The use of Dynamic Bayesian Network Modelling for the Spatial and Temporal Understanding of Marine Ecosystem Dynamics
Chaired by: Dr Neda Trifonova, University of Aberdeen
Taking place: Wednesday 26 March 2025, 1:00 - 1:40pm
(Note: the date has been rescheduled from a postponed session on January 29)
Dr Trifonova will discuss the use of machine learning techniques to understand the ecosystem-level effects at regional and shelf-wide scales following the deployment of large-scale offshore wind and under alternative fishing and climate change scenarios. Bayesian ecosystem models will be discussed with a focus on how they can be used to predict the cumulative effects on the population trends across a range of species and to link these outputs to changes in ecosystem services and natural capital to assess the environmental and socio-economic benefits and trade-offs.
About the Speaker
Dr Neda Trifonova is an Advanced Research Fellow at the University of Aberdeen. Her expertise is in the application of machine learning techniques such as Bayesian networks and their use as whole ecosystem approaches to understand species interactions across space and time and their interactions with natural and anthropogenic factors. Currently, Dr Trifonova works on the ECOWind Programme, PELAgIO project to build an ecosystem-level understanding of projected changes following the development of large-scale offshore wind and climate change to support the development of evidence-based policy and marine management.
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