Modeling the chemical and toxic water status of the Scheldt basin (Belgium), using aquatic invertebrate assemblages and an advanced modeling method Muriel Gevrey a, * , Lise Comte b , Dick de Zwart c , Eric de Deckere d , Sovan Lek b a CNRS, Lab Evolution et Diversité Biologique (EDB), UMR 5174 CNRS-UPS,118 route de Narbonne, 31062 Toulouse cedex 4, France b Université Paul Sabatier, Lab Evolution et Diversité Biologique (EDB), UMR 5174 CNRS-UPS,118 route de Narbonne, 31062 Toulouse cedex 4, France c National Institute for Public Health and the Environment (RIVM), Laboratory for Ecological Risk Assessment (LER), PO Box 1, NL-3720 BA Bilthoven, The Netherlands d University of Antwerp, Institute of Environment & Sustainable Development, Department of Biology, Universiteitsplein 1, 2610 Wilrijk, Belgium The use of assemblage-level data in a Self-Organizing Maps algorithm to evaluate the ecological status of the Scheldt basin and to support environmental decision-making. article info Article history: Received 21 October 2009 Received in revised form 6 July 2010 Accepted 7 July 2010 Keywords: Physico-chemical and toxic water status Self-Organizing Maps multi-substance Potentially Affected Fraction of species abstract Self-Organizing Maps have been used on monitoring sites in several Scheldt sub-basins to identify the main aquatic invertebrate assemblages and relate them to the physico-chemical and toxic water status. 12 physico-chemical variables and 2 estimates of toxic risk were available for a dataset made up of a total of 489 records. Two of the five defining clusters reflecting a relatively clean environment were composed by very well diversified functional feeding groups and sensitive taxa. The cleanest assemblage was mainly linked to the sites from the Nete sub-basin. The three other clusters were inversely described with a dominance of oligochaetes and deposit feeders as well as a bad water quality. Such an analysis can be used to support ecological status assessment of rivers and thus might be useful for decision-makers in the evaluation of chemical and toxic water status, as required by the EU Water Framework Directive. Ó 2010 Elsevier Ltd. All rights reserved. 1. Introduction Natural water is an important resource for industry, agriculture, recreation and drinking water but represents also crucial habitats for many different types of wildlife. Nevertheless, increasing problems with regard to water quantity and quality led to the development of an integrated approach for water management, including all water-related impacts (Achleitner et al., 2005) as the amendment of the European Water Framework Directive (WFD) (EU, 2000). One of the main objectives of this directive is the achievement of a “good ecological status” in all water bodies of the European Union. The WFD qualifies the status of aquatic ecosys- tems based on traditional hydromorphological, physico-chemical and biological parameters and on priority pollutant concentrations. In order to support the WFD by proposing some tools able to identify the causes of insufficient ecological status, a European Integrated Project within the Sixth Framework Programme called MODELKEY started in 2005 (Contract No. 511237-GOCE, http:// www.modelkey.org/). MODELKEY stands for “Models for assess- ing and forecasting the impact of environmental key pollutants on freshwater and marine ecosystems and biodiversity” (Brack et al., 2005). Aquatic communities are rapidly disturbed by modifications in the physical or chemical quality of rivers (Hellawell,1986). Chemical pollution is a well-known factor that may cause a decline in biodi- versity in freshwater ecosystems. However, the diagnosis, predic- tion and forecasting of toxic impacts require discrimination from other stresses and for reliable causeeeffect relationships between chemical pollution and biodiversity decline (Brack et al., 2005). As mentioned by Brack et al. (2009), the applicable tools routinely used for the analysis of the role of toxicant mixtures in affecting the ecological status are still limited, even though toxic pollution can be of particular local and regional significance, despite the importance of hydromorphology and eutrophication. One of the objectives of this project is the development of inte- grated diagnostic effect models based on the patterns of aquatic communities and applying new modeling tools such as Artificial Neural Networks (ANNs). * Corresponding author. E-mail addresses: gevrey@cict.fr (M. Gevrey), griselda.comte@orange.fr (L. Comte), dick.de.Zwart@rivm.nl (D. de Zwart), eric.dedeckere@ua.ac.be (E. de Deckere), lek@ cict.fr (S. Lek). Contents lists available at ScienceDirect Environmental Pollution journal homepage: www.elsevier.com/locate/envpol 0269-7491/$ e see front matter Ó 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.envpol.2010.07.006 Environmental Pollution 158 (2010) 3209e3218