Abstract
The European Water Framework Directive prescribes that the development of a river assessment system should be based on an ecological typology taking the biological reference conditions of each river type as a starting point. Aside from this assessment, water managers responsible for river restoration actions also need to know the steering environmental factors to meet these reference conditions for biological communities in each ecological river type. As such, an ecological typology based on biological communities is a necessity for efficient river management. In this study, different clustering techniques including the Sørensen similarity ratio, ordination analysis and self-organizing maps were applied to come to an ecological classification of a river. For this purpose, a series of sites within the Zwalm river basin (Flanders, Belgium) were monitored. These river sites were then characterized in terms of biotic (macroinvertebrates), physical–chemical and habitat variables. The cluster analysis resulted in a series of characteristic biotic communities that are found under certain environmental conditions, natural as well as human-influenced. The use of multiple clustering techniques can be of advantage to draw more straightforward and robust conclusions with regard to the ecological classification of river sites. The application of the clustering techniques on the Zwalm river basin, allowed for distinguishing five mutually isolated clusters, characterized by their natural typology and their pollution status. On the basis of this study, one may conclude that river management could benefit from the use of clustering methods for the interpretation of large quantities of data. Furthermore, the clustering results might enable the development of a cenotypology useful for efficiently steering river restoration and enabling river managers to meet a good ecological status in most of the rivers as set by the European Water Framework Directive.
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Adriaenssens V., Simons F., Goddeeris B., NguyenThi Hong L. and Goethals P.L.M. (2004). Potential of bio-indication of chironomid communities for assessment of running water quality (Flanders, Belgium). Belg. J. Zool. 134(1): 31–40
Austin M.P. (1985). Continuum conceptordination methods and niche theory. Annu. Rev. Ecol. Syst. 16: 39–61
Austin M.P. and Smith T.M. (1989). A new model for the continuum concept. Vegetatio 83: 35–47
Barbour M.T., Gerritsen J., Snyder B.D. and Stribling J.B. 1999. Rapid Bioassessment Protocols for use in Wadable Streams and Rivers: Periphyton, Benthic Macroinvertebrates and Fish, 2nd Ed. EPA 841-B-99-002. USEPAOffice of Water, Washington, DC.
Brosse S., Giraudel J.L. and Lek S. (2001). Utilisation of non-supervised neural networks and principal component analysis to study fish assemblages. Ecol. Model. 146: 159–166
Cao Y., Bark A.W. and Williams W.P. (1997). A comparison of clustering methods for river benthic community analysis. Hydrobiologia 347: 25–40
Chave P. (2001). The EU Water Framework Directivean introduction. IWA Publishing, 208
Collins S.L., Glenn S.M. and Roberts D.W. (1993). The hierarchical continuum concept. J. Veg. Sci. 4: 391–413
Cooley W.W. and Lohnes P.R. (1971). Multivariate Data Analysis. John Wiley and Sons, Inc.
Vanhooren G. (1983). Method for biological quality assessment of watercourses in Belgium. Hydrobiologia 100: 153–183
Vannevel R. (1991). Macroinvertebrates and Water Quality. Stichting Leefmilieu, Antwerp, Belgium, 316
Heylen S. (2001). Biotic index for sediment quality assessment of watercourses in Flanders, Belgium. Aquat. Ecol. 35(2): 121–133
EU 2000. Directive of the European Parliament and of the Council 2000/60/EC Establishing a Framework for Community Action in the Field of Water Policy. European Union, The European ParliamentThe Council, PE-CONS 3639/1/00 REV 1 EN62p. + annexes.
