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REVIEW article

Front. Vet. Sci., 12 August 2022
Sec. Animal Behavior and Welfare
This article is part of the Research Topic Using Methods and Approaches from Behavioral Ecology to Address Issues in Applied Animal Sciences View all 4 articles

Social behavior in farm animals: Applying fundamental theory to improve animal welfare

  • 1Animal Behaviour and Welfare, Animal and Veterinary Sciences Department, Scotland's Rural College (SRUC), Edinburgh, United Kingdom
  • 2Institute for Global Food Security, School of Biological Sciences, Queen's University, Belfast, United Kingdom

A fundamental understanding of behavior is essential to improving the welfare of billions of farm animals around the world. Despite living in an environment managed by humans, farm animals are still capable of making important behavioral decisions that influence welfare. In this review, we focus on social interactions as perhaps the most dynamic and challenging aspects of the lives of farm animals. Social stress is a leading welfare concern in livestock, and substantial variation in social behavior is seen at the individual and group level. Here, we consider how a fundamental understanding of social behavior can be used to: (i) understand agonistic and affiliative interactions in farm animals; (ii) identify how artificial environments influence social behavior and impact welfare; and (iii) provide insights into the mechanisms and development of social behavior. We conclude by highlighting opportunities to build on previous work and suggest potential fundamental hypotheses of applied relevance. Key areas for further research could include identifying the welfare benefits of socio–positive interactions, the potential impacts of disrupting important social bonds, and the role of skill in allowing farm animals to navigate competitive and positive social interactions. Such studies should provide insights to improve the welfare of farm animals, while also being applicable to other contexts, such as zoos and laboratories.

Introduction

A fundamental understanding of behavior is essential for improving the welfare of billions of farm animals globally. Although artificial environments release animals from natural selection pressures, fundamental ethological principles remain relevant as farm animals carry an “evolutionary legacy” that influences behavior [(1); see also (25)]. For example, comparative studies have found that the behavioral repertoire of many farmed species has been qualitatively preserved since domestication [(6); e.g., chickens: (3); pigs: (7, 8)]. On the other hand, domestication has also quantitatively modified behavior in many farmed species by altering response thresholds (2, 9). These behavioral changes may be brought about intentionally through artificial selection, or inadvertently due to correlations between behavior and production-relevant traits (9). Although the process of domestication involves adaptation to captivity and management by humans, some behaviors that once enhanced fitness under natural conditions may compromise welfare in farm environments. For example, while a life in captivity releases animals from the need to find food and avoid predators, it may create additional challenges by housing animals at high population densities or in groups with an unnatural social structure (10). As a result, the behavioral strategies that allowed animals to navigate their social environment under natural conditions may be constrained, or no longer beneficial, in captivity (2, 10). Understanding the evolutionary origins and ontogeny of behavior, and how behavior is altered or constrained by the farm environment, is therefore central to improving welfare (1, 4, 5).

Although farm animals may not be able to control or modify their environment, they are still capable of making important behavioral decisions that influence their welfare (2, 10). Decision making may require overcoming the challenges of recognizing social companions, remembering previous interactions and attending to social cues (11). While farm animals have been shown to discriminate between conspecifics (12), how they cope with other challenges, such as recognizing their position in a dominance hierarchy or estimating the fighting ability (resource holding potential, RHP) of competitors, is not well understood. Moreover, farm social environments may exert additional challenges beyond those experienced by animals' wild ancestors [e.g., by housing animals in groups of the same sex, age and RHP, or in such large groups that individual discrimination is impossible; e.g., chickens (13), pigs (14)]. This impacts welfare as animals may compete for longer to establish new dominance relationships, and subordinate individuals are offered limited opportunities to escape. Indeed, acute and chronic social stress of farmed animals is a leading welfare concern (15, 16). Mitigating social stress therefore requires an understanding of how the farm social environment differs from the ancestral state, the social challenges associated with artificial environments, and how these challenges are overcome (1, 2, 12).

Farm animal systems have also been used to address fundamental questions regarding behavioral control and development, offering opportunities for longitudinal studies at large sample sizes with replication, and with a high degree of environmental control that may be difficult to achieve with wild animals. Studies of farm animals have contributed to our fundamental understanding of various aspects of animal behavior, including parent–offspring conflict (4, 7, 8, 17), signaling (1820), foraging decisions (3, 2125), and social learning (2628). These studies illustrate how applying fundamental ethological principles to farm animals provides insights into the mechanisms underlying behavior, with findings being of relevance to wild animals but often having implications for the management and welfare of captive animals too (4, 7, 29). For example, both fundamental and applied ethologists share the common goal of understanding how and why individuals vary in their social behavior. Factors including age, sex, personality, cognitive ability, affective state, and previous experience may interact to generate inter-individual variation, influencing wild and farm animal behavior and the efficacy of welfare interventions (3032). In particular, social skills [e.g., appropriately giving and interpreting social signals, performing behavioral responses appropriate to a given situation, responding to the behavior of conspecifics; (33, 34)] may play an important role in mediating social interactions in livestock. These skills may contribute to social competence by allowing individuals to optimize their social behavior across contexts (35). The development of social competence and skill is a key topic of interest in animal behavior research, from both applied and fundamental perspectives (34, 35). Studies of livestock not only lead to welfare benefits but also play an important part in improving our understanding of the control, development, and function of social skills by providing opportunities for large scale, carefully controlled experiments grounded in fundamental behavioral theory.

In this review, we highlight opportunities to build on existing work, where further integration of fundamental behavioral theory may benefit the study of farm animal welfare. As social interactions represent perhaps the most dynamic and challenging aspects of the lives of farm animals, we focus on agonistic and socio–positive interactions, and suggest potential fundamental hypotheses of applied relevance. While we focus primarily on farm animals, enhancing our fundamental understanding of social behavior may also provide insights to improve the welfare of managed animals in other captive settings, such as zoos and laboratories (36, 37).

