Adam’s background is in evolutionary ecology. He carried out his PhD at the University of Edinburgh, investigating interactions between ageing and parasitic nematode infections in the wild population of Soay sheep living in the remote St Kilda archipelago.

Sick of sheep and worms (or so he thought!), Adam then took a postdoctoral position at Sheffield where he worked largely on how environmental variation affected the health and fitness of pre-industrial Finns, but also found time to delve a little into the parasitology of Asian elephants in Myanmar.

Refreshed, he returned to the Soay sheep during a 3-year Research Fellowship at the University of Stirling, working on variation in immune responses and tolerance to infection, and the links between reproductive effort in females and resistance to worms.

Having seen the light, and with the remit of bringing insight and statistical techniques from ecology into livestock disease, Adam began his current Fellowship at Moredun in April 2018.

The over-arching aim of Adam’s research is to study variation between individuals in responses to infection. Rather than treating animals as a homogeneous flock or herd, he aims to determine how much variation there is between animals and identify the drivers of this variation. Why do some animals mount effective responses to worm infections? Why do two animals with the same infection have very different health outcomes? Understanding this variation can then be exploited to devise strategies for the management of disease, including breeding and management of the environment.

Currently, Adam’s main focus is on helminth parasites of sheep (gastro-intestinal nematodes) and cattle (liver fluke). He aims to collaborate with immunologists and parasitologists with more expertise in the lab, and producers and commercial companies with more knowledge of animal production. Adam applies approaches and statistical techniques more commonly used in other fields to address his research questions – such approaches are not used as often in livestock disease, but are ideal for dealing with messy data sets.

A big aim moving forward is to explore how data that are routinely collected, such as on the farm or at the abattoir, can be exploited for the study of livestock disease.