Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/18103
Title: Developing best-practice Bayesian Belief Networks in Ecological Risk Assessments for freshwater and estuarine ecosystems: A quantitative review
Contributor(s): McDonald, Karlie (author); Ryder, Darren  (author); Tighe, Matthew  (author)
Publication Date: 2015
DOI: 10.1016/j.jenvman.2015.02.031
Handle Link: https://hdl.handle.net/1959.11/18103
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.
Publication Type: Journal Article
Source of Publication: Journal of Environmental Management, v.154, p. 190-200
Publisher: Elsevier BV
Place of Publication: United Kingdom
ISSN: 1095-8630
0301-4797
Fields of Research (FoR) 2008: 050102 Ecosystem Function
050206 Environmental Monitoring
Fields of Research (FoR) 2020: 410203 Ecosystem function
410599 Pollution and contamination not elsewhere classified
Socio-Economic Objective (SEO) 2008: 961102 Physical and Chemical Conditions of Water in Coastal and Estuarine Environments
960903 Coastal and Estuarine Water Management
960503 Ecosystem Assessment and Management of Coastal and Estuarine Environments
Socio-Economic Objective (SEO) 2020: 180205 Measurement and assessment of estuarine water quality
180299 Coastal and estuarine systems and management not elsewhere classified
180601 Assessment and management of terrestrial ecosystems
Peer Reviewed: Yes
HERDC Category Description: C1 Refereed Article in a Scholarly Journal
Appears in Collections:Journal Article

Files in This Item:
2 files
File Description SizeFormat 
Show full item record
Google Media

Google ScholarTM

Check

Altmetric


Items in Research UNE are protected by copyright, with all rights reserved, unless otherwise indicated.