Study level

  • PhD
  • Master of Philosophy
  • Honours
  • Vacation research experience scheme


Topic status

We're looking for students to study this topic.


Dr Matthew Adams
Research Fellow (DECRA)
Division / Faculty
Faculty of Science
Dr Kate Helmstedt
Research Fellow (DECRA)
Division / Faculty
Faculty of Science


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 decisions. A natural question, then, is what data is needed to better improve these decisions?

This project seeks to answer that question using decision science techniques, including value-of-information theory which is a coherent methodology for quantifying the relevance of new information for impacting decision-making. If of interest, the project could be potentially scoped to focus on networks on sub-Antarctic islands, for which advice on data collection is currently of great research importance.

Research activities

  • Coding up ordinary differential equations of ecosystems (e.g. Lotka-Volterra models in MATLAB)
  • Applying Bayesian inference techniques for model-data calibration
  • Applying value-of-information analysis to calibration outputs


  • Skills development in coding of models, model-data calibration and/or decision science techniques
  • Development of expertise in multidisciplinary research, cutting across mathematics, ecology and decision science
  • New hypotheses or explanations for environmental management decisions regarding future monitoring actions

In this project there would also be an opportunity to collaborate with and/or present results to decision science and quantitative ecology researchers from external institutions.

Skills and experience

Excellent skills in coding, especially ordinary differential equations and statistical inference, an interest in using mathematics and decision science techniques to address applied and/or theoretical ecology problems to inform environmental management, and a potential interest in working/communicating with a multidisciplinary team of researchers.


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