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Designing efficient sampling algorithms for ensemble ecosystem modelling

This project seeks to use a combination of matrix algebra and advanced Monte Carlo methods for rare-event simulation to identify efficient algorithms for ensemble ecosystem modelling in large ecosystems. This project has the potential to significantly change the methods that researchers useto investigate complex ecosystems for the purposes of environmental management and future predictions.Ensemble ecosystem modelling (EEM) is a novel and increasingly popular method for generating predictions of future species abundance in complex ecosystems represented by generalisations of the Lotka-Volterra …

Study level
PhD, Master of Philosophy, Honours, Vacation research experience scheme
Faculty of Science
School of Mathematical Sciences
Research centre(s)
Centre for Data Science

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