Professor David Warton
ARC Future Fellow
Field of Research: 
Ecological statistics, multivariate analysis, species distribution modelling, allometric line-fitting
Contact details:
+61 2 9385-7031


Room 2052 Red Centre UNSW, Kensington 2052


Research & Current Projects

My research interests are in ecological statistics - developing new methodologies for data analysis in ecological research, and increasing awareness in ecology and related disciplines of existing methodologies. For more details, see the Eco-Stats website, which summarises my current research activity together with that of a growing team of collaborators and research students.

My attraction to ecology stems from an interest in the natural world - and ecology is, after all, the study of how organisms get by from day-to-day in the natural world.  My attraction to statistics comes through an interest in general problems, and methodological problems can be quite general.  For example, my work in allometry is relevant not only to ecology, but to the other life sciences, astronomy, engineering, etc.

The Eco-Stats Research Group is a team of statistics researchers and students led by David Warton who specialise in ecological statistics — improving the methods for making use of data to answer research questions commonly asked in ecology.

We evaluate existing methodologies, explore the application of modern methods that are essentially unknown to ecologists, and where needed we develop entirely new statistical methodology, with an emphasis on model-based approaches (which are usually easier to interpret and which often have optimality properties).

We are based in the School of Mathematics and Statistics at UNSW, but our members are also affiliated with the Evolution & Ecology Research Centre, the School of Computer Science and Engineering, and the Australian River and Wetlands Centre.

We are supported by the Australian Research Council, with over $1M in current ARC funding.

Current Projects

  • Efficient algorithms for fitting latent variable models
  • New model-based approaches for analysis of high-dimensional abundances
  • Advances for errors-in variables modelling
  • Community-level modelling - (multivariate) spatial models in ecology
  • Allometry - extending tools for inference about size


See list: