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- aggregation classification "C1".
- aggregation creator person.
- aggregation creator person.
- aggregation creator person.
- aggregation date "2010".
- aggregation format "application/pdf".
- aggregation hasFormat 1020729.bibtex.
- aggregation hasFormat 1020729.csv.
- aggregation hasFormat 1020729.dc.
- aggregation hasFormat 1020729.didl.
- aggregation hasFormat 1020729.doc.
- aggregation hasFormat 1020729.json.
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- aggregation hasFormat 1020729.txt.
- aggregation hasFormat 1020729.xls.
- aggregation hasFormat 1020729.yaml.
- aggregation isPartOf urn:isbn:9788890357411.
- aggregation language "eng".
- aggregation publisher "International Environmental Modelling and Software Society (iEMSs)".
- aggregation rights "I have transferred the copyright for this publication to the publisher".
- aggregation subject "Earth and Environmental Sciences".
- aggregation title "Development of data-driven models for the assessment of macroinvertebrates in rivers in Flanders".
- aggregation abstract "The Flemish Environment Agency (VMM) has been gathering water quality and biological data in more than 1000 sites per year since 1989. These data have been used to develop predictive models for macroinvertebrates based on data-driven methods (regression trees). These models relate the river status to the Multimetric Macroinvertebrate Index Flanders (MMIF), which is a score system developed to report in the context of the European Water Framework Directive. The trees have been developed in the R software, and several optimisations have been made by altering the dataset (variable and record selections). Models were evaluated based on mathematical criteria, ecological insight and user convenience (clarity, simplicity and coupling-potential with water quality models of the VMM). The study is a first attempt to construct a set of models that can be used by the VMM to evaluate the ecological benefits of their river management plans.".
- aggregation authorList BK182221.
- aggregation endPage "1956".
- aggregation startPage "1948".
- aggregation volume "3".
- aggregation aggregates 1026390.
- aggregation isDescribedBy 1020729.
- aggregation similarTo LU-1020729.