Graph neural networks and transfer entropy enhance forecasting of mesozooplankton community dynamics.

ABSTRACT: Mesozooplankton are critical components of marine ecosystems, acting as key intermediaries between primary producers and higher trophic levels by grazing on phytoplankton and influencing fish populations. They play pivotal roles in the pelagic food web and export production, affecting the biogeochemical cycling of carbon and nutrients. Therefore, accurately modeling and visualizing mesozooplankton community dynamics is essential for understanding marine ecosystem patterns and informing effective management strategies. However, modeling these dynamics remains challenging due to the complex interplay among physical, chemical, and biological factors, and the detailed parameterization and feedback mechanisms are not fully understood in theory-driven models. Graph neural network (GNN) models of

SUBMITTER: Jeung M 

PROVIDER: S-EPMC11655696 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature