Stream fish assemblages and basin land cover in a river network

The Science of the Total Environment
Young-Seuk ParkSovan Lek

Abstract

This study focused on characterizing fish assemblages in the Adour-Garonne basin and identifying the relative influences of landscape-scale features on observed patterns in stream fish assemblages. Two different artificial neural network algorithms were used: a self-organizing map (SOM) and a multilayer perceptron (MLP). A SOM was applied to determine fish assemblage types, and a MLP was used to predict the fish assemblage types defined by the SOM. Thirty four species were collected at 191 sampling sites in a major river-system, the Adour-Garonne basin, and topographical factors, namely altitude, distance from source and surface area of drainage basin were measured. Using GIS, land cover types (agricultural land, forests and urbanized artificial surface) were calculated for each site and expressed as percentage of the surface area of basin. These variables were introduced to the MLP and factorial discriminant analysis for the prediction of assemblage types. As a result, the SOM distinguished three fish assemblage types according to the differences of species composition, and the assemblage types were better predicted with landscape-scale features by MLP than discriminant analysis. The percentages of agricultural land and the su...Continue Reading

References

Dec 9, 1998·Proceedings of the National Academy of Sciences of the United States of America·J S HardingE B Jones
Jul 10, 2001·Environmental Management·L WangR Bannerman
Jun 3, 2004·The Science of the Total Environment·Young-Seuk ParkSovan Lek

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Citations

Apr 27, 2010·Environmental Science and Pollution Research International·Lise ComteMuriel Gevrey
Dec 4, 2012·International Journal of Environmental Research and Public Health·Yong-Su KwonYoung-Seuk Park
Dec 10, 2015·Global Change Biology·Johannes RadingerChristian Wolter
May 16, 2006·The Science of the Total Environment·Andrew J Wade
Jun 15, 2010·The Science of the Total Environment·Yongfeng HeSovan Lek

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