Agonistic interactions

Agonistic interactions serve an important function by influencing access to fitness-enhancing resources. In many animal societies, the outcome of these interactions results in relatively stable dominance relationships that reduce the need for frequent and costly aggressive interactions (38). Due to their ancestral socio–ecology, agonistic behavior and dominance relationships remain major features of the social lives of farm animals, even when the need to compete for resources is reduced. For example, domestic pigs, and to a lesser extent other livestock species, retain the motivation to establish dominance and will do so both in the absence of resources to compete over, or in the presence of adequate resources for all (3941). However, in the context of the artificial farm environment, welfare issues arise if aggression is severe and/or persists in the long term. Aggression is a widespread problem in pig farming, and is associated with increased stress (42, 43) and injury risk (44), and reduced immune function (45). In turn, these welfare impacts have consequences for farm profitability and sustainability by compromising growth rates (46) and feed use efficiency (46, 47). Managing aggression in pigs is therefore of considerable research interest, with a wealth of empirical studies quantifying variation in aggressive behavior within and between groups [e.g., (41, 44, 48)]. Most experimental work to date has focused on the role of housing conditions and group size on aggression [e.g., (15, 49, 50)], and comparatively little is known about the fundamental drivers of the observed variation in aggressive behavior (2). Our research group has used predictions from game theory to better understand contest behavior and decision making in pigs, with the goal of improving welfare and providing fundamental insights into the mechanisms and development of contest behavior more widely.

A game theoretical approach to studying competitive interactions

Insights from behavioral ecology may enhance our understanding of aggressive behavior in farm animals. In particular, game theory models have been widely applied to explain the evolution of contest behavior in wild species. Early game theory models sought to explain the evolution of contest behavior by comparing the relative fitness payoffs of aggressive and non-aggressive behavioral strategies, and how these strategies influence contest outcomes (51). Initial models set the scene for more realistic game theory models that considered asymmetries between contestants and the costs and benefits of obtaining information during contests (52). During a contest, individuals may gather information on the value of the resource being disputed (53), and their likelihood of winning based on factors such as size, skill, or weaponry [RHP; (52, 54)]. Contestants may also gather information on the RHP of their opponent (52). While gathering this information is likely to reduce uncertainty and allow individuals to only engage in contests that they are likely to win, it also carries costs (55). Selection may therefore favor the adoption of assessment strategies that dictate the information sources that individuals use in deciding when to escalate a contest, and when to withdraw (52). Several candidate models have been proposed, including: (i) resource-only assessment strategies, where decisions to withdraw are based on the value that each rival places on the contested resource (53); (ii) self-assessment strategies, where individuals rely on information about their own RHP and losers withdraw once their individual cost-bearing threshold is exceeded [e.g., war-of-attrition models, (56, 57); cumulative assessment model, (58)]; (iii) opponent-only assessment strategies, where individuals base their decision to withdraw on opponent RHP independently of their own RHP or fighting ability (52); and (iv) mutual assessment strategies, where individuals gather information regarding their own RHP relative to their opponent, and losers withdraw once they establish that they are the weaker rival (59). To distinguish between these potential models, empirical studies analyze how the costs of competitive interactions differ according to RHP of the defeated and victorious opponent (52). A recent meta-analysis determined that self-assessment strategies appear to be more common overall (60), while some studies provide robust evidence for mutual assessment [e.g., dragonflies Diastatops obscura (61); cuttlefish Sepia apama (62)]. However, most studies find no strong support for any single assessment strategy [e.g., the freshwater crustacean Aegla longirostri (63)], suggesting that they may not be mutually exclusive and instead represent variation along a continuum (64, 65). While the optimal assessment strategy is likely to differ according to ecology and life history (60), assessment strategies may also vary within species if different information is available to different opponents (52, 65). Furthermore, individuals may alter their assessment strategy over their lifetime, or even over a single contest (6569).

Several factors may explain individual variation in contest behavior and assessment strategies. In some species, males and females differ in their contest behavior [convict cichlid Amatitlania nigrofasciata (70); jumping spider Phidippus clarus (71); brown anole Anolis sagrei (72)], and while the underlying mechanisms are not always clear, differences in life history may influence the cost of defeat and individuals' assessment of RHP and resource value [see (71)]. Motivation to engage in fights may also vary as individuals age: for example, older individuals may increase investment in contests that maximize their current reproductive opportunities, while younger individuals may prioritize the future survival over the current reproductive attempt [(73); but see (74)]. Age-related effects may also influence RHP through changes in body size, condition, or morphology (75), and over time, contest experience may allow individuals to develop fighting skills (33, 34). The outcomes of prior contests can generate winner and loser effects, whereby victories increase the probability of winning in subsequent contests, and defeat increases the probability of losing in future without directly affecting fighting ability (74, 7678). Furthermore, consistent inter-individual variation in behavior, comprising traits such as boldness and aggressiveness, are likely to have an important influence on contest behavior and outcomes (79). Other factors, including affective state and cognitive ability, are also likely to contribute to individual variation in decision making during contests (80, 81). Affective state comprises short-term emotions and longer-term moods that influence responses to potentially rewarding or punishing stimuli (82). Specifically, an animal's affective state determines how stimuli in the environment are appraised based on prior experience, and is therefore likely to play a central role in contest behavior and decision making (81). Though studied in applied ethology as an indicator of welfare, the role of affective state has received little attention from behavioral ecologists and is yet to be formally integrated into contest theory (81). Likewise, the role of cognition in influencing contest dynamics and the development of fighting skills is an important avenue for future research (80, 83). Cognitive processes including perception, categorization, learning, and memory are vital to assessment and decision making and may form an important component of RHP (80, 83, 84). Several factors including diet, environmental enrichment, developmental stress, and personality may affect individual cognitive performance, and therefore decision making during contests (80, 85, 86). The effect of the social environment on cognitive development is a key area of interest in livestock studies (8791), and these systems provide opportunities to design experiments investigating how social experience shapes assessment strategies and information use during contests (80).

Applying game theory to improve farm animal welfare

To illustrate how a game theoretic approach can be applied to examining agonistic interactions in farm animals, we draw on previous work investigating contest behavior and decision making in pigs. Substantial variation in aggression persists at an individual and group level, associated with the establishment of dominance relationships between unfamiliar pigs and in competition for resources between familiar individuals (41, 44, 48). Identifying the mechanisms underlying this variation is the focus of considerable research effort. Aggression in pigs has a heritable genetic component [e.g., (9295)], but is also influenced by social experience (40, 96, 97). Along with others (98), recent work from our group has used a game theoretical approach to explain variation in contest behavior in pigs, with a view to minimizing the costs of agonistic encounters.

