Hidden variables in a Dynamic Bayesian Network identify ecosystem level change

Laura Uusitalo, Maciej T Tomczak (Collaborator), Barbel Mueller Karulis (Collaborator), Ivars Putnis (Collaborator), Neda Trifonova (Collaborator), Allan Tucker (Collaborator)

Research output: Contribution to journalArticlepeer-review

27 Citations (Scopus)


Ecosystems are known to change in terms of their structure and functioning over time. Modelling this change is a challenge, however, as data are scarce, and models often assume that the relationships between ecosystem components are invariable over time. Dynamic Bayesian Networks (DBN) with hidden variables have been proposed as a method to overcome this challenge, as the hidden variables can capture the unobserved processes. In this paper, we fit a series of DBNs with different hidden variable structures to a system known to have undergone a major structural change, i.e. the Baltic Sea food web. The exact setup of the hidden variables did not considerably affect the result, and the hidden variables picked up a pattern that agrees with previous research on the system dynamics.
Original languageEnglish
Pages (from-to)9-15
Number of pages6
JournalEcological Informatics
Early online date12 Mar 2018
Publication statusPublished - May 2018


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