Discretization of continuous predictor variables in Bayesian networks: an ecological threshold approach

Article

Lucena-Moya, Paloma, Brawata, Renee, Kath, Jarrod, Harrison, Evan, El Sawah, Sondoss and Dyer, Fiona. 2015. "Discretization of continuous predictor variables in Bayesian networks: an ecological threshold approach." Environmental Modelling and Software. 66, pp. 36-45. https://doi.org/10.1016/j.envsoft.2014.12.019
Article Title

Discretization of continuous predictor variables in Bayesian networks: an ecological threshold approach

ERA Journal ID4673
Article CategoryArticle
AuthorsLucena-Moya, Paloma (Author), Brawata, Renee (Author), Kath, Jarrod (Author), Harrison, Evan (Author), El Sawah, Sondoss (Author) and Dyer, Fiona (Author)
Journal TitleEnvironmental Modelling and Software
Journal Citation66, pp. 36-45
Number of Pages10
Year2015
PublisherElsevier
Place of PublicationUnited Kingdom
ISSN1364-8152
1873-6726
Digital Object Identifier (DOI)https://doi.org/10.1016/j.envsoft.2014.12.019
Abstract

Bayesian networks (BNs) are a popular tool in natural resource management but are limited when dealing with ecological assemblage data and when discretizing continuous variables. We present a method that addresses these challenges using a BN model developed for the Upper Murrumbidgee River Catchment (south-eastern Australia). A selection process was conducted to choose the taxa from the
whole macroinvertebrate assemblage that were incorporated in the BN as endpoints. Furthermore, two different approaches to the discretization of continuous predictor variables for the BN were compared. One approach used Threshold Indicator Taxa Analysis (TITAN) which estimates the thresholds based on the biological community. The other approach used was the expert opinion. The TITAN-based discretizations provided comparable predictions to expert opinion-based discretizations but in combining
statistical rigor and ecological relevance, offer a novel and objective approach to the discretization. The
TITAN-based method may be used together with expert opinion.

KeywordsBayesian networks, thresholds, aquatic ecology, macroinvertebrates, ecological community, TITAN, discretization
ANZSRC Field of Research 2020410404. Environmental management
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Institution of OriginUniversity of Southern Queensland
Byline AffiliationsUniversity of Canberra
Australian National University
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