Current Projects
Individual-level interactions
A main interest of mine is in the evolution of behaviours related to the generation, acquisition and processing of socially derived information. We are currently investigating processes of aggression and cooperation using a combination of theoretical and empirical methods. I am increasingly interested in linking animal behaviour and interactions at individual-levels to population level patterns and processes, such as specialism/generalism, niche width, community structure, population biology and ultimately conservation. In this context I have worked previously on vulture foraging in light of their conservation, marine turtle nesting patterns and population consequences, and predation driven colony fragmentation in penguins. We are continuing our research on vulture foraging behaviour in Swaziland in collaboration with Prof Ara Monadjem.
Variation in the framerate of visual perception
Some animals see the world faster than others. That is, the frame rate of vision varies considerably across species. This is related to how fast they have to move in the world and therefore has important functional and ecological consequences. Humans on average see the world at 36 “frames per second”, but this trait varies substantially between individuals and we know nothing about how normal variation might affect performance. This phenomenon can be measured using techniques such as Critical Flicker Fusion threshold, which measures the frequency at which a flickering stimulus can no longer be detected as such. We aim to develop robust psychophysical methods to reliably measure those differences in field conditions outside the laboratory and quantify the magnitude of variation within and among individuals. We will assess the real-world consequences of this variation in an arena where human perceptual abilities are tested to the limits and where small individual differences may make the difference between success and failure, namely in high-speed sports. This collaborative work is being undertaken by PhD candidate Clinton Haarlem with a co-supervisory team comprised of Dr Andrew Jackson (zoology), Dr Kevin Mitchell (genetics) and Prof Redmond O'Connell (psychology).
SIAR - Stable Isotope Analysis in R.
This on-going project focuses primarily on the development of computational and statistical models for application to stable isotope ecology. The main output so far is the development of a Bayesian mixing model for inferring diet from stable isotope analysis of consumer and source tissues. This project also includes the new SIBER models for exploring niche width in isotopic d-space.
Find out more about SIAR - Stable Isotope Analysis in R.