Enabling litters to mix prior to weaning (termed socialization) allows pigs to resolve later life dominance disputes more quickly and at a lower cost, by increasing investment in display behavior rather than escalated fighting (40, 96). Allowing piglets to interact with a greater diversity of social companions from a young age may facilitate the development of later life social skills and assessment abilities, through activities such as play fighting (69, 99). Interestingly, the findings of these studies suggest that the effects of play fighting experience on contest outcomes differed between males and females, possibly due to sex differences in sociality and the costs of contests in the wild. While male piglets demonstrated more play fighting behavior than females (69, 100), play fighting experience only increased the probability of winning in contests between females, suggesting that play fighting may not prepare males for adult conflict (97). Early life socialization and play fighting experience may also determine the assessment strategy that pigs adopt during contests. Specifically, when pigs with socialization experience later engaged in a dyadic contest with an unfamiliar opponent, losers of lower RHP engaged in longer and more costly contests against stronger opponents (40, 97). This effect is consistent with a form of mutual assessment, albeit in the opposite direction to the initial predictions of mutual assessment models [which predict a negative relationship between winner RHP and fight duration (40)]. Despite being counter-intuitive, in some cases it may be beneficial for small individuals to engage in contests with larger opponents. For example, smaller individuals may be motivated to engage in fights if RHP is not the sole predictor of contest outcome [a “Napoleon strategy” (101, 102)], or if low-RHP individuals have few alternative options by which to gain resources [a desperado effect; (103)]. In this case, it implies that early life social experience allows pigs to develop higher confidence in their own RHP (97), possibly through improving assessment abilities (40). The effect of early life experiences on assessment strategies was further supported when subjects were matched against an opponent of similar play-fighting experience; pigs in dyads with more play-fighting experience appear to employ a self-assessment strategy, while those in dyads with less play-fighting experience showed no clear assessment strategy (104). Early life social experience also appears to influence the development of aggression as socialized piglets, particularly females, were quicker to attack a smaller opponent (69). Taken together, these findings suggest that experience of play fighting allows female pigs to signal their motivation to engage in a contest and thereafter resolve disputes quickly and with fewer costs. In contrast, it may be that males are less inclined to initiate aggression due to the higher costs associated with male-male contests in the wild (69). It is noteworthy that, in the specific and ecologically relevant context of a dyadic contest (as compared to reformation of the entire social group which is rarely seen in the wild), immature male domestic pigs show aggression that is more prolonged and 3.7 times more damaging than between females (68). Consequently, the legacy of male–male conflict in the wild may still be relevant to male domestic pigs and lead to their reluctance to rush into escalated fights. At least, this appears to be the case in these studies of entire male pigs: In many countries, pigs are still routinely castrated and while this appears to reduce overall aggression (105, 106), the most in-depth studies of contest dynamics in male pigs to date have focused on uncastrated males. Overall, these studies suggest that the welfare of domestic pigs is likely to be improved by management systems that promote early life social experience and reduce contest costs, but primarily in females. In addition to play fighting, experience of prior contests is also important in determining assessment strategy. We showed that naive pigs adopt a self-assessment strategy in their first contest, and a mutual assessment strategy in subsequent contests (68). However, after intensive fighting experience, individuals revert to a self-assessment strategy. This suggests that while previous fighting experience is useful in developing mutual assessment, individuals rely on estimates of their own RHP if this information is sufficiently reliable or the costs of obtaining information about the opponent are too high (68).

Game theory predicts the emergence of variation in aggressiveness which may be predictable over time and form a component of personality (79). In agonistic contests, aggressiveness may contribute to RHP and provide information to be utilized during assessment (79, 107). In line with other studies (108, 109), Camerlink et al. (107) found that aggressiveness in pigs did not predict contest outcome or the probability that a contest would escalate to a fight, but more aggressive opponents were likely to initiate the first attack. Consequently, aggressive individuals were more likely to win contests that did not escalate to a fight (107), suggesting that aggression may act as an honest “signal of intent” rather than a component of RHP. Aggressiveness also affects other aspects of contest behavior in pigs (110). Among the winners of contests, less aggressive winners spent more time in the pre-escalation phase of a contest compared to more aggressive winners, and showed fewer agonistic behaviors following their opponent's retreat. Failure to invest in pre-escalation assessment likely leads to unnecessary escalation whilst excessive aggression toward a defeated opponent likely contributes to the welfare issues associated with contests. However, in subsequent contests, winner–loser effects appeared to have a stronger influence than aggressiveness on the initiation of agonistic behavior, suggesting that both more- and less-aggressive pigs integrate past experience during contest decision making (78). Taken together, these findings suggest that management or breeding approaches which reduce aggressiveness would be expected to benefit welfare without preventing the effective establishment of dominance relationships, or the ability of individuals to learn from previous contest experience.

Other personality traits, such as boldness and impulsivity, along with factors such as cognitive ability and affective state, may be important in farm animal contests (7981). For example, bold individuals may be more willing to take risks that help them to win fights (79). Similarly, more impulsive individuals may be more likely to initiate fights, potentially influencing contest outcome (84). Aspects of personality, cognition, and affective state are widely studied in livestock species, and have been shown to vary between the individuals (85, 111113). Currently, the importance of personality, cognition and affective state in determining information use and RHP during agonistic interactions is not well understood [but see (84) and (108)]. Future work in this area has the potential to create new understanding of the fundamental determinants of contest behavior and improve welfare in pigs by identifying how individual characteristics influence assessment strategies and dominance. This knowledge could be applied to minimize the cost of agonistic interactions, by informing optimal group composition or facilitating the development of social skills. To date, the majority of game theoretic studies in farm systems have focused on pigs and fowl [e.g., (114)], with all research on contest assessment strategies in domesticated species focusing on pigs. Although aggression in other livestock species is less severe, studies of a broader range of species may provide insights into the generality of the proximate mechanisms underlying agonistic behavior, and their welfare implications for animals kept in captivity.

Positive social interactions

In addition to competitive interactions, positive interactions also form part of an animal's “social world.” Positive interactions with conspecifics have been shown to be beneficial in a range of social species (11, 115). For example, studies of non-human primates (116118), cetaceans (119121), and horses (122) demonstrate that individuals with more and/or stronger affiliative bonds benefit from enhanced survival or reproductive success in the wild. Precisely how social bonds increase fitness varies depending on the socio–ecology of the species in question. While social bonds are often formed between close kin, bonds between non-relatives also occur in some animal societies (123) and may be associated with fitness benefits [e.g., feral horses (122); vampire bats (124); bottlenose dolphins (125); greater ani (126); Assamese macaques (127); house mice (128)]. Farm animals may also be motivated to form and maintain relationships with specific social companions, if these relationships are beneficial (30). For example, some farmed species may form social relationships if these served an important function in their pre-domesticated evolutionary history, and/or because they continue to derive benefits from these interactions in a captive setting. Positive social interactions have the potential to enhance welfare, but have received comparatively less research attention than negative social interactions, such as aggression (30, 129).

