Biased social learning and directed information transfer: a comparative approach

‘Social learning’ (learning from others) occurs across the animal kingdom and can affect not only individual fitness but also the patterns of information transmission through entire social groups. An individual’s ability to learn from others is determined not only by its own behaviour but by the behaviours of those in possession of the knowledge (the ‘demonstrator’) and by the structure of the underlying social network. In this thesis, I use theoretical and empirical approaches to investigate the physical, social and behavioural factors influencing social transmission within complex, spatially realistic environments. I find that individual variation in space use and tendency to transmit and receive information influence information transmission patterns in an agent-based model of social insect communication (Chapter 2). I also show that the characteristics of social bonds connecting individuals within the larger social network determine patterns of learning in zebra finches, which show biases towards learning from aggressors and mates (Chapter 3). Finally, a limitation of the human research is restrictive laboratory environments that offer little ecological validity and make generalisations across the human / non-human divide difficult. I tackle this limitation through the development (Chapter 4) and employment (Chapter 5) of novel, three-dimensional virtual research environments for studying human social learning, where I demonstrate that people are biased towards learning asocially (independently) and towards demonstrators greater in number and success rates. In Chapter 6, I discuss how individual variation in the aforementioned behaviours appears to play a particularly important role in determining the pathways of social transmission at the population level and, in some cases, can result in the existence of ‘keystone’ information transmitters, which have a disproportionate influence over the behaviours of others. I discuss ideas for future research and the potential application of these findings outside of behavioural ecology and evolution in fields including conservation, epidemiology and education.