Assessing the welfare of extensively managed sheep : an evaluation of animal-based welfare indicators

The increased public interest in the welfare of animals used in food production has led to the emergence of welfare assessment schemes for a range of livestock species. There are currently over 100 million sheep in the EU which are primarily bred for milk, meat and wool production and the majority of these animals are managed extensively. The general perception of sheep in extensive systems living “natural lives” with few welfare compromises, along with the practical challenges of adequately assessing their welfare, has caused them to be largely ignored in comparison to other species. It was only relatively recently that the lack of animalbased welfare assessments for extensively kept small ruminants was recognised. Thus, the aim of this project was to evaluate potential animal-based welfare indicators for use during on-farm welfare assessments of extensively managed sheep. The current project used the Welfare Quality® 4 principles and 12 criteria as a foundation for selecting indicators for the assessment of extensively managed sheep. Following a comprehensive review of the scientific literature and a meeting attended by experts from across the EU, 16 indicators were selected for evaluation. Each principle and criteria were covered by at least one of these 16 indicators ensuring the main aspects of sheep welfare were addressed. The indicators selected for investigation could either be applied without handling or gathering the animals during an 'Assessment in the Field', or during a more thorough hands-on 'Assessment at Gather'. The reliability, feasibility and validity of some indicators (e.g. body condition scoring) are already established. However for others (e.g. Qualitative Behavioural Assessment approach), at least one of these criteria required further investigation before the indicator could be accepted. The reliability of selected measures was evaluated by assessing their repeatability and inter-observer agreement. Face validity was assumed for the indicators selected during the expert meeting, and further cross validation was performed when appropriate using additional information collected on the animal’s physical health status. During the Assessments at Gather blood samples were collected for the assessment of metabolic profiles, and faecal samples provided gastro-intestinal parasite counts. The Assessments at Gather were performed on the same 100-135 Scottish Blackface ewes across a two year period (2011-2013) on a Scottish hill farm. The Assessments at Gather occurred five times a year coinciding with key points in the ewes’ reproductive cycle: pre-mating, mid-pregnancy, late pregnancy, mid lactation and weaning. During the assessments data were collected on the ewe’s body condition, coat cleanliness, faecal soiling score, respiratory conditions, anaemia, lameness and udder condition (udders assessed during lactation only). Current stage in the reproductive cycle and seasonality were found to have significant impacts upon the long-term reliability of the following measures: body condition score, tooth loss, nasal discharge and anaemia scores (P < 0.001) with variation both within, and between years. On commercial farms older and less productive ewes tend to be removed from the flock once a year prior to mating. Of the indicators applied to the ewes during the Assessments at Gathers, tooth loss and body condition score were the best predictors for the ewe’s exclusion from the flock, predicting the future removal of a ewe from the flock 12 months in advance of the shepherd’s decision. For the Assessments in the Field, indicators which did not necessitate close contact were required. A whole-animal method (Qualitative Behavioural Assessment (QBA) was therefore particularly useful as it can be performed with minimal disturbance. Rather than quantitatively scoring the behaviour patterns of an animal the assessor focusses on how the animal interacts with their environment. This information is translated in to qualitative descriptors such as “calm” or “agitated”. Good interobserver reliability was found when three observers assessed 49 individual ewes on two occasions (W=0.77, P < 0.001). When QBA was applied 13 times to 50 individual ewes over a six-month time period (spanning late pregnancy to post-weaning) four meaningful Principal Components were identified; the first two accounted for more than half of the explained variation between sheep. The two main components were ‘General Mood’ (PC1), describing the overall affective state of the ewe, and ‘Arousal’ (PC2) reflecting energy levels. General Mood scores significantly increased in the post-lambing period compared to pre-lambing observations, and significantly increased again post-weaning (P < 0.001). Ewes were significantly experiencing significantly higher Arousal in post-lambing and post-weaning conditions compared to pre-lambing (P < 0.001), but there was no difference between post-lambing and post-weaning. During the Assessments in the Field data were also collected on: the ewe’s response to human approach, a surprise test, the ewe’s social group size, group demographics and behavioural synchrony. Ewes with lower mood scores tended to have larger distances between them and other ewes (P=0.023). The distance to which a human could approach before the ewe fled was significantly related to Arousal (P=0.05), as ewes in a higher energy state fled from the approaching human sooner than those who were in lower Arousal states. Ewes in social groups with higher numbers of ewe and lamb vocalisations tended to have lower General Mood scores (P=0.014), and lower Arousal scores (P < 0.001) than those in smaller groups. Indicators which met the conditions of feasibility, reliability and validity (for example, those reported above) proved to be suitable for use when assessing the welfare of extensively managed sheep. The effect of time on the reliability of the indicators applied during the assessments have important implications for understanding temporary fluctuations in the animal’s welfare caused by either internal (reproductive state) or external (environmental) factors. These fluctuations may not be representative of a farm’s overall welfare levels in the long term and therefore further careful consideration of the most appropriate time to apply the selected indicators is required.