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

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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.

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Titel: Integrating diverse model results into decision support for good environmental status and blue growth
Författare: Uusitalo, Laura; Blenckner, Thorsten; Puntila-Dodd, Riikka; Skyttä, Annaliina; Jernberg, Susanna; Voss, Rudi; Müller-Karulis, Bärbel; Tomczak, Maciej T.; Möllmann, Christian; Peltonen, Heikki
Upphovmannens organisation: Suomen ympäristökeskus
The Finnish Environment Institute
Utgivare: Elsevier
Datum: 2022
Språk: en
Tillhör serie: Science of the Total Environment
ISSN: 0048-9697
Permanenta länken (URI):
Abstrakt: 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.
Beskrivning: 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.
Subject: ympäristönhoito
ympäristön tila
bayesilainen menetelmä
sininen kasvu
Subject (yso): decision support system
bayesian network
environmental management
ecosystem novelty
model emulator
socio-ecological system
blue growth
good environmental status
Baltic Sea
Licens: CC BY 4.0

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