While many farm animals appear to benefit from positive interactions with conspecifics [see (30) for a review], whether and how individuals benefit from interactions with specific social companions is less well studied. The mother–offspring bond often has an important influence on offspring health and welfare in a wide range of species, particularly in mammals (11, 115), and understandably, mother–offspring bonds have been a strong focus for farm animal research. Studies in cattle, for example, have shown that cows are highly motivated to return to their calf after a period of separation (130, 131), and that access to the dam has positive effects on calf social development [(132), see also (133, 134)]. This suggests that maternal contact in farm animals informs the development of social behavior, and raises the possibility that the early weaning age associated with many livestock systems may constrain positive behavioral development. Access to social companions, particularly the dam, influences the response of young farm animals to stressful or challenging events [e.g., calves (135137); goats (138)]; and in cattle, familiar social companions provide more effective social support than unfamiliar conspecifics (139, 140). However, the importance of individualized social relationships beyond the mother-offspring bond has received comparatively less research attention. Within social groups, preferential associations have been observed in cattle (141, 142) and goats (143) and to a lesser extent in pigs (144146) and sheep (147). Some species also engage in behaviors such as allogrooming [e.g., cattle (142)] and social nosing [e.g., pigs (148)]. The exact function of these behaviors in farm animals is not fully understood, but current evidence suggests that they may provide various benefits to actors and/or recipients [reviewed in (30, 129, 149)]. For example, it has been suggested that social grooming may play a role in maintaining dominance relationships and social cohesion in cattle (150), and reduce social tension in competitive situations (142). While allogrooming and similar behaviors in farm animals are often interpreted as affiliative, the extent to which they represent a reciprocal or preferential social relationship is unclear (142). Further work investigating whether farm animals form socio–positive relationships with particular social companions, how these relationships are formed and maintained, and how they influence welfare, would be very valuable (30). It may be that the apparent welfare benefits that farm animals derive from socio–positive interactions are a legacy of the drivers that enhanced fitness in these species' pre-domesticated evolutionary past. To this end, studying the functions of socio–positive interactions in closely-related wild species may yield valuable insights as to why livestock may be motivated to maintain these relationships in captivity.

Few empirical studies have investigated how social relationships are initially formed in non-human animals (11). Not all individuals form preferential relationships to the same extent, and likewise, positive social interactions may benefit individuals in different ways. These differences can arise for several reasons. Firstly, animals may prefer to associate with familiar individuals, as seen in cattle and pigs (151, 152). Kin-based associations (e.g., between sisters) have also been identified in closely-related members of wild species [e.g., collared peccary Pecari tajacu (153); wild boar Sus scrofa (154); European bison Bison bonasus (155)], and many farm animals form preferential relationships with related and unrelated individuals [reviewed in (129)]. In this way, the “unnatural” regrouping of unfamiliar animals on farms may result in separation of preferred social companions, creating welfare problems in addition to those associated with regrouping aggression. Sex differences may also play an important role; in many species, the philopatric sex invests in social relationships to a greater extent, as these relationships may be of greater fitness relevance [e.g., (156159)]. Few studies have investigated whether male and female farm animals differ in their tendency to form socio-positive relationships, and how these differences may be explained in terms of their ancestral ecology. Further research in this area would help to identify and explain individual variation in behavior in captivity. The benefits and nature of social bonding may also vary with age. Longitudinal studies in rhesus macaques (Macaca mulatta), for example, have shown that social relationships appear to be closely tied to survival, particularly for younger individuals [(160); see also (161)]. How and why individuals' social relationships vary with age is not fully understood but may provide insights that aid our understanding of the social structure of farm animals. Few studies have investigated age effects on social associations in farm animals, although reproductive status appears to influence associations in female cattle and sheep [possibly driven by offspring behavior (162, 163)]. In this case too, an understanding of the function and evolutionary history of socio–positive relationships in ancestral species would be useful to determine the importance of these interactions in livestock across the life course.

Finally, individual differences in social behavior, underpinned by variation in personality, previous experience and decision making, may affect the formation of social relationships. The role of personality in relationship formation has been studied in other species [e.g., (164167)], providing some evidence that individuals may form preferential associations or relationships based on homophily in personality. How personality specifically influences social relationship formation has yet to be tested in farm animals, although some studies find links between personality measures and general sociality or social motivation [e.g., (168)]. In the field of animal behavior more widely, there is growing interest in identifying the behavioral skills involved in navigating socio–positive interactions (34), the factors underpinning variation in these skills [e.g., cognition (32, 34)], and how the ability to form socio–positive relationships correlates with performance in other social contexts (such as agonistic interactions) to contribute to social competence (34, 35). As a result, studies investigating how farm animals vary in their tendency to form positive social relationships may provide valuable insights into the mechanisms and development of behavior in addition to the potential implications for enhancing welfare.

Identifying the benefits of positive social interactions has attracted growing interest from behavioral ecologists in recent years, and developments in this field may be useful to enhance our understanding of social relationships in farm animals. Studies in wild animals have identified some of the functional benefits of social relationships (116122), how these benefits vary according to species' ecology (118, 120122) and the proximate mechanisms underlying social structure (161, 165, 169). While the majority of studies to date provide correlative rather than causative evidence, some studies have begun to test hypotheses relating to social structure through experimental manipulations of social groups (170). For example, studies in Paridae have used RFID technology to manipulate which members of a population gain access to foraging opportunities. These experiments showed that social relationships have wide-ranging effects on individual behavior and decision making. First, the social associations formed during foraging appear to carry over to other situations, demonstrating that the effects of social network disruption may extend beyond the immediate behavioral context in which the disruption occurs (171). Furthermore, individuals were willing to forego feeding opportunities to maintain important social relationships (172), and individuals responded to the loss of a close social associate by increasing their connections to the wider network (173). Automated monitoring systems are increasingly being used on farms to analyze space use, activity budgets and spatial associations, and are being developed to automatically distinguish between affiliative and agonistic social interactions [e.g., (151, 174176)]. Similarly, automated systems have been used to control animals' access to resources in farm systems, in order to manipulate social interactions [e.g., in cattle (177, 178)]. Motivation tests are also widely used to assess the behavioral needs of farm animals (179), including motivation to obtain contact with particular social companions [e.g., (130, 180)]. There may be opportunities to make further use of these methods to conduct controlled experiments determining the extent to which individuals are willing to invest in social relationships with different individuals within their social group, and how these relationships influence behavior and welfare across contexts. By understanding the value of positive social relationships in farm animals, we can identify the welfare impacts of separating individuals from preferred social companions. For example, a recent preliminary study found that separating dairy cows from their preferred partner increases variability in milk yield, a possible indicator of stress (177). In some situations, the impacts of separating preferred partners could be severe; on the other hand, the loss of a social companion may be mitigated if individuals compensate by strengthening relationships with other group members. While controlled experiments could be used to address these questions, social disruptions also occur frequently during on-farm activities, and these perturbations provide opportunities to investigate the speed and ease with which new positive social relationships are formed and their influence on welfare and productivity [e.g., (177, 181)]. These studies could also be used to identify “keystone” individuals that have a disproportionate influence on group-level behavior. While this idea has drawn interest in the context of harmful social behavior in farmed animals (99, 182185), it has yet to be tested in the context of affiliative behavior [but see (152)]. The farm system provides a highly controlled environment in which to investigate the dynamics of positive social interactions, the formation of preferential relationships, and the potential welfare implications.