Foody G.M. (1999). Applications of the self-organising feature map neural network in community data analysis. Ecol. Model. 120: 97–107
Furse M.T., Moss D., Wright J.F. and Armitage P.D. (1984). The influence of seasonal and taxonomic factors on the ordination and classification of running-water sites in Great Britain on the prediction of macroinvertebrate communities. Freshwater Biol. 14: 257–280
Giraudel J.L. and Lek S. (2003). Ecological applications of unsupervised neural networks. In: Recknagel, F. (eds) Understanding Ecology by Biologically Inspired Computation, pp 15–33. Springer-Verlag, Berlin Heidelberg
Goethals P.L.M. and Pauw N. (2001). Development of a concept for integrated ecological river assessment in Flanders (Belgium). J. Limnol. 60: 7–16
Halkidi M., Batistakis Y. and Vazirgiannis M. (2001). On clustering validation techniques. J. Intell. Inf. Syst. 17(2–3): 107–145
Hawkes H.A. (1979). Invertebrates as indicators of river water quality. In: James, A. and Evison, L. (eds) Biological Indicators of Water Quality, pp. John Wiley, Chichester, UK
Hawkins C.P., Norris R.H., Gerritsen J., Hughes R.M., Jackson S.K., Johnson R.K. and Stevenson R.J. (2000). Evaluation of the use of landscape classifications for the prediction of freshwater biota: synthesis and recommendations. J. N. Am. Benthol. Soc. 19: 541–556
Hildrew A.G. (1992). Food webs and species interactions. In: Calow, P. and Petts, G.E. (eds) The Rivers Handbook: Hydrological and Ecological Principles, Vol. I, pp 309–329.
Hill M.O. (1973). Reciprocal averaging: an eigenvector method of ordination. J. Ecol. 61: 237–249
Hill M.O. (1979). DECORANA – a FORTRAN Program for Detrended Correspondence Analysis and Reciprocal Averaging. – Ecology and Systematics. Cornell University, Ithaca, New York, USA, 52
(1984). Norme Belge T 92-402. Biological Water Quality. Determination of a Biotic Index Based on Aquatic Macroinvertebrates. Institut Belge de Normalisation, Brussels, Belgium, 11
Jackson D.A. (1993). Multivariate analysis of benthic invertebrate communities: the implication of choosing particular data standardizations, measures of association and ordination methods. Hydrobiologia 268: 9–26
Kohonen T. (1982). Self-organization and associative memory. Springer-Verlag, Berlin, Germany, 312
McIntosh R.P. (1967). The continuum concept of vegetation. Bot. Rev. 33: 130–187
Palmer A. and White P.S. (1994). On the existence of ecological communities. J. Veg. Sci. 5: 279–282
Palmer A., Ambrose R.F. and LeRoy Poff N. (1997). Ecological theory and community restoration ecology. Restor. Ecol. 5(4): 291–300
Pardo I. and Armitage P.D. (1997). Species assemblages as descriptors of mesohabitats. Hydrobiologia 344: 111–128
Parsons M., Thoms M.C. and Norris R.H. (2003). Scales of macroinvertebrate distribution in relation to the hierarchical organization of river systems. J. N. Am. Benth. Soc. 22(1): 105–122
Prati L., Pavanello R. and Pesarin F. (1971). Assessment of surface water quality by a single index of pollution. Water Res. 5: 741–751
Rosenberg D.M. and Resh V.H. (1993). Introduction to freshwater biomonitoring and benthic macroinvertebrates. In: Rosenberg, D.M. and Resh, V.H. (eds) Freshwater Biomonitoring and Benthic Macroinvertbrates, pp. Chapman and Hall, New York, USA
Ruse L.P. (1996). Multivariate techniques relating macroinvertebrate and environmental data from a river catchment. Water Res. 30(12): 3017–3024
Schneiders A. and Verheyen R. (1998). A concept of integrated water management illustrated for Flanders (Belgium). Ecosyst. Health 4(4): 256–263
Schneiders A., Wils C. and Verheyen R. (1999). The use of ecological information in the selection of quality objectives for river conservation and restoration in Flanders (Belgium). Aquat. Ecosyst. Health Manage. 2: 137–154
Sørensen T. (1948). A method of establishing groups of equal amplitude in plant sociology based on similarity of species content. Det Kong Danske Vidensk Selsk Biol Slr (Copenhagen) 5(4): 1–34
Ter Braak C.J.F. and Smilauer P. (1998). Reference Manual and User's Guide to Canoco for Windows: Software for Canonical Community Ordination (version 4). Microcomputer Power, Ithaca, NY, USA, 352
Ter Braak C.J.F. and Verdonschot P.F.M. (1995). Canonical correspondence analysis and related multivariate analysis in aquatic ecology. Aquat. Sci. 57(3): 255–289
Townsend C.R. (1989). The patch dynamic concept of stream community ecology. J. N. Am. Benthol. Soc. 8: 36–50
Ultsch A. and Siemon H.P. (1990). Kohonen's self organizing feature maps for exploratory data analysis. Kluwer, Dordrecht, The Netherlands, 305–308
Vandenberghe V., Goethals P.L.M., Van Griensven A., Meirlan J., De Pauw N., Vanrolleghem P. and Bauwens W. 2004. Application of automated measurement stations for continuous water quality monitoring of the Dender river in Flanders, Belgium. Environ. Monit. Assess., in press.
