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Incorporating Regime Metrics into Latent Variable Dynamic Models to Detect Early-Warning Signals of Functional Changes in Fisheries Ecology
[chapter]
2014
Lecture Notes in Computer Science
In this study, dynamic Bayesian networks have been applied to predict future biomass of geographically different but functionally equivalent fish species. A latent variable is incorporated to model functional collapse, where the underlying food web structure dramatically changes irrevocably (known as a regime shift). We examined if the use of a hidden variable can reflect changes in the trophic dynamics of the system and also whether the inclusion of recognised statistical metrics would improve
doi:10.1007/978-3-319-11812-3_26
fatcat:jqx23rj53rb5japs3b2yjmuiye