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Bayesian Networks in Environmental Risk Assessment: A Review
Human activities both depend upon and have consequences on the environment. Environmental risk assessment (ERA) is a process of estimating the probability and consequences of the adverse effects of human activities and other stressors on the environment. Bayesian networks (BNs) can synthesize differ...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7821106/ https://www.ncbi.nlm.nih.gov/pubmed/32841493 http://dx.doi.org/10.1002/ieam.4332 |
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author | Kaikkonen, Laura Parviainen, Tuuli Rahikainen, Mika Uusitalo, Laura Lehikoinen, Annukka |
author_facet | Kaikkonen, Laura Parviainen, Tuuli Rahikainen, Mika Uusitalo, Laura Lehikoinen, Annukka |
author_sort | Kaikkonen, Laura |
collection | PubMed |
description | Human activities both depend upon and have consequences on the environment. Environmental risk assessment (ERA) is a process of estimating the probability and consequences of the adverse effects of human activities and other stressors on the environment. Bayesian networks (BNs) can synthesize different types of knowledge and explicitly account for the probabilities of different scenarios, therefore offering a useful tool for ERA. Their use in formal ERA practice has not been evaluated, however, despite their increasing popularity in environmental modeling. This paper reviews the use of BNs in ERA based on peer‐reviewed publications. Following a systematic mapping protocol, we identified studies in which BNs have been used in an environmental risk context and evaluated the scope, technical aspects, and use of the models and their results. The review shows that BNs have been applied in ERA, particularly in recent years, and that there is room to develop both the model implementation and participatory modeling practices. Based on this review and the authors’ experience, we outline general guidelines and development ideas for using BNs in ERA. Integr Environ Assess Manag 2021;17:62–78. © 2020 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC) |
format | Online Article Text |
id | pubmed-7821106 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-78211062021-01-26 Bayesian Networks in Environmental Risk Assessment: A Review Kaikkonen, Laura Parviainen, Tuuli Rahikainen, Mika Uusitalo, Laura Lehikoinen, Annukka Integr Environ Assess Manag Special Series: Applications of Bayesian Networks for Environmental Risk Assessment and Management Human activities both depend upon and have consequences on the environment. Environmental risk assessment (ERA) is a process of estimating the probability and consequences of the adverse effects of human activities and other stressors on the environment. Bayesian networks (BNs) can synthesize different types of knowledge and explicitly account for the probabilities of different scenarios, therefore offering a useful tool for ERA. Their use in formal ERA practice has not been evaluated, however, despite their increasing popularity in environmental modeling. This paper reviews the use of BNs in ERA based on peer‐reviewed publications. Following a systematic mapping protocol, we identified studies in which BNs have been used in an environmental risk context and evaluated the scope, technical aspects, and use of the models and their results. The review shows that BNs have been applied in ERA, particularly in recent years, and that there is room to develop both the model implementation and participatory modeling practices. Based on this review and the authors’ experience, we outline general guidelines and development ideas for using BNs in ERA. Integr Environ Assess Manag 2021;17:62–78. © 2020 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC) John Wiley and Sons Inc. 2020-10-06 2021-01 /pmc/articles/PMC7821106/ /pubmed/32841493 http://dx.doi.org/10.1002/ieam.4332 Text en © 2020 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC) This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Special Series: Applications of Bayesian Networks for Environmental Risk Assessment and Management Kaikkonen, Laura Parviainen, Tuuli Rahikainen, Mika Uusitalo, Laura Lehikoinen, Annukka Bayesian Networks in Environmental Risk Assessment: A Review |
title | Bayesian Networks in Environmental Risk Assessment: A Review |
title_full | Bayesian Networks in Environmental Risk Assessment: A Review |
title_fullStr | Bayesian Networks in Environmental Risk Assessment: A Review |
title_full_unstemmed | Bayesian Networks in Environmental Risk Assessment: A Review |
title_short | Bayesian Networks in Environmental Risk Assessment: A Review |
title_sort | bayesian networks in environmental risk assessment: a review |
topic | Special Series: Applications of Bayesian Networks for Environmental Risk Assessment and Management |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7821106/ https://www.ncbi.nlm.nih.gov/pubmed/32841493 http://dx.doi.org/10.1002/ieam.4332 |
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