Future directions

In this section, we suggest key questions for future research and highlight potential hypotheses of both fundamental and welfare relevance. We summarize our ideas in Table 1, using three of Tinbergen's four questions (function, mechanism, and development) as a framework.

TABLE 1
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Table 1. Summary of potential avenues for future research.

Ancestral function of social behavior, effects of domestication and relevance for farm animal welfare

Knowledge of the ancestral functions and origins of behavior can contribute to our understanding of farm animal social behavior, including how a history of artificial selection has altered behavioral expression, and how behaviors that may have historically enhanced fitness in the wild translate to the captive farm setting. For example, has the expression of contest skills in farm animals been altered by artificial selection and/or the nature of the farm environment? What relevance might these changes have for animal welfare? While the consequences of farm animal agonistic interactions are relatively well documented overall, there are many opportunities to identify important skills and the mechanisms influencing their development. Moreover, comparatively fewer studies have investigated the benefits of socio-positive interactions for farm animal health and welfare (30, 129). Social preference tests and experiments that measure individuals' motivation to return to specific group members may be particularly useful in addressing these questions [e.g., see (130, 140, 180); see Table 1]. Investigating the emotional costs of breaking social bonds may also provide valuable insights into the function and benefits of positive social interactions. For instance, judgement bias tests are widely used in applied ethology to quantify changes in affective state (112, 196), and may be employed to investigate the emotional responses of animals separated from preferred social companions. As most studies of socio-positive interactions in farm animals focus on short-term benefits, it would be especially valuable to extend studies to assess long-term effects on animal health and wellbeing and the costs of separating socially bonded individuals (30).

Proximate mechanisms underlying behavior

How individual variation in cognition, affective state, and personality interact to influence social skills and decision making in farm animals forms a key area for future research, with potential implications beyond managed species. Examining individual differences in social behavior, and the drivers of this variation, may be useful in influencing how group composition determines patterns of aggression and affiliation, and how behaviors are transmitted through groups. Technological developments have resulted in social network experiments becoming increasingly popular in the fields of both behavioral ecology and applied ethology, often incorporating manipulations of group characteristics to provide a wealth of information about social dynamics. Social network studies are being applied to understand patterns of affiliation, aggression and the spread of problematic behaviors in farm animals (197, 198), and there are opportunities to build on previous studies by manipulating interactions within social networks, either as part of controlled experiments or existing management activities.

There are also opportunities to learn more about the communicative mechanisms by which farm animals mediate their social interactions (1). While there is a body of work focusing on mother-offspring communication in farm animals [e.g., (18, 19, 190192)], less is known about communication and signaling between peers, particularly during socio-positive interactions. Do individuals communicate with all group members, or direct signals toward preferred social companions? In the latter case, communication patterns may provide important information about the nature and strength of social relationships. For example, pigs vocalize when separated from their peer group [e.g., (199)]; while this appears to be a clear indicator of social isolation stress, it would also be useful to determine whether these vocalizations are more frequently targeted toward particular peer-group members, and how they influence receiver behavior. Farm animals may also communicate during agonistic interactions, providing signals of RHP, motivation or skill that facilitate decision making. Currently, very little is known about signals of RHP in farm animals. More work is needed to identify the relevant signals mediating these interactions, and how individuals interpret these signals. Beyond their role in mediating social interactions, vocalizations and other signals are often important indicators for welfare (1, 29, 129, 200, 201). Important insights can therefore be gained from identifying the functions of different signals and how the frequency of signaling varies according to management conditions (29).

Development of behavior

The development of social skills is attracting growing interest in animal behavior research (33, 34), and empirical studies testing theories on the development of skill in farm animals would be both valuable and timely. Evidence that early social experiences shape contest behavior in pigs provides a useful model to test the role of skill and its development, and further research in other species would help to establish how skill influences contest outcome and assessment strategy. Following the predictions of game theory, these studies could identify how skills (including choice of behavior, accuracy, precision and efficiency) contribute to RHP, and quantify inter-individual variation in skill acquisition based on prior experience (33). It would also be valuable to further examine the role of social stability in influencing contest dynamics. In the case of pigs, while some studies show that maintaining stable social groups reduces aggression and benefits welfare (202, 203), long-term social stability is not common in most farm production systems. Interestingly, it may be that some degree of aggression is necessary for pigs to establish dominance relationships in unfamiliar groups, and an initial period of acute aggression after regrouping may lead to social stability being achieved more quickly (204). Identifying and encouraging the development of social skills may allow pigs to navigate these periods of acute aggression more successfully and lead to the establishment of stable dominance relationships with fewer costs. Further work could investigate the dynamics of aggression in livestock groups comprised of skillful individuals, and how these dynamics compare to less skillful groups, and groups that remain stable over a long period of time.

In addition to influencing agonistic interactions, social skills may play an important role in farm animals' affiliative interactions. Which skills are involved in forming beneficial social relationships? How do early life experiences facilitate the acquisition of these skills? Is there a key developmental window for the acquisition of particular social skills in farm animals (96, 205)? These questions could be addressed by identifying the specific behaviors involved in forming and maintaining social relationships in different species, and how individual social relationships change over time. More information is also needed on how farm animals choose their preferred social companions, based on factors such as familiarity, age, and personality. Longitudinal studies would be particularly valuable in this regard, allowing researchers to manipulate social associations, observe the formation of new social relationships and identify the relevant behaviors involved in mediating positive social interactions. By identifying the relevant skills farm animals use to navigate their social world, we can begin to investigate how individuals vary in their ability to choose the most appropriate behavior in different social contexts, and how this contributes to social competence (3335).

