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.
Uusitalo, L., Tomczak, M. T., Mueller Karulis, B., Putnis, I., Trifonova, N., & Tucker, A. (2018). Hidden variables in a Dynamic Bayesian Network identify ecosystem level change. Ecological Informatics, 45, 9-15. https://doi.org/10.1016/j.ecoinf.2018.03.003