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| Titel |
Modelling groundwater-dependent vegetation patterns using ensemble learning |
| VerfasserIn |
J. Peters, B. Baets, R. Samson, N. E. C. Verhoest |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1027-5606
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| Digitales Dokument |
URL |
| Erschienen |
In: Hydrology and Earth System Sciences ; 12, no. 2 ; Nr. 12, no. 2 (2008-03-19), S.603-613 |
| Datensatznummer |
250010579
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| Publikation (Nr.) |
 copernicus.org/hess-12-603-2008.pdf |
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| Zusammenfassung |
| Vegetation patterns arise from the interplay between intraspecific and interspecific
biotic interactions and from different abiotic constraints and interacting driving
forces and distributions. In this study, we constructed an ensemble learning model that,
based on spatially distributed environmental variables, could model vegetation
patterns at the local scale. The study site was an alluvial floodplain with marked
hydrologic gradients on which different vegetation types developed. The model
was evaluated on accuracy, and could be concluded to perform well. However, model
accuracy was remarkably lower for boundary areas between two distinct vegetation
types. Subsequent application of the model on a spatially independent data set
showed a poor performance that could be linked with the niche concept to conclude
that an empirical distribution model, which has been constructed on local observations,
is incapable to be applied beyond these boundaries. |
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