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Developing best-practice Bayesian Belief Networks in ecological risk assessments for freshwater and estuarine ecosystems: a quantitative review

Citation

McDonald, KS and Ryder, DS and Tighe, M, Developing best-practice Bayesian Belief Networks in ecological risk assessments for freshwater and estuarine ecosystems: a quantitative review, Journal of Environmental Management, 154 pp. 190-200. ISSN 0301-4797 (2015) [Refereed Article]

Copyright Statement

2015 Elsevier Ltd.

DOI: doi:10.1016/j.jenvman.2015.02.031

Abstract

Bayesian Belief Networks (BBNs) are being increasingly used to develop a range of predictive models and risk assessments for ecological systems. Ecological BBNs can be applied to complex catchment and water quality issues, integrating multiple spatial and temporal variables within social, economic and environmental decision making processes. This paper reviews the essential components required for ecologists to design a best-practice predictive BBN in an ecological risk assessment (ERA) framework for aquatic ecosystems, outlining: (1) how to create a BBN for an aquatic ERA?; (2) what are the challenges for aquatic ecologists in adopting the best-practice applications of BBNs to ERAs?; and (3) how can BBNs in ERAs influence the science/management interface into the future? The aims of this paper are achieved using three approaches. The first is to demonstrate the best-practice development of BBNs in aquatic sciences using a simple nutrient model. The second is to discuss the limitations and challenges aquatic ecologists encounter when applying BBNs to ERAs. The third is to provide a framework for integrating best-practice BBNs into ERAs and the management of aquatic ecosystems. A quantitative review of the application and development of BBNs in aquatic science from 2002 to 2014 was conducted to identify areas where continued best-practice development is required. We outline a best-practice framework for the integration of BBNs into ERAs and study of complex aquatic systems.

Item Details

Item Type:Refereed Article
Keywords:modelling, ecosystem health, ecology
Research Division:Biological Sciences
Research Group:Ecology
Research Field:Freshwater ecology
Objective Division:Environmental Management
Objective Group:Coastal and estuarine systems and management
Objective Field:Assessment and management of coastal and estuarine ecosystems
UTAS Author:McDonald, KS (Ms Karlie McDonald)
ID Code:154689
Year Published:2015
Web of Science® Times Cited:28
Deposited By:Sustainable Marine Research Collaboration
Deposited On:2022-12-21
Last Modified:2023-01-12
Downloads:0

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