Improving ecosystem services modelling: Insights from a Bayesian network tools review. (November 2016)

• Record Type: Journal Article
• Authors: Pérez-Miñana, Elena
• Is Part Of: Environmental modelling & software. Volume 85(2016:Nov.)
• Page Start: 184
• Page End: 201
• Publication Date: 2016-11
• Subjects: Environmental risk management -- BN -- Bayesian networks -- Biodiversity -- Ecosystem services; 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.2016.07.007
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: Numerous studies attempt to unravel the role played by Biodiversity in ecosystems and ES reliance on Biodiversity. Achieving this aim is difficult given: the multi-layered Biodiversity-ES relationship; the temporal and spatial heterogeneity of ES; and, the interactions between biotic and abiotic components in ecosystems influencing processes and services. Bayesian networks have recently gained importance in ecological modelling. The integration of empirical data with expert knowledge and the explicit treatment of uncertainties, demonstrate their usefulness. Publications describing network-based Biodiversity-ES models, demonstrate their application is still limited. A watershed's environmental risk management network modelled from a Biodiversity-ES perspective is discussed. It demonstrates an improvement on conventional approaches, expressing risk in terms of the underlying causal relations between environmental risk events, triggers, controls and consequences. The model is developed in AgenaRisk and two other tools, Netica and Hugin. A comparison between them highlights the dependence on the tool of choice. Highlights: The event-trigger-control-consequence approach is a useful means to model environmental risk. Developing powerful solutions in environmental sciences often requires integrating GIS and BN. Certain difficulties identified when using BNs are caused by the modelling tool.