Trifonova, NedaKenny, AndrewMaxwell, DavidDuplisea, DanielFernandes, JoseTucker, Allan2020-04-022020-04-022015-11Trifonova, N, Kenny, A, Maxwell, D, Duplisea, D, Fernandes, J & Tucker, A 2015, 'Spatio-temporal Bayesian network models with latent variables for revealing trophic dynamics and functional networks in fisheries ecology', Ecological Informatics, vol. 30, pp. 142-158. https://doi.org/10.1016/j.ecoinf.2015.10.0031574-9541https://hdl.handle.net/2164/13958We would like to thank Johan Van Der Molen from CEFAS for providing the ERSEM model outputs, the ICES DATRAS database for the North Sea IBTS data and Historical Catch Statistics, ICES North Sea Integrated Assessment Working Group (WGINOSE) and the organisations which provide data for the ICES assessment process, in particular SAHFOS who have provided the North Sea plankton data, Chiara Franco for general advice and the Natural Environment Research Council, UK (NE/J01642X/1) who has provided the funding of this research. We gratefully acknowledge support from the European Commission (OCEAN-CERTAIN, FP7-ENV-2013-6.1-1; no: 603773) for David Maxwell and support from CEFAS for Andrew Kenny and David Maxwell.172517982engSDG 14 - Life Below WaterBayesian networkHidden variableSpatial autocorrectionBiomass predictionFunctional networkTrophic interactionsMarine ecologyGC OceanographyGE Environmental SciencesNatural Environment Research Council (NERC)NE/J01642X/1European CommissionOCEAN-CERTAIN, FP7-ENV-2013-6.1-1; no: 603773GCGEJournal article10.1016/j.ecoinf.2015.10.00330