An ecological risk assessment for managing and predicting trophic shifts in estuarine ecosystems using a Bayesian network. (November 2016)

• Record Type: Journal Article
• Authors: McDonald, K.S.; Tighe, M.; Ryder, D.S.
• Is Part Of: Environmental modelling & software. Volume 85(2016:Nov.)
• Page Start: 202
• Page End: 216
• Publication Date: 2016-11
• Subjects: Primary production -- Eutrophication -- Spatial and temporal variability -- Predictive modelling; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2016.08.014
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: Estuaries are dynamic systems at the transition between freshwater and marine ecosystems. In this study, a spatially and temporally explicit Bayesian network (BN) was developed for a tidally connected estuary in southeastern Australia. The BN provides an environmental risk assessment (ERA) for the probability of a shift to a eutrophied state based on markers of pelagic and benthic primary production. The model was created to provide an initial framework of system knowledge based on empirical data, with the intention that the model and its linkages be iteratively developed as more information becomes available. The BN was investigated for its potential to predict trophic shifts and provide a framework for evidence-based decision making. Model assessment was conducted through both sensitivity analysis and scenario tests. Through evaluation and updating, the BN can provide information on the key nutrients and bio-physical mechanisms regulating changes in trophic state in estuarine ecosystems. Highlights: Investigate the biophysical and chemical mechanisms regulating trophic shifts. Develop a best-practice Bayesian Network for shifts to a eutrophied state. Provide an ecological risk assessment to inform decision making for trophic shifts. Outline an approach for the prediction of trophic shifts in estuarine ecosystems.