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The prediction of macrophyte species occurrence in Swiss ponds

Joye, D. ; Oertli, B. ; Lehmann, A. ; Juge, R. ; Lachavanne, J.

In: Hydrobiologia, 2006, vol. 570, no. 1, p. 175-182

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    Titre
    • The prediction of macrophyte species occurrence in Swiss ponds
    Auteur
    • Joye, D.. Laboratoire d'écologie et de biologie aquatique, Université de Genève, chemin des Clochettes 18, CH-1206, Genève, Switzerland
    • Oertli, B.. University of Applied Sciences of Western Switzerland, EIL, 150 route de Presinge, CH-1254, Jussy, Switzerland
    • Lehmann, A.. GRID-Europe, International Environmental House, 18 ch. des Anémones, CH-1219, Châtelaine, Switzerland
    • Juge, R.. Laboratoire d'écologie et de biologie aquatique, Université de Genève, chemin des Clochettes 18, CH-1206, Genève, Switzerland
    • Lachavanne, J.. Laboratoire d'écologie et de biologie aquatique, Université de Genève, chemin des Clochettes 18, CH-1206, Genève, Switzerland
    Type de document
    • Postprint
    Identifiant OAI-PMH
    • oai:doc.rero.ch:318132
    Summary
    The study attempted to model the abundance of aquatic plant species recorded in a range of ponds in Switzerland. A stratified sample of 80 ponds, distributed all over the country, provided input data for model development. Of the 154 species recorded, 45 were selected for modelling. A total of 14 environmental parameters were preselected as candidate explanatory variables. Two types of statistical tools were used to explore the data and to develop the predictive models: linear regression (LR) and generalized additive models (GAMs). Six LR species models had a reasonable predictive ability (30-50% of variance explained by the selected predictors). There was a gradient in the quality of the 45 GAM models. Ten species models exhibited both a good fit and statistical robustness: Lemnaminor, Phragmitesaustralis, Lysimachiavulgaris, Galiumpalustre, Lysimachianummularia, Irispseudacorus, Lythrumsalicaria, Lycopuseuropaeus, Phalarisarundinacea, Alismaplantago-aquatica, Schoenoplectuslacustris, Carexnigra. Altitude appeared to be a key explanatory variable in most of the species models. In some cases, the degree to which the shore was shaded, connectivity between water bodies, pond area, mineral nitrogen levels, pond age, pond depth, and the extent of agriculture or pasture in the catchment were selected as additional explanatory variables. The species models demonstrated that it is possible to predict species abundance of aquatic macrophytes and that each species responded individually to distinct environmental variables