Abstract

Whilst the incorporation of mathematical and engineering methods has greatly advanced in other areas of the life sciences, they have been under-utilised in the field of animal welfare. Exceptions are beginning to emerge and share a common motivation to quantify some ‘hidden’ aspect in the structure of the behaviour of an individual, or group of animals. Such analyses have the potential to quantify behavioural markers of pain, disease and stress in addition to objective quantification of abnormal behaviour. I will explore the scope of such analytical methods as behavioural indicators of welfare. Four classes of analyses that can be used to quantify aspects of behavioural organisation will be introduced: fractal analysis, Markov chains, social network analysis and agent-based modelling and simulation. The overview will include mathematical principles, origins, animal welfare applications and advantages and disadvantages. The hope is to encourage further application behavioural organisation methodology to animal welfare by providing an intuitive understanding of a suite of potential welfare indicators.