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Bayesian inference meets value-of-information: how much more data do we really need for management of ecological networks?

The project involves applying value-of-information analysis across ecosystem models fit to data using Bayesian inference, to yield conclusions that have potentially wide application across the field of community ecology.Ecological networks use generalisations of the Lotka-Volterra model to describe the interactions between species, including predator-prey, mutualism, parasitism and others. Lotka-Volterra models fit to noisy data from synthetic ecological networks using Bayesian inference reveal that the predictions made in these networks carry large uncertainty but they may still be useful for informing …

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

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