosystems. Although process-based models are commonly used in exposure assessment, the assessment of effects usually comprises purely descriptive models and rules-of-thumb. The problems with this approach start with the analysis of laboratory ecotoxicity tests, because only a limited amount of information is extracted. Standard summary statistics (NOEC, ECx, LC50) are of limited use in part because they change with exposure duration in a manner that varies with the tested species and the toxicant. As an alternative, process-based models are available. These models allow for toxicity measures that are independent of exposure time, make efficient use of the available data from routine toxicity tests, and are better suited for educated extrapolations (e.g., from individual to population, and from continuous to pulse exposure). These capabilities can be used to improve regulatory decisions and allow for a more efficient assessment of effects, which ultimately will reduce the need for animal testing. Process-based modeling also can help to achieve the goals laid out in REACH, the new strategy of the European Commission in dealing with chemicals. This discussion is illustrated with effects data for Daphnia magna, analyzed by the DEBtox model.
KeywordsEffects assessment Toxicity testing Dose-response modeling DEBtox REACH
This research was supported by the Netherlands Technology Foundation STW, applied science division of NWO and the technology programme of the Ministry of Economic Affairs (WEB. 5509). We thank Kees van Leeuwen (EC-JRC, Ispra) and the two anonymous reviewers for their valuable comments on drafts of this manuscript.
- Bartell SM, Gardner RH, O’Neill RV (1992) Ecological Risk Estimation. Lewis Publishers Chelsea, MI, USGoogle Scholar
- Christensen FM, De Bruijn JHM, Hansen BG, Munn SJ, Sokull-Klüttgen B, Pedersen F (2003) Assessment tools under the new European Union chemicals policy. GMI 41:5–19Google Scholar
- Crommentuijn T, Doodeman CJAM, Doornekamp A, Van Gestel CAM (1997) Life-table study with the springtail Folsomia candida (Willem) exposed to cadmium, chlorpyrifos and triphenyltin hydroxide. In Van Straalen NM, Løkke H (eds) Ecological Risk Assessment of Contaminants in Soil. Chapman & Hall, London, UK, pp 275–91Google Scholar
- EC (2003) Technical Guidance Documents on Risk Assessment, Part II. EUR 20418 EN/2 (http://ecb.jrc.it/tgdoc). Ispra, Italy: European Commission, Joint Research CentreGoogle Scholar
- Heugens, EHW (2003) Predicting Effects of Multiple Stressors on Aquatic Biota. Ph.D. Thesis, University of AmsterdamGoogle Scholar
- Kooijman SALM (2000) Dynamic Energy and Mass Budgets in Biological Systems. Cambridge University Press Cambridge, UKGoogle Scholar
- Kooijman SALM, Bedaux JJM, Gerritsen AAM, Oldersma H, Hanstveit AO (1998) Dynamic measures for ecotoxicity. In Newman MC, Strojan C (eds) Risk Assessment: Logic and Measurement. Ann Arbor Press, Chelsea, MI, US, pp 187–224Google Scholar
- OECD (1998) Report of the OECD Workshop on Statistical Analysis of Aquatic Toxicity Data. Organisation for Economic Cooperation and Development (OECD) Paris, FranceGoogle Scholar
- OECD (2003) Draft Guidance Document on the Statistical Analysis of Ecotoxicity Data. Paris, France: Organisation for Economic Cooperation and Development (OECD), (for ISO as working draft ISO TC 147/SC 5 N 18, ISO/WD 1)Google Scholar
- Posthuma L, Suter GW, Traas TP (2002) Species Sensitivity Distributions in Ecotoxicology. Lewis Publishers, Boca Raton, FL, USAGoogle Scholar