2005

Modelling Community Structure in Freshwater Ecosystems

ISBN: 978-3-540-23940-6 (Print) 978-3-540-26894-9 (Online)

Table of contents (37 chapters)

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  1. No Access

    Book Chapter

    Pages 1-5

    General introduction

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    Book Chapter

    Pages 7-19

    Using bioindicators to assess rivers in Europe: An overview

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    Book Chapter

    Pages 21-40

    Review of modelling techniques

  4. Fish community assemblages

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      Pages 41-42

      Introduction

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      Pages 43-53

      Patterning riverine fish assemblages using an unsupervised neural network

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      Book Chapter

      Pages 54-63

      Predicting fish assemblages in France and evaluating the influence of their environmental variables

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      Book Chapter

      Pages 64-75

      Fish diversity conservation and river restoration in southwest France: a review

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      Book Chapter

      Pages 76-89

      Modelling of freshwater fish and macro-crustacean assemblages for biological assessment in New Zealand

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      Book Chapter

      Pages 90-99

      A Comparison of various fitting techniques for predicting fish yield in Ubolratana reservoir (Thailand) from a time series data

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      Book Chapter

      Pages 100-113

      Patterning spatial variations in fish assemblage structures and diversity in the Pilica River system

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      Pages 114-129

      Optimisation of artificial neural networks for predicting fish assemblages in rivers

  5. Macroinvertebrate community assemblages

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      Book Chapter

      Pages 131-132

      Introduction

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      Book Chapter

      Pages 133-146

      Sensitivity and robustness of a stream model based on artificial neural networks for the simulation of different management scenarios

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      Book Chapter

      Pages 147-157

      A neural network approach to the prediction of benthic macroinvertebrate fauna composition in rivers

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      Book Chapter

      Pages 158-166

      Predicting Dutch macroinvertebrate species richness and functional feeding groups using five modelling techniques

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      Book Chapter

      Pages 167-188

      Comparison of clustering and ordination methods implemented to the full and partial data of benthic macroinvertebrate communities in streams and channels

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      Book Chapter

      Pages 189-205

      Prediction of macroinvertebrate diversity of freshwater bodies by adaptive learning algorithms

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      Book Chapter

      Pages 206-220

      Hierarchical patterning of benthic macroinvertebrate communities using unsupervised artificial neural networks

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      Book Chapter

      Pages 221-238

      Species spatial distribution and richness of stream insects in south-western France using artificial neural networks with potential use for biosurveillance

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      Book Chapter

      Pages 239-251

      Patterning community changes in benthic macroinvertebrates in a polluted stream by using artificial neural networks

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