Trifonova, NedaScott, BethDominicis, Michela DeWaggitt, James J.Wolf, Judith2021-07-272021-07-272021-10Trifonova, N, Scott, B, Dominicis, M D, Waggitt, J J & Wolf, J 2021, 'Bayesian Network Modelling provides Spatial and Temporal Understanding of Ecosystem Dynamics within Shallow Shelf Seas', Ecological Indicators, vol. 129, 107997. https://doi.org/10.1016/j.ecolind.2021.1079971470-160XORCID: /0000-0001-5412-3952/work/162251669https://hdl.handle.net/2164/16869Acknowledgements This work was supported by the Supergen Offshore Renewable Energy (ORE) Hub, funded by the Engineering and Physical Sciences Research Council (EPSRC EP/S000747/1) and the NERC/DEFRA funded Marine Ecosystems Research Programme (MERP: NE/L003201/1). The authors would also like to thank the following people for providing data to this study: Debbie Russel, Signe Sveegaard, Mirko Hauswirth, Ruben Fijn, Chelsea Bradbury, Mark Lewis, Steve Geelhoed, Nicolas Vanermen, Oliver Boisseau, Dave Wall, Mark Jessopp, Jared Wilson, Alex Banks, Graham Pierce, Sally Hamilton, Jan Haelters, Suzanne Henderson, Peter Evans, Anita Gilles, Eric Stienen, Paul Thompson, Nicola Hodgins and Andrea Salkeld. For detailed information on their organizations and contacts, please refer to the SI. The authors would like to thank Ella-Sophia Benninghaus (University of Aberdeen) for providing the images in Fig. 6.169756980engSDG 7 - Affordable and Clean EnergySDG 13 - Climate ActionSDG 14 - Life Below Waterclimate changeHidden variablefunctional ecosystem changetop predator dynamicsFisheries effectsQH301 BiologyEngineering and Physical Sciences Research Council (EPSRC)EP/S000747/1Natural Environment Research Council (NERC)NE/L003201/1QH301Journal article10.1016/j.ecolind.2021.107997129