Using models to understand emergent properties of systems

• Examples of emergent properties demonstrated in recent modelling work include: Complex responses to movement-based disease control; Counter-intuitive increases in disease following culling; and Climate-induced tipping points in macro-parasite infection risk.
• Other important areas where modelling can help to explain observed emergent properties are the maintenance of diversity and function within human gut microbial communities , and the emergence of diversity-stability-productivity relationships in ecological communities.

Developing inference methods for stochastic processes

• Development of such methods has enabled data driven risk assessment for disease incursions, the estimation of transmission rates in spatio-temporal epidemics in crop mixtures, and the joint use of genetic data on pathogens and epidemiological field observations to infer key characteristics of disease transmission.
• Recent work has also developed approaches to assess the adequacy of different components of spatio temporal models in epidemiology & ecology.

See recent publication describing a novel method for fast inference in discrete state Markov processes

Epidemiology

We have:

• developed approaches to assess the risk of between farm spread of Classical Swine Fever using data on small historic outbreaks
• produced a model based framework to assess traceability in the Scottish sheep population .
• used models to understand disease control at local scales and the dynamics and control of disease spread between farms at larger scales.
• considered the implications of climate change for disease risks from macro-parasites .
• and studied the sometimes counter-intuitive impact of surveillance and culling on wildlife populations.

Ecology

We have used models to increase understanding of a range of ecological issues including:

• inferring the spread of invasive species from observational data
• understanding genetic limits to the evolution of species range boundaries in changing environments
• modelling the growth of sandeels
• and assessing forest stand transformation using a size-structured spatial population model.

In addition, we have also used models to explore

• the maintenance of diversity and
• the emergence of diversity-stability-productivity relationships in ecological communities.

See the recent publication on the ecology of wildlife disease surveillence

Modelling microbiomes

We have developed a range of models and approaches to describe the complex dynamics and behaviours of microbiomes. Applications include:

• modelling the production of metabolites by colonic bacteria
• understanding gut bacterial community dynamics in humans
• modelling modelling methane production from ruminants which is helping to improve understanding of the underlying causes of thus major source of greenhouse gas emissions.