متغیرهای پنهان در یک شبکه بیسیم پویا، تغییر سطح اکوسیستم را تعیین می کنند

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.