Hidden variables in a Dynamic Bayesian Network identify ecosystem level change

Uusitalo, Laura, Tomczak, Maciej T., Müller-Karulis, Bärbel, Putnis, Ivars, Trifonova, Neda and Tucker, Allan (2018) Hidden variables in a Dynamic Bayesian Network identify ecosystem level change. Ecological Informatics, 45. pp. 9-15. ISSN 1574-9541

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Abstract

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.

Item Type:	Article
Uncontrolled Keywords:	baltic sea,dynamic bayesian network,ecosystem modelling,gotland basin,hidden variable,ecology, evolution, behavior and systematics,ecology,modelling and simulation,ecological modelling,computer science applications,computational theory and mathematics,applied mathematics ,/dk/atira/pure/subjectarea/asjc/1100/1105
Faculty \ School:	Faculty of Science > School of Environmental Sciences
Related URLs:	http://www.scopus.com/inward/record.url?...
Depositing User:	LivePure Connector
Date Deposited:	20 Feb 2026 17:30
Last Modified:	22 Feb 2026 07:30
URI:	https://ueaeprints.uea.ac.uk/id/eprint/102000
DOI:	10.1016/j.ecoinf.2018.03.003

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