Konferenzbeitrag
Relating Biodiversity of River Communities to Physical and Chemical Water Properties
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Datum
2001
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Metropolis
Zusammenfassung
We address the problem of finding relationships between the physical and chemical properties of river water and the biodiversity of the community present in that water . We apply the machine learning approach of induction of regression trees to biological and chemical data collected through regular monitoring of rivers in Slovenia. A predictive model is built, which identifies the most important parameters for predicting the species richness (the number oftaxa) of the community: these include biological oxygen demand (an overall indicator of pollution), water temperature, the season (month), total hardness, NO3, SiO2 and alkalinity.