Integrating diverse model results into decision support for good environmental status and blue growth

Show simple item record Uusitalo, Laura Blenckner, Thorsten Puntila-Dodd, Riikka Skyttä, Annaliina Jernberg, Susanna Voss, Rudi Müller-Karulis, Bärbel Tomczak, Maciej T. Möllmann, Christian Peltonen, Heikki 2022-05-04T15:05:56Z 2022-05-04T15:05:56Z 2022
dc.identifier.citation Laura Uusitalo, Thorsten Blenckner, Riikka Puntila-Dodd, Annaliina Skyttä, Susanna Jernberg, Rudi Voss, Bärbel Müller-Karulis, Maciej T. Tomczak, Christian Möllmann, Heikki Peltonen. Integrating diverse model results into decision support for good environmental status and blue growth. Science of The Total Environment 806, part 2 (2022), 150450, ISSN 0048-9697.
dc.description Highlights • Environmental management needs to integrate multiple tools and objectives. • Bayesian network based decision support system is used as an integrating meta model. • Uncertainty of model projections is incorporated, enabling the evaluation of risks. • The model enables evaluation of synergies and trade-offs in management. • There are large uncertainties related to the future projections of the Baltic Sea.
dc.description.abstract Sustainable environmental management needs to consider multiple ecological and societal objectives simultaneously while accounting for the many uncertainties arising from natural variability, insufficient knowledge about the system's behaviour leading to diverging model projections, and changing ecosystem. In this paper we demonstrate how a Bayesian network- based decision support model can be used to summarize a large body of research and model projections about potential management alternatives and climate scenarios for the Baltic Sea. We demonstrate how this type of a model can act as an emulator and ensemble, integrating disciplines such as climatology, biogeochemistry, marine and fisheries ecology as well as economics. Further, Bayesian network models include and present the uncertainty related to the predictions, allowing evaluation of the uncertainties, precautionary management, and the explicit consideration of acceptable risk levels. The Baltic Sea example also shows that the two biogeochemical models frequently used in future projections give considerably different predictions. Further, inclusion of parameter uncertainty of the food web model increased uncertainty in the outcomes and reduced the predicted manageability of the system. The model allows simultaneous evaluation of environmental and economic goals, while illustrating the uncertainty of predictions, providing a more holistic view of the management problem.
dc.language.iso en
dc.publisher Elsevier
dc.relation.ispartofseries Science of the Total Environment
dc.rights CC BY 4.0
dc.subject ympäristönhoito
dc.subject ympäristön tila
dc.subject sosiaaliekologia
dc.subject päätöksenteko
dc.subject bayesilainen menetelmä
dc.subject mallit
dc.subject epävarmuus
dc.subject sininen kasvu
dc.subject meret
dc.subject strategia
dc.subject meristrategia
dc.subject Itämeri
dc.title Integrating diverse model results into decision support for good environmental status and blue growth
dc.format.volume 806
dc.format.issue Part 2
dc.identifier.urn URN:NBN:fi-fe2022050432735
dc.subject.yso decision support system
dc.subject.yso bayesian network
dc.subject.yso environmental management
dc.subject.yso ecosystem novelty
dc.subject.yso model emulator
dc.subject.yso socio-ecological system
dc.subject.yso blue growth
dc.subject.yso MSFD
dc.subject.yso good environmental status
dc.subject.yso Baltic Sea
dc.contributor.organization Suomen ympäristökeskus fi
dc.contributor.organization The Finnish Environment Institute en
dc.relation.issn 0048-9697
dc.relation.issn 1879-1026
dc.type.okm A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä fi
dc.type.okm A1 Journal article (refereed), original research en

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