Predicting ecosystem components in the Gulf of Mexico and their responses to climate variability with a dynamic Bayesian network model.

ABSTRACT: The Gulf of Mexico is an ecologically and economically important marine ecosystem that is affected by a variety of natural and anthropogenic pressures. These complex and interacting pressures, together with the dynamic environment of the Gulf, present challenges for the effective management of its resources. The recent adoption of Bayesian networks to ecology allows for the discovery and quantification of complex interactions from data after making only a few assumptions about observations of the system. In this study, we apply Bayesian network models, with different levels of structural complexity and a varying number of hidden variables to account for uncertainty when modeling ecosystem dynamics. From these models, we predict focal ecosystem components within the Gulf of Mexico. The pred

SUBMITTER: Trifonova N 

PROVIDER: S-EPMC6344104 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature