Literature DB >> 22707420

Bayesian networks in environmental and resource management.

David N Barton1, Sakari Kuikka, Olli Varis, Laura Uusitalo, Hans Jørgen Henriksen, Mark Borsuk, Africa de la Hera, Raziyeh Farmani, Sandra Johnson, John D C Linnell.   

Abstract

This overview article for the special series, "Bayesian Networks in Environmental and Resource Management," reviews 7 case study articles with the aim to compare Bayesian network (BN) applications to different environmental and resource management problems from around the world. The article discusses advances in the last decade in the use of BNs as applied to environmental and resource management. We highlight progress in computational methods, best-practices for model design and model communication. We review several research challenges to the use of BNs in environmental and resource management that we think may find a solution in the near future with further research attention.
Copyright © 2012 SETAC.

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Year:  2012        PMID: 22707420     DOI: 10.1002/ieam.1327

Source DB:  PubMed          Journal:  Integr Environ Assess Manag        ISSN: 1551-3777            Impact factor:   2.992


  5 in total

1.  Probabilistic Evaluation of Ecological and Economic Objectives of River Basin Management Reveals a Potential Flaw in the Goal Setting of the EU Water Framework Directive.

Authors:  Turo Hjerppe; Antti Taskinen; Niina Kotamäki; Olli Malve; Juhani Kettunen
Journal:  Environ Manage       Date:  2016-12-16       Impact factor: 3.266

2.  Involving stakeholders in building integrated fisheries models using Bayesian methods.

Authors:  Päivi Haapasaari; Samu Mäntyniemi; Sakari Kuikka
Journal:  Environ Manage       Date:  2013-04-19       Impact factor: 3.266

Review 3.  From science to society: implementing effective strategies to improve wild pollinator health.

Authors:  Jane C Stout; Lynn V Dicks
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2022-05-02       Impact factor: 6.671

4.  Quantification of biophysical adaptation benefits from Climate-Smart Agriculture using a Bayesian Belief Network.

Authors:  Patrick J de Nijs; Nicholas J Berry; Geoff J Wells; Dave S Reay
Journal:  Sci Rep       Date:  2014-10-20       Impact factor: 4.379

5.  Increased Use of Bayesian Network Models Has Improved Environmental Risk Assessments.

Authors:  S Jannicke Moe; John F Carriger; Miriam Glendell
Journal:  Integr Environ Assess Manag       Date:  2020-12-11       Impact factor: 3.084

  5 in total

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