Social personality in sheep: Can social strategies predict individual differences in cognitive abilities, morphology features, and reproductive success?

Attention bias and novel object test in rams (Ovis aries) under intensive farming

Affective states are long lasting mood states resulting from an accumulation of experiences. The knowledge of the affective state of animals can significantly help maintain and/or increase animal welfare. The aim of the study was to recognize the affective state of 13 adult rams reared under an intensive system and to further associate their affective state with hierarchy, sociability order and maintenance and social behaviour. The affective state was estimated by exposing them to an attention bias test and two novel object tests. Individuals with negative affective states performed reduced head hanging (p = 0.014), reduced agonistic behaviour (p = 0.033), increased social proximity (p = 0.009) and received less affiliative behaviours (p = 0.006). The study estimated the affective state of the rams and indicated easily recognizable maintenance and social behaviours correlated with negative affective state. Such behaviours could increase the awareness of the animals' welfare and thus improve management practices.

Positive Aspects of Welfare in Sheep: Current Debates and Future Opportunities

The concept of positive welfare is an expansion of the traditional understanding that animal welfare is defined by minimizing stress, pain, suffering, and disease. Positive welfare shifts the animal welfare narrative from a focus on reducing negative experiences to proactively providing animals with opportunities to have positive experiences and feelings. The concept, although around for several decades, is in its infancy in terms of developing ways of assessing positive welfare on farms, especially in extensive systems, and there are challenges in the adoption of positive welfare practices and the monitoring of continuous improvement at the farm level. Using an iterative approach, this critical review aims to explore the extent to which positive welfare interventions and indicators are positioned and have been developed within the animal welfare literature for sheep. This paper critiques existing positive welfare indicators, such as choices in food and the physical environment, conspecific social synchronization, maternal bonds, intergenerational knowledge transfer, positive human-animal relationships, etc., as currently assessed by the 'good life framework'. It also reviews the characteristics of scientific measures for (positive) affective states in the current sheep literature and their potential contribution to understanding positive welfare states in sheep. In conclusion, this paper provides recommendations for future research regarding sheep welfare.

Using Real-Time Kinematic (RTK) Devices to Show a Limited Effect of Boldness and Fearfulness on Social Proximity in Sheep Grazing at Pasture

Sheep are gregarious animals that can form close inter-individual relationships. Social bonds are affected by environmental and within-animal factors, but there is limited understanding of individual factors that influence social relationships, in part due to the challenges of accurately measuring individual social proximity within a group. This study used geospatially precise RTK-GNSS localization devices (Real-Time-Kinematic Global Navigation Satellite System) to evaluate social proximity between individuals with different personality traits in small sheep flocks. First, unsupervised clustering algorithms were used to categorize 78 individual Merino sheep (from a research flock of 108 grazed together for 11 months prior) based on their behavior measured in four behavioral tests: arena, novel object, flight speed, and isolation box. Sixty-five sheep were then categorized into five cohorts of 13 individuals each (clustered into three bold, six bold/fearful, and four fearful animals per cohort). Bold/fearful animals were bold toward a novel object but fearful of a human. Sheep within a single cohort were released into a 0.70 Ha test paddock with RTK-GNSS devices attached to their backs for 3 days to monitor relative positions. All cohorts were tested sequentially over a 5-week period. Social network analyses of GNSS locational data with a distance threshold of up to 30 m for all cohorts together showed no significant effect of personality traits (P = 0.11). There were, however, some significant but inconsistent differences in distances based on personality traits within separate cohorts [i.e., cohorts 1, 3, 4 (P ≤ 0.02), cohorts 2, 5 (P ≥ 0.44)]. When GNSS locational data were analyzed with a distance threshold of up to 2 m (day 2 excluded from all cohorts due to missing values), there was a significant effect of personality traits (P = 0.01) across all cohorts combined. The bold animals showed greater distances from each other relative to their distances from fearful or bold/fearful individuals. Additionally, regardless of personality traits, the average distance between animals decreased 2.2 m over the 3 test days. Social interactions in sheep flocks may be influenced by personality traits of fearfulness and boldness, but further research with larger numbers of sheep across varying environments is needed.

Exploration of early social behaviors and social styles in relation to individual characteristics in suckling piglets

Social behavior is a key component of pig welfare on farms, but little is known on the development of social behaviors in piglets. This study aimed to explore social behaviors and identify early social styles in suckling piglets. Social behaviors of 68 piglets from 12 litters were scored continuously for 8 h per day at 21 and 42 days of age, and were included in a Hierarchical Clustering on Principal Components analysis to identify clusters of pigs with similar social styles. Social nosing represented 78% of all social interactions given. Three social styles were identified: low-solicited inactive animals (inactive), active animals (active), and highly-solicited avoiders (avoiders). Belonging to a cluster was independent of age, but was influenced by sex, with females being more represented in the ‘inactive’ cluster, and males in the ‘active’ cluster, whereas both sexes were equally represented in the ‘avoider’ cluster. Stability of piglets’ allocation to specific clusters over age was high in the ‘inactive’ (59%) and ‘active’ (65%) clusters, but low in the ‘avoider’ cluster (7%). Haptoglobin and growth rate were higher in ‘active’ than ‘inactive’ pigs, and intermediate in ‘avoiders’. Our findings suggest the existence of transient social styles in piglets, likely reflective of sexual dimorphism or health status.

Sheep's coping style can be identified by unsupervised machine learning from unlabeled data

The objective of this study was to define coping style of sheep by using unsupervised machine learning approaches. A total of 105 Norduz sheep (age 3-5 years) were subjected to a 5-minute arena test. Agglomerative Hierarchical Clustering (HCA) was performed on scores of selected principal components retained from Principal Components Analysis (PCA) on arena behaviors to identify sheep coping style. Initially, the variables retained for the PCA were determined with Bartlett's test for sphericity and Kaiser-Meyer-Olkin (KMO) measure of sample adequacy. Seven behavioral variables with KMO values greater than 0.5 were used for final PCA: the average distance to group sheep (DTG), the average distance to stimulus (DTS), the duration of locomotion (LOC), the total number of zone boundaries crossed during the test (CRS), the total number of times that tested sheep sniffed stimulus (NSS), latency to the first sniff the stimulus (LSS), and subjective scores (SCR) scored by an observer on a scale from 1 to 5 (1: extremely calm, 5: extremely restless). The first two components, which were the only ones with an eigenvalue greater than one, accounted for 70.32% of the total variation and were used for clustering analysis. Clustering tendency showed that the scores for the first two components were suitable for clustering (Hopkins' H = 0.852). Several cluster validity indexes were used to obtain aggregated results to determine the most appropriate clustering method and number of clusters. Five different clustering methods: k-means and hierarchical clustering with Ward, average, single and complete linkage were compared. Bootstrap resampling was used to evaluate the stability of a given cluster using the Jaccard coefficient. The clustering method and number of clusters corresponding to the highest rank aggregation score from the bootstrap resampling indicate that the hierarchical clustering method with average linkage and 5 clusters is the most suggested clustering method. However, Ward's algorithm identified the strongest clustering structure for hierarchical clustering, as it had the highest agglomerative coefficient value (0.98). When both Jaccard and aggregation scores are considered together, Ward's method with 3 clusters was selected as the most appropriate method. Sheep were classified into three coping styles (CS) based on HCA results as reactive (Cluster 1, n = 71), intermediate (Cluster 2, n = 22) or proactive (Cluster 3, n = 12). Coping style had significant effect on behavioral variables, DTG, DTS, LOC, CRS and NSS (P < 0.05). The individuals that have proactive coping style had the highest mean values for the variables DTG, DTS and LOC and SCR (P < 0.0001). This indicates that proactive sheep are more active then reactive sheep. The CRS, LOC and NSS mean values were higher for intermediate sheep compared to reactive sheep (P < 0.05). The NSS values were higher for intermediate sheep compare to proactive sheep (P < 0.0001). The findings of the current study show that distinct coping styles in sheep may be identified based on behaviors recorded in an arena test. The findings also revealed that sheep's coping style can be objectively identified by unsupervised machine learning from unlabeled behavioral data.

Aggressive dominance can decrease behavioral complexity on subordinates through synchronization of locomotor activities

Social environments are known to influence behavior. Moreover, within small social groups, dominant/subordinate relationships frequently emerge. Dominants can display aggressive behaviors towards subordinates and sustain priority access to resources. Herein, Japanese quail (Coturnix japonica) were used, given that they establish hierarchies through frequent aggressive interactions. We apply a combination of different mathematical tools to provide a precise quantification of the effect of social environments and the consequence of dominance at an individual level on the temporal dynamics of behavior. Main results show that subordinates performed locomotion dynamics with stronger long-range positive correlations in comparison to birds that receive few or no aggressions from conspecifics (more random dynamics). Dominant birds and their subordinates also showed a high level of synchronization in the locomotor pattern, likely emerging from the lack of environmental opportunities to engage in independent behavior. Findings suggest that dominance can potentially modulate behavioral dynamics through synchronization of locomotor activities.