Vannote R.M., Minshall G.W., Cummins K.W., Sedell J.R. and Cushing E. (1980). The river continuum concept. Can. J. Fish Aquat. Sci. 37: 130–137
(1986). Flexclus, an interactive program for classification and tabulation of ecological data. Acta Bot. Neerl. 35(3): 137–142
Verdonschot P.F.M. (1990). Ecological Characterization of Surface Waters in the Province of Overijssel (the Netherlands). PhD thesis, Wageningen, 255
Verdonschot P.F.M. (1995). Typology of macrofaunal assemblages: a tool for the management of running waters in the Netherlands. Hydrobiologia 297: 99–122
Verdonschot P.F.M. (2000). Integrated ecological assessment methods as a basis for sustainable catchment management. Hydrobiologia 422(423): 389–412
Verdonschot P.F.M. and Nijboer R.C. (2000). Typology of macrofaunal assemblages applied to water and nature management: a Dutch approach. In: Wright, J.F., Sutcliffe, D.W. and Furse, M.T. (eds) Assessing the Biological Quality of Fresh Water: RIVPACS and Other Techniques, pp 241–262. Ambleside, UK, FBA
Verdonschot P.F.M., Nijboer R.C. and Janssen S.N. (2000). Ecological typology limburg. Alterra, Wageningen, The Netherlands, 78
Verdonschot P.F.M. and Nijboer R.C. (2002). Towards a decision support system for stream restoration in the Netherlands: an overview of restoration projects and future needs. Hydrobiologia 478(1–3): 131–148
Vesanto J., Himber J., Alhoniemi E. and Parhankangas J. (2000). SOM toolbox for MATLAB 5. Helsinki University of Technology, Publications in Computer and Information Science, Helsinki, Finland, 59
(1997). Water quality 1996. Report Surface Water Monitoring. Aalst, Belgium (in Dutch)
Walley W.J., Martin R.W. and O’Connor M.A. (2000). Self-organising maps for classification of river quality from biological and environmental data. In: Denzer, R., Swayne, D.A., Purvis, M., and Schimak, G. (eds) Environmental Software Systems: Environmental Information and Decision Support. IFIP Conference Series, pp 27–41. Kluwer Academic Publishers
Walley W.J. and O’Connor M.A. (2001). Unsupervised pattern recognition for the interpretation of ecological data. Ecol. Model. 146: 219–230
Whittaker R.H. (1967). Gradient analysis of vegetation. Biol. Rev. 49: 207–264
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Adriaenssens, V., Verdonschot, P.F.M., Goethals, P.L.M. et al. Application of clustering techniques for the characterization of macroinvertebrate communities to support river restoration management. Aquat Ecol 41, 387–398 (2007). https://doi.org/10.1007/s10452-005-2836-0
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DOI: https://doi.org/10.1007/s10452-005-2836-0