Relating Biodiversity of River Communities to Physical and Chemical Water Properties

dc.contributor.author	Džeroski, Sašo
dc.contributor.author	Grbovic, Jasna
dc.contributor.editor	Hilty, Lorenz M.
dc.contributor.editor	Gilgen, Paul W.
dc.date.accessioned	2019-09-16T09:32:01Z
dc.date.available	2019-09-16T09:32:01Z
dc.date.issued	2001
dc.description.abstract	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.	de
dc.description.uri	http://enviroinfo.eu/sites/default/files/pdfs/vol103/0367.pdf	de
dc.identifier.uri	https://dl.gi.de/handle/20.500.12116/26730
dc.publisher	Metropolis
dc.relation.ispartof	Sustainability in the Information Society
dc.relation.ispartofseries	EnviroInfo
dc.title	Relating Biodiversity of River Communities to Physical and Chemical Water Properties	de
dc.type	Text/Conference Paper
gi.citation.publisherPlace	Marburg
gi.conference.date	2001
gi.conference.location	Zürich
gi.conference.sessiontitle	Water Management

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