Killer Whale Team

The UK project is coordinated by Prof Darren Croft at the University of Exeter, with the help of Co-Investigators Prof Michael Cant and Dr Dan Franks at the University of York.

Prof Croft is a behavioural ecologist and his research interests lie in two main questions (i) What are the mechanisms and functions that underpin the structure of animal societies? (ii) What are the evolutionary implications of this structure? To address these questions Prof Croft’s research group combines experimental and observational work on wild animal populations with controlled laboratory experiments. The research topics covered by his group are broad and include; the evolution of cooperation, life history evolution, social recognition and sexual conflict. As such they work on a wide range of study systems ranging from small fresh water fish to resident killer whales. The team use social network analysis as a tool to unravel the complex nature of how animal societies are structured. Recently they have extended the group’s research to questions of animal health and welfare and are working with the UK dairy industry to study social components of welfare and productivity in commercial dairy cattle.

I study the evolution of sociality and ask why social relationships are formed and how they are maintained. Within groups of animals, individuals differ in their tendency to interact with others and in how deeply embedded they are in their social network. Investigating these differences allows me to determine the genetic and physiological causes of sociality, as well as its impact on Darwinian fitness. My research is centred on wild or free-ranging populations with long-term datasets that permit me to quantify inter-individual differences in sociality, relatedness, survival and reproductive output.

Dr Dan Franks is a Reader in the York Centre for Complex Systems Analysis (YCCSA) at the University of York. He wears two hats. One as a Biologist, and one as a Computer Scientist.
In biology Dr Franks’ group researches questions in evolutionary and behavioural ecology. They use a variety of empirical and modelling methods to research social behaviour and life-history evolution.
In computer science his group researches the use of games for scientific discovery (gamification), and non-standard computation such as evolutionary algorithms, and biological modelling.