Iceberg Indicators for Animal Welfare in Rural Sheep Farms Using the Five Domains Model Approach

SIMPLE SUMMARY: Animal welfare is difficult to quantify, especially among farmers, in extensive rural sheep farms where there is a low level of animal interaction and a lack of technology. In this study, we searched for iceberg indicators of animal welfare using the Five Domains Model approach, and studied the relationship among sheep flight distance, sheep handling training and job satisfaction in extensive rural sheep systems. A structured survey was used to obtain socio-demographical, job satisfaction and sheep handling training data. A full animal welfare evaluation was performed on all farms; furthermore, a health status examination was also made in which blood and stool samples were taken. Four iceberg indicators were found with the potential to predict overall animal welfare scores on farms, and one to study state of mind in extensive rural sheep systems, as well as interactions among job satisfaction, training in sheep handling and sheep mind state. ABSTRACT: Animal welfare for sheep in extensive rural farms is difficult to quantify among rural farmers due to several factors, including the lack of technology and the low level of interaction they have with the animals. The purpose of this study was to search for animal-based iceberg indicators using the Five Domains Model approach and study the relationship between sheep reactive behavior (flight distance), sheep handling training and farmers job satisfaction. Thirteen extensive commercial dual-purpose sheep farms (n = 520 animals) were evaluated in Marulanda, Caldas (Colombia, South America). On-farm Animal Welfare Indicators (AWIN) were assessed using an adapted version of this protocol. Socio-demographic characteristics, sheep handling training and job satisfaction were evaluated using a structured interview. Blood and stool samples were taken to determine Fecal Egg Count and Packed Cell Volume. Bivariate regression models were used to find animal-based indicators that predicted Nutrition, Ambience, Health and Behavior welfare domains, and a Qualitative Behavior Analysis was used for mind state domain analysis. Body condition score (BCS) (p = 0.001), fleece cleanliness (p = 0.03), FAMACHA© Score (p = 0.05), and flight distance in meters (p = 0.19) were found to be indicators, and were useful for predicting overall welfare assessment (R2 = 0.85) on theses farms. Regarding mind welfare domain, Qualitative Behavioral Assessment found two principal components (PC) that explained 82% and 67% of the variance, and described emotional valence and energy levels of sheep, respectively. Sheep handling training (β = −8.75, p = 0.004) and job satisfaction (β = −7.5, p = 0.013) had a negative association with the average flock flight distance. Spearman’s rank correlations were significant (p < 0.001) between Fecal Egg Count, Packed Cell Volume, FAMACHA© Score (FS), Body Weight (BW) and, BCS. The strongest association was observed between Packed Cell Volume (PCV) and Fecal Egg Count (FEC) (r = −0.43), also FS was correlated with PCV (r = −0.28) and FEC (r = 0.21), and BCS was correlated with weight (r = 0.32). We suggest that these animal-based indicators could be useful as iceberg indicators for extensive sheep production systems and may set the ground for more research in small extensive sheep farms to develop strategies to find welfare problems and solutions.