Lucena-Moya, Paloma and Brawata, Renee and Kath, Jarrod and Harrison, Evan and 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. ISSN 1364-8152
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.
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| Item Type: | Article (Commonwealth Reporting Category C) |
|---|---|
| Refereed: | Yes |
| Item Status: | Live Archive |
| Additional Information: | Permanent restricted access to Published version, in accordance with the copyright policy of the publisher. |
| Faculty / Department / School: | No Faculty |
| Date Deposited: | 18 Sep 2018 01:54 |
| Last Modified: | 28 Sep 2018 02:43 |
| Uncontrolled Keywords: | Bayesian networks, thresholds, aquatic ecology, macroinvertebrates, ecological community, TITAN, discretization |
| Fields of Research : | 05 Environmental Sciences > 0502 Environmental Science and Management > 050205 Environmental Management |
| Socio-Economic Objective: | D Environment > 96 Environment > 9605 Ecosystem Assessment and Management > 960506 Ecosystem Assessment and Management of Fresh, Ground and Surface Water Environments |
| Identification Number or DOI: | 10.1016/j.envsoft.2014.12.019 |
| URI: | http://eprints.usq.edu.au/id/eprint/34813 |
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