We developed a Bayesian belief network (BBN) model for application as a learning tool to simulate and assess the reach- and segment-scale effects of riparian vegetation properties and land use on stream ecosystem integrity. We modelled the ecological condition based on the Average Score Per Taxon (ASPT) index, a macroinvertebrate-based index widely used in European bioassessment, as a function of different riparian variables. We published this model in the journal of the Science of the Total Environment
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To download the manuscript, supplementary materials and the BBN model, click the links
* To explore the model, a Netica software is needed and can be downloaded here |