Our research group uses quantitative approaches to study the evolution and adaptive value of animal behaviour in natural contexts. We are interested in how behaviour has evolved, what the adaptive value of behaviour is, and what the mechanisms that underlie behaviour are.
Using many different taxa, we seek to understand how social interactions are modified by current context, how animals perceive and process social cues, and how environments – both social and physical – change and are changed by behaviour. We take a broad approach, combining studies of proximate neurobiological and genetic mechanisms, with analyses of the physics of interactions, up to broad evolutionary and ecological studies of social influence and behaviour.
Although we are traditional behavioural ecologists at heart, we borrow computational approaches developed for model laboratory systems like Drosophila and Zebrafish, and employ them in settings where animal behaviour has evolved – Lake Tanganyika, the Mediterranean Sea, coral reefs, and tropical rainforests. Using techniques like computer vision and machine learning, automated tracking of behaviour, and 3D reconstruction of environments, we aim for a quantitative assessment of the expression and value of behaviour in the places it naturally occurs.
Our research is focused in three main areas:
The structure and evolution of behaviour
When complex social structures evolve, what needs to change in terms of the behaviour animals express? Do social animals need to do more behaviour? Must a richer or more complex behavioural repertoire evolve to support complex social organisations? Are we as human observers able to detect the potentially subtle ways that behaviour may differ in what appear to be similar contexts? And can machine learning approaches help us in this endeavour?
This work is focused on the Lake Tanganyika cichlid radiation, capitalizing on the incredible diversity in behaviour within the Lamprolgines.
Living in groups potentially imposes cognitive challenges that solitary animals do not face. Memory of past interactions, inference of unknown relationships, and recognition of individuals may be required to maintain functional social groups. Using a blend of virtual and traditional approaches, we try to understand the range of cognitive abilities that have evolved along with social living, along with how these differences may be encoded in the brain itself.
Mechanisms of behavioural diversity
Behaviour is an ephemeral phenomenon, and to get a handle on how behaviour evolves we must study the structures that produce it. To that end, we focus on understanding the diversity of neuroanatomy and brain activity in species and individuals that vary in their social behaviour. We have successfully created a link between field observations of behaviour in natural settings and analyses of brain gene activity in the lab.
We also have a keen interest in exploring the links between science, art, and architecture:
“We shape our buildings; thereafter they shape us” – Winston Churchill
Animals affect, and are affected by, their environments. This simple relationship means that it is difficult to assess how removing animals from their natural contexts might influence their behavioural expression. We aim to quantify the natural structures in which animals live and interact, and manipulate attributes of these structures to experimentally test their effects. See ART for more information on these and related projects.
If you’re interested in finding out about Alex Jordan, more information is here.