Ben Burgess

 

PhD Title

Testing a mechanistic general model of global ecosystems: improving prediction by increasing simplicity?

Current Research

The Madingley Model was developed as the first general ecosystem model, (GEM), which has a mechanistic basis and is able to be applied to both terrestrial and marine environments. It utilises small-scale events, (e.g. deaths), to make predictions for patterns at the ecosystem scale. Several of the predictions made by the Madingley Model are observed in empirical data, whilst other predictions raise interesting questions regarding ecological processes.

The focus of my PhD is to provide a greater understanding of how the processes within the Madingley Model inter-relate and whether there are any biological processes which may be functionally redundant. Additional processes, including intelligent animal behaviour, will also be incorporated into the Madingley Model in order to determine whether the model is missing key ecological processes.

Currently, I am investigating the how different stressors impact trophic cascades.

Supervisors

Dr David Murrell (CBER, UCL)

Dr Drew Purves (DeepMind, Google)

Professor Georgina Mace (CBER, UCL))

Other Interests 

Outside of work I like to spend time outdoors undertaking activities such as hiking, and skiing. I enjoy travelling and am looking forward to visiting new cities and environments over the next few years.

Brief CV

Years	Position	Department	Institution
2017 – Present	PhD in Computational Ecology	CBER	University College London
2016 – 2017	MRes in Computational Methods in Ecology and Evolution	Life Sciences	Imperial College London
2013 – 2016	BSc in Environmental Sciences	Biosciences	University of Nottingham