Abstract
Interaction networks are studied by a wide variety of researchers and are known to be vital to understanding important processes including disease spread, information transmission, and food-web regulation. Thus, they are important for understanding the ecological pressures imposed on animals and their environments and, in the case of disease transmission, important for developing preventative methods for conserving wildlife. Sampling is necessary because animal social networks are generally large. For example, although a feral cat may come into contact with only thirty other cats, some of these contacts will be connected to individuals outside the original group of thirty; so the social network for UK feral cats may easily involve thousands of individuals. However, there is no quantitative methodology underpinning the collection of ecological network data. This can result in social network data being unreliable. This project will take an interdisciplinary approach to solving the problem by building state-of-the-art computer models to simulate and test different network sampling protocols and to define a robust quantitative methodology for data collection.
United Kingdom