Conclusions

In this review, we have outlined how a deeper fundamental understanding of social behavior in farm animals can inform management and welfare. Important areas for further research include identifying the behavioral skills farm animals use to navigate competitive and positive social interactions; the factors underlying variation in skill; how different skills allow individuals to maximize the benefits arising from social interactions; and how a lack of skill contributes to welfare problems resulting from harmful social interactions. Exploring the welfare benefits of socio-positive interactions, and the potential costs associated with the disruption of important social bonds, also presents an important avenue for future research. Further increasing collaboration between fundamental and applied ethologists may provide opportunities to build on existing research, to mitigate social stress in livestock and address relevant questions regarding the mechanisms and development of social behavior. Similarly, the findings of these studies may provide insights that could be used to improve the welfare of managed animals in other contexts.

Author contributions

VL wrote the manuscript with input and guidance from GA and ST. All authors contributed to the article and approved the submitted version.

Funding

This project was funded by a BBSRC grant awarded to ST and GA (SRUC: BB/T001046/1; QUB: BB/T000716/1). SRUC also receives support from the Scottish Government Strategic Research Programme.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

References

1. Dawkins MS. A user's guide to animal welfare science. Trends Ecol Evol. (2006) 21:77–82. doi: 10.1016/j.tree.2005.10.017

PubMed Abstract | CrossRef Full Text | Google Scholar

2. Andersen IL, Nævdal E, Bøe KE, Bakken M. The significance of theories in behavioural ecology for solving problems in applied ethology - possibilities and limitations. Appl Anim Behav Sci. (2006) 97:85–104. doi: 10.1016/j.applanim.2005.11.020

CrossRef Full Text

3. Andersson M, Nordin E, Jensen P. Domestication effects on foraging strategies in fowl. Appl Anim Behav Sci. (2001) 72:51–62. doi: 10.1016/S0168-1591(00)00195-7

PubMed Abstract | CrossRef Full Text | Google Scholar

4. Fraser D, Kramer DL, Pajor EA, Weary DM. Conflict and cooperation: sociobiological principles and the behaviour of pigs. Appl Anim Behav Sci. (1995) 44:139–57. doi: 10.1016/0168-1591(95)00610-5

CrossRef Full Text | Google Scholar

5. Jensen P. New answers – old questions; new questions – old answers: how applied ethology is cross- fertilised by other disciplines. In: Brown JA, Seddon YM, Appleby MC, eds. Animals and Us: 50 Years and More of Applied Ethology. Wageningen: Wageningen Academic Publishers (2016), p. 1–336.

Google Scholar

6. Price EO. Behavioral development in animals undergoing domestication. Appl Anim Behav Sci. (1999) 65:245–71. doi: 10.1016/S0168-1591(99)00087-8

CrossRef Full Text | Google Scholar

7. Gustafsson M, Jensen P, De Jonge FH, Illmann G, Spinka M. Maternal behaviour of domestic sows and crosses between domestic sows and wild boar. Appl Anim Behav Sci. (1999) 65:29–42. doi: 10.1016/S0168-1591(99)00048-9

CrossRef Full Text | Google Scholar

8. Špinka M, Illmann G, De Jonge F, Andersson M, Schuurman T, Jensen P. Dimensions of maternal behaviour characteristics in domestic and wild x domestic crossbred sows. Appl Anim Behav Sci. (2000) 70:99–114. doi: 10.1016/S0168-1591(00)00151-9

PubMed Abstract | CrossRef Full Text | Google Scholar

9. Price EO. Behavioral aspects of animal domestication. Q Rev Biol. (1984) 59:1–32. doi: 10.1086/413673

CrossRef Full Text | Google Scholar

10. Estevez I, Andersen IL, Nævdal E. Group size, density and social dynamics in farm animals. Appl Anim Behav Sci. (2007) 103:185–204. doi: 10.1016/j.applanim.2006.05.025

PubMed Abstract | CrossRef Full Text | Google Scholar

11. Brent LJN, Chang SWC, Gariépy J-F, Platt ML. The neuroethology of friendship. Ann N Y Acad Sci. (2014) 1316:1–17. doi: 10.1111/nyas.12315

PubMed Abstract | CrossRef Full Text | Google Scholar

12. Nawroth C, Langbein J, Coulon M, Gabor V, Oesterwind S, Benz-Schwarzburg J, et al. Farm animal cognition-linking behavior, welfare and ethics. Front Vet Sci. (2019) 6:1–16. doi: 10.3389/fvets.2019.00024

PubMed Abstract | CrossRef Full Text | Google Scholar

13. D'Eath RB, Keeling LJ. Social discrimination and aggression by laying hens in large groups: from peck orders to social tolerance. Appl Anim Behav Sci. (2003) 84:197–212. doi: 10.1016/j.applanim.2003.08.010

CrossRef Full Text | Google Scholar

14. Peden RSE, Turner SP, Boyle LA, Camerlink I. The translation of animal welfare research into practice: the case of mixing aggression between pigs. Appl Anim Behav Sci. (2018) 204:1–9. doi: 10.1016/j.applanim.2018.03.003

CrossRef Full Text | Google Scholar

15. Rodenburg TB, Koene P. The impact of group size on damaging behaviours, aggression, fear and stress in farm animals. Appl Anim Behav Sci. (2007) 103:205–14. doi: 10.1016/j.applanim.2006.05.024

CrossRef Full Text | Google Scholar

16. Proudfoot K, Habing G. Social stress as a cause of diseases in farm animals: Current knowledge and future directions. Vet J. (2015) 206:15–21. doi: 10.1016/j.tvjl.2015.05.024

PubMed Abstract | CrossRef Full Text | Google Scholar

17. Drake A, Fraser D, Weary DM. Parent-offspring resource allocation in domestic pigs. Behav Ecol Sociobiol. (2008) 62:309–19. doi: 10.1007/s00265-007-0418-y

CrossRef Full Text | Google Scholar

18. Weary DM, Fraser D. Calling by domestic piglets: reliable signals of need? Anim Behav. (1995) 50:1047–55. doi: 10.1016/0003-3472(95)80105-7

