The stability of social prominence and influence in a dynamic sow herd: A social network analysis approach

Impact of proximity definitions and sampling rates on social networks in pigs based on tracking using computer vision

In farm animals, social network analysis has become a popular approach to explore preferential associations. This study investigated how different spatial proximity definitions and sampling rates affect social networks based on proximity using computer vision. Video data collected over three days in 21 pens (6 pigs/pen), either enriched or barren, were analyzed using a tracking-by-detection method based on bounding boxes. Networks were constructed with five different definitions of proximity: (1) distance between centroids of bounding boxes < 50 cm, (2) occurrence of overlap of surfaces of bounding boxes, (3) surface overlap of bounding boxes > 20%, (4) a combination of (1) and (3), and (5) the harmonic mean of the distance between the two individuals. For each proximity definition, networks built with downsampled data were compared to a network built with 0.5 frames per second. The network metric degree centrality was less affected by proximity definitions compared to eigenvector centrality and clustering coefficient. To maintain high correlations with the complete network (r > 0.90), downsampling should not go beyond 1 frame every 6 min. This work shows how computer vision data can be used for social network analysis in livestock with limited space and choice of social environment, and how metrics depend on proximity definitions and sampling rates.

Preferential associations in an unstable social network: applying social network analysis to a dynamic sow herd

Preferential associations are fitness-enhancing ties between individuals, documented in a range of taxa. Despite this, research into preferential associations remains underrepresented in commercial species, particularly pigs. This study investigates the development of preferential associations in a dynamic sow herd. Preferential associations were defined as approaching a resting sow and then sitting or lying with physical contact with the selected sow, separated by < 1 m from the head or directly next to her, with interaction tolerated for > 60 s. For individual identification, each sow was marked with colored dots, stripes, or both, corresponding to their ear-tag number. Preferential associations were measured over one production cycle of 21 days. Behavioral observations took place on 7 days of the study, with 3 h of behavior per day recorded during peak activity times (08:00-09:00, 15:00-16:00, 20:00-21:00 h). Behaviors were recorded using five cameras, each positioned within the barn to provide coverage of the functional areas. The network metrics applied included in-degree centrality (received ties), out-degree centrality (initiated ties), centralization (the extent to which an individual is central within the network), clustering coefficient (a measure of tie strength), and the E-I Index (a measure of assortment by trait: parity, familiarity, and sociality). Individuals were added and removed during the study, so the centrality metrics of missing sows were weighted. To describe the structure of the network, brokerage typologies were applied. Brokerage typologies include five positions, including coordinators, gatekeepers, representatives, consultants, and liaisons. The results revealed social discrimination in assortment by connectedness even when ties were not reciprocal, and the most connected sows were significantly more likely to be approached than less connected individuals. The most connected sows had significantly higher in-degree and out-degree centrality. With the application of brokerage typologies, the results showed a relationship between connectedness and brokering type, with the most connected sows predominantly engaging in coordinating behavior. The results suggest that the motivation for discrimination in the unstable preferential association network was not founded upon bidirectional interactions. These findings highlight the complexities involved when forming social preferences and present a platform for further exploring the motivations for preferential associations among intensively farmed pigs.