Recent advances in the analysis of behavioural organization and interpretation as indicators of animal welfare

Lucy Asher, Lisa M. Collins, Angel Ortiz-Pelaez, Julian A. Drewe, Christine J. Nicol, Dirk U. Pfeiffer

Abstract

While the incorporation of mathematical and engineering methods has greatly advanced in other areas of the life sciences, they have been under-utilized in the field of animal welfare. Exceptions are beginning to emerge and share a common motivation to quantify ‘hidden’ aspects in the structure of the behaviour of an individual, or group of animals. Such analyses have the potential to quantify behavioural markers of pain and stress and quantify abnormal behaviour objectively. This review seeks to explore the scope of such analytical methods as behavioural indicators of welfare. We outline four classes of analyses that can be used to quantify aspects of behavioural organization. The underlying principles, possible applications and limitations are described for: fractal analysis, temporal methods, social network analysis, and agent-based modelling and simulation. We hope to encourage further application of analyses of behavioural organization by highlighting potential applications in the assessment of animal welfare, and increasing awareness of the scope for the development of new mathematical methods in this area.

Footnotes

  • Glossary:
    Bootstrapping:
    A method for making statistical inference based on repeated randomly sampling from an actual sample.
    Bottom-up:
    A strategy for information processing derived from piecing together component parts.
    Euclidean:
    An area of mathematics relating to standard geometry based on the mathematician Euclid's axioms.
    Monte Carlo methods:
    A suite of heuristic mathematical techniques where possible random variation in all parameters is examined and can be used to assess the cause of observed effects.
    Random permutations:
    The random ordering of discrete items.
    Random walk:
    A sequence of random movements of fixed step length where each movement depends only on the direction of the previous movement.
    Top-down:
    Information processing based on decomposition of a system into component units. The opposite of bottom-up.
    • Received June 9, 2009.
    • Accepted August 5, 2009.
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