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

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.

Development of a new welfare assessment protocol for practical application in long-term dog shelters

In many European shelters, dogs may spend many years confined. A poor environment and inappropriate management may lead to a low quality of life. The absence of harmonised European regulatory frameworks defining the minimum requirements for shelter facilities makes the definition of welfare standards for kennelled dogs challenging. Here, a new protocol was developed and tested to help identify the main welfare issues for shelter dogs. Twenty-six indicators were identified including management, resource and animal based measures. Accuracy and interobserver reliability were checked between four assessors. The protocol was applied in 29 shelters (n=1308 dogs) in six European countries. Overall prevalence of poor health conditions was below 10%. Test-retest reliability and validity of the protocol were investigated with encouraging results. A logistic regression was carried out to assess the potential of the protocol as a tool to identify welfare hazards in shelter environments. Inappropriate space allowance, for example, was found to be a risk factor potentially affecting the animal's cleanliness, skin condition and body condition. The protocol was designed to be concise and easy to implement. Systematic data collection could help identify welfare problems that are likely to arise in certain shelter designs and thus determine improvement in animal care standards.