Descy, Jean-Pierre

Modelling Community Structure in Freshwater Ecosystems

Descy, Jean-Pierre - Modelling Community Structure in Freshwater Ecosystems, ebook


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ISBN: 9783540268949
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Table of contents

1. General introduction
S Lek

2. Using bioindicators to assess rivers in Europe: An overview
3. Review of modelling techniques
3.Fish community assemblages

4. Introduction
5. Patterning riverine fish assemblages using an unsupervised neural network
Y S Park, T Oberdorff, S Lek

6. Predicting fish assemblages in France and evaluating the influence of their environmental variables
M Gevrey, Y S Park, T Oberdorff, S Lek

7. Fish diversity conservation and river restoration in southwest France: a review
A Aguilar Ibarra, P Lim, S Lek

8. Modelling of freshwater fish and macro-crustacean assemblages for biological assessment in New Zealand
M K Joy, R G Death

9. A Comparison of various fitting techniques for predicting fish yield in Ubolratana reservoir (Thailand) from a time series data
J Moreau, S Lek, W Leelaprata, B Sricharoendham, M Concepcion Villanueva

10. Patterning spatial variations in fish assemblage structures and diversity in the Pilica River system
T Penczak, A Kruk, Y S Park, S Lek

11. Optimisation of artificial neural networks for predicting fish assemblages in rivers
M Scardi, S Cataudella, E Ciccotti, P Dato, G Maio, E Marconato, S Salviati, L Tancioni, P Turin, M Zanetti

4.Macroinvertebrate community assemblages

12. Introduction
13. Sensitivity and robustness of a stream model based on artificial neural networks for the simulation of different management scenarios
A P Dedecker, P L M Goethals, N Pauw

14. A neural network approach to the prediction of benthic macroinvertebrate fauna composition in rivers
P Dato, L Mancini, L Tancioni, M Scardi

15. Predicting Dutch macroinvertebrate species richness and functional feeding groups using five modelling techniques
M Gevrey, Y S Park, P F M Verdonschot, S Lek

16. Comparison of clustering and ordination methods implemented to the full and partial data of benthic macroinvertebrate communities in streams and channels
R C Nijboer, Y S Park, S Lek, P F M Verdonschot

17. Prediction of macroinvertebrate diversity of freshwater bodies by adaptive learning algorithms
Y S Park, P F M Verdonschot, T S Chon, M Gevrey, S Lek

18. Hierarchical patterning of benthic macroinvertebrate communities using unsupervised artificial neural networks
Y S Park, I S Kwak, S Lek, T S Chon

19. Species spatial distribution and richness of stream insects in south-western France using artificial neural networks with potential use for biosurveillance
A Compin, Y S Park, S Lek, R Céréghino

20. Patterning community changes in benthic macroinvertebrates in a polluted stream by using artificial neural networks
I S Kwak, M Y Song, Y S Park, G Liu, S H Kim, H D Cho, E Y Cha, T S Chon

21. Patterning, predicting stream macroinvertebrate assemblages in Victoria (Australia) using artificial neural networks and genetic algorithms
N Horrigan, J Bobbin, F Recknagel, L Metzeling

5.Diatom and other algal assemblages

22. Introduction
23. Applying case-based reasoning to explore freshwater phytoplankton dynamics
P A Whigham

24. Modelling community changes of cyanobacteria in a flow regulated river (the lower Nakdong River, S. Korea) by means of a Self-Organizing Map (SOM)
G J Joo, K S Jeong

25. Use of artificial intelligence (MIR-max) and chemical index to define type diatom assemblages in Rhône basin and Mediterranean region
F Rimet, H M Cauchie, L Tudesque, L Ector

26. Classification of stream diatom communities using a self-organizing map
J Tison, J L Giraudel, Y S Park, M Coste, F Delmas

27. Diatom typology of low-impacted conditions at a multi-regional scale: combined results of multivariate analyses and SOM
V Gosselain, S Campeau, M Gevrey, M Coste, L Ector, F Rimet, J Tison, F Delmas, Y S Park, S Lek, J-P Descy

28. Prediction with artificial neural networks of diatom assemblages in headwater streams of Luxembourg
F Rimet, L Ector, L Hoffmann, M Gevrey, J L Giraudel, Y S Park, S Lek

29. Use of neural network models to predict diatom assemblages in the Loire-Bretagne basin (France)
P Dato, F Rimet, L Tudesque, L Ector, M Scardi

6.Development of community assessment techniques

30. Introduction
31. Evaluation of relevant species in communities: development of structuring indices for the classification of communities using a self-organizing map
Y S Park, M Gevrey, S Lek, J L Giraudel

32. Projection pursuit with robust indices for the analysis of ecological data
H Werner, T Rohatsch, G Pöppel, M Obach, R Wagner

33. A framework for computer-based data analysis and visualisation by pattern recognition
M A O’Connor, W J Walley

34. A rule-based vs. a set-covering implementation of the knowledge system LIMPACT and its significance for maintenance and discovery of ecological knowledge
M Neumann, J Baumeister

35. Predicting macro-fauna community types from environmental variables by means of support vector machines
W Akkermans, P Verdonschot, R Nijboer, P Goedhart, C Braak

36. User interface tool
Y S Park, S Lek

37. General conclusions and perspectives
M Scardi


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Keywords: SCIENCE / Environmental Science SCI026000

Publication year
Natural Sciences

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