CrossRef Full Text | Google Scholar

19. Weary DM, Lawson GL, Thompson BK. Sows show stronger responses to isolation calls of piglets associated with greater levels of piglet need. Anim Behav. (1996) 52:1247–53. doi: 10.1006/anbe.1996.0272

CrossRef Full Text | Google Scholar

20. Castren H, Algers B, Jensen P, Saloniemi H. Suckling behaviour and milk consumption in newborn piglets as a response to sow grunting. Appl Anim Behav Sci. (1989) 24:227–38. doi: 10.1016/0168-1591(89)90069-5

CrossRef Full Text | Google Scholar

21. Nicol CJ, Caplen G, Statham P, Browne WJ. Decisions about foraging and risk trade-offs in chickens are associated with individual somatic response profiles. Anim Behav. (2011) 82:255–62. doi: 10.1016/j.anbehav.2011.04.022

CrossRef Full Text | Google Scholar

22. Gustafsson M, Jensen P, De Jonge FH, Schuurman T. Domestication effects on foraging strategies in pigs (Sus scrofa). Appl Anim Behav Sci. (1999) 62:305–17. doi: 10.1016/S0168-1591(98)00236-6

CrossRef Full Text | Google Scholar

23. Held SDE, Byrne RW, Jones S, Murphy E, Friel M, Mendl MT. Domestic pigs, Sus scrofa, adjust their foraging behaviour to whom they are foraging with. Anim Behav. (2010) 79:857–62. doi: 10.1016/j.anbehav.2009.12.035

CrossRef Full Text | Google Scholar

24. Schütz KE, Forkman B, Jensen P. Domestication effects on foraging strategy, social behaviour and different fear responses: a comparison between the red junglefowl (Gallus gallus) and a modern layer strain. Appl Anim Behav Sci. (2001) 74:1–14. doi: 10.1016/S0168-1591(01)00156-3

CrossRef Full Text | Google Scholar

25. Jensen P, Recén B. When to wean - observations from free-ranging domestic pigs. Appl Anim Behav Sci. (1989) 23:49–60. doi: 10.1016/0168-1591(89)90006-3

CrossRef Full Text | Google Scholar

26. Nicol CJ, Pope SJ. Social learning in small flocks of laying hens. Anim Behav. (1994) 47:1289–96. doi: 10.1006/anbe.1994.1177

CrossRef Full Text | Google Scholar

27. Nicol CJ, Pope SJ. The effects of demonstrator social status and prior foraging success on social learning in laying hens. Anim Behav. (1999) 57:163–71. doi: 10.1006/anbe.1998.0920

PubMed Abstract | CrossRef Full Text | Google Scholar

28. Sherwin CM, Heyes CM, Nicol CJ. Social learning influences the preferences of domestic hens for novel food. Anim Behav. (2002) 63:933–42. doi: 10.1006/anbe.2002.2000

CrossRef Full Text | Google Scholar

29. Weary DM, Fraser D. Signalling need: costly signals and animal welfare assessment. Appl Anim Behav Sci. (1995) 44:159–69. doi: 10.1016/0168-1591(95)00611-U

CrossRef Full Text | Google Scholar

30. Rault JL. Friends with benefits: social support and its relevance for farm animal welfare. Appl Anim Behav Sci. (2012) 136:1–14. doi: 10.1016/j.applanim.2011.10.002

CrossRef Full Text | Google Scholar

31. Brakes P. Sociality and wild animal welfare: future directions. Front Vet Sci. (2019) 6:1–7. doi: 10.3389/fvets.2019.00062

PubMed Abstract | CrossRef Full Text | Google Scholar

32. Wascher CAF, Kulahci IG, Langley EJG, Shaw RC. How does cognition shape social relationships? Philos Trans R Soc B Biol Sci. (2018) 373:15–8. doi: 10.1098/rstb.2017.0293

PubMed Abstract | CrossRef Full Text | Google Scholar

33. Briffa M, Lane SM. The role of skill in animal contests: a neglected component of fighting ability. Proc R Soc B Biol Sci. (2017) 284: 20171596. doi: 10.1098/rspb.2017.1596

PubMed Abstract | CrossRef Full Text | Google Scholar

34. Sih A, Sinn DL, Patricelli GL. On the importance of individual differences in behavioural skill. Anim Behav. (2019) 155:307–17. doi: 10.1016/j.anbehav.2019.06.017

CrossRef Full Text | Google Scholar

35. Taborsky B, Oliveira RF. Social competence: an evolutionary approach. Trends Ecol Evol. (2012) 27:679–88. doi: 10.1016/j.tree.2012.09.003

PubMed Abstract | CrossRef Full Text | Google Scholar

36. Rose PE, Croft DP. The potential of social network analysis as a tool for the management of zoo animals. Anim Welf. (2015) 24:123–38. doi: 10.7120/09627286.24.2.123

PubMed Abstract | CrossRef Full Text | Google Scholar

37. Ward SJ, Hosey G. The need for a convergence of agricultural/laboratory and zoo-based approaches to animal welfare. J Appl Anim Welf Sci. (2020) 23:484–92. doi: 10.1080/10888705.2019.1678038

PubMed Abstract | CrossRef Full Text | Google Scholar

38. Holekamp KE, Strauss ED. Aggression and dominance: an interdisciplinary overview. Curr Opin Behav Sci. (2016) 12:44–51. doi: 10.1016/j.cobeha.2016.08.005

CrossRef Full Text | Google Scholar

39. Meese GB, Ewbank R. The establishment and nature of the dominance hierarchy in the domesticated pig. Anim Behav. (1973) 21:326–34. doi: 10.1016/S0003-3472(73)80074-0

CrossRef Full Text | Google Scholar

40. Camerlink I, Turner SP, Farish M, Arnott G. Advantages of social skills for contest resolution. R Soc Open Sci. (2019) 6:1–8. doi: 10.1038/s41598-018-30634-z

PubMed Abstract | CrossRef Full Text | Google Scholar

41. Turner SP, Nevison IM, Desire S, Camerlink I, Roehe R, Ison SH, et al. Aggressive behaviour at regrouping is a poor predictor of chronic aggression in stable social groups. Appl Anim Behav Sci. (2017) 191:98–106. doi: 10.1016/j.applanim.2017.02.002

CrossRef Full Text | Google Scholar

42. Marchant JN, Mendl MT, Rudd AR, Broom DM. The effect of agonistic interactions on the heart rate of group-housed sows. Appl Anim Behav Sci. (1995) 46:49–56. doi: 10.1016/0168-1591(95)00636-2

CrossRef Full Text | Google Scholar

43. Coutellier L, Arnould C, Boissy A, Orgeur P, Prunier A, Veissier I, et al. Pig's responses to repeated social regrouping and relocation during the growing-finishing period. Appl Anim Behav Sci. (2007) 105:102–14. doi: 10.1016/j.applanim.2006.05.007

CrossRef Full Text | Google Scholar

44. Turner SP, Farnworth MJ, White IMS, Brotherstone S, Mendl M, Knap P, et al. The accumulation of skin lesions and their use as a predictor of individual aggressiveness in pigs. Appl Anim Behav Sci. (2006) 96:245–59. doi: 10.1016/j.applanim.2005.06.009

CrossRef Full Text | Google Scholar

45. Morrow-Tesch JL, McGlone JJ, Salak-Johnson JL. Heat and social stress effects on pig immune measures. J Anim Sci. (1994) 72:2599–609. doi: 10.2527/1994.72102599x

PubMed Abstract | CrossRef Full Text | Google Scholar

46. Tan S, Shackleton D, Beames R. The effect of mixing unfamiliar individuals on the growth and production of finishing pigs. Anim Sci. (1991) 52:201–6. doi: 10.1017/S0003356100005845

CrossRef Full Text | Google Scholar

47. Stookey J, Gonyou H. The effects of regrouping on behavioral and production parameters in finishing swine. J Anim Sci. (1994) 72:2804–11. doi: 10.2527/1994.72112804x

PubMed Abstract | CrossRef Full Text | Google Scholar

48. Erhard HW, Mendl M. Measuring aggressiveness in growing pigs in a resident-intruder situation. Appl Anim Behav Sci. (1997) 54:123–36. doi: 10.1016/S0168-1591(97)00069-5

CrossRef Full Text | Google Scholar

49. Büttner K, Scheffler K, Czycholl I, Krieter J. Network characteristics and development of social structure of agonistic behaviour in pigs across three repeated rehousing and mixing events. Appl Anim Behav Sci. (2015) 168:24–30. doi: 10.1016/j.applanim.2015.04.017

CrossRef Full Text | Google Scholar

50. Turner SP, Horgan GW, Edwards SA. Effect of social group size on aggressive behaviour between unacquainted domestic pigs. Appl Anim Behav Sci. (2001) 74:203–15. doi: 10.1016/S0168-1591(01)00168-X

CrossRef Full Text | Google Scholar

51. Maynard Smith J, Price GR. The logic of animal conflict. Nature. (1973) 246:15–8. doi: 10.1038/246015a0

CrossRef Full Text | Google Scholar

52. Arnott G, Elwood RW. Assessment of fighting ability in animal contests. Anim Behav. (2009) 77:991–1004. doi: 10.1016/j.anbehav.2009.02.010

CrossRef Full Text | Google Scholar

53. Arnott G, Elwood RW. Information gathering and decision making about resource value in animal contests. Anim Behav. (2008) 76:529–42. doi: 10.1016/j.anbehav.2008.04.019

CrossRef Full Text | Google Scholar

54. Palaoro A V, Briffa M. Weaponry and defenses in fighting animals: how allometry can alter predictions from contest theory. Behav Ecol. (2017) 28:328–36. doi: 10.1093/beheco/arw163

CrossRef Full Text | Google Scholar

55. Dall SRX, Giraldeau L-A, Olsson O, McNamara JM, Stephens DW. Information and its use by animals in evolutionary ecology. Trends Ecol Evol. (2005) 20:187–93. doi: 10.1016/j.tree.2005.01.010

PubMed Abstract | CrossRef Full Text | Google Scholar

56. Mesterton-Gibbons M, Marden JH, Dugatkin LA. On wars of attrition without assessment. J Theor Biol. (1996) 181:65–83. doi: 10.1006/jtbi.1996.0115

CrossRef Full Text | Google Scholar

57. Payne RJH, Pagel M. Escalation and time costs in displays of endurance. J Theor Biol. (1996) 183:185–93. doi: 10.1006/jtbi.1996.0212

CrossRef Full Text | Google Scholar

58. Payne RJH. Gradually escalating fights and displays: the cumulative assessment model. Anim Behav. (1998) 56:651–62. doi: 10.1006/anbe.1998.0835

PubMed Abstract | CrossRef Full Text | Google Scholar

59. Enquist M, Leimar O. Evolution of fighting behaviour: decision rules and assessment of relative strength. J Theor Biol. (1983) 102:387–410. doi: 10.1016/0022-5193(83)90376-4

CrossRef Full Text | Google Scholar

60. Pinto NS, Palaoro A V, Peixoto PEC. All by myself? Meta-analysis of animal contests shows stronger support for self than for mutual assessment models. Biol Rev. (2019) 94:1430–42. doi: 10.1111/brv.12509

PubMed Abstract | CrossRef Full Text | Google Scholar

61. Junior RSL, Peixoto PEC. Males of the dragonfly Diastatops obscura fight according to predictions from game theory models. Anim Behav. (2013) 85:663–9. doi: 10.1016/j.anbehav.2012.12.033

CrossRef Full Text | Google Scholar

62. Schnell AK, Smith CL, Hanlon RT, Harcourt R. Giant Australian cuttlefish use mutual assessment to resolve male-male contests. Anim Behav. (2015) 107:31–40. doi: 10.1016/j.anbehav.2015.05.026

CrossRef Full Text | Google Scholar

63. Palaoro A V, Dalosto MM, Costa JR, Santos S. Freshwater decapod (Aegla longirostri) uses a mixed assessment strategy to resolve contests. Anim Behav. (2014) 95:71–9. doi: 10.1016/j.anbehav.2014.06.014

CrossRef Full Text | Google Scholar

64. Prenter J, Taylor P, Elwood R. Large body size for winning and large swords for winning quickly in swordtail males, Xiphophorus helleri. Anim Behav. (2008) 75:1981–7. doi: 10.1016/j.anbehav.2007.12.008

CrossRef Full Text | Google Scholar

65. Chapin KJ, Peixoto PEC, Briffa M. Further mismeasures of animal contests: a new framework for assessment strategies. Behav Ecol. (2019) 30:1177–85. doi: 10.1093/beheco/arz081

CrossRef Full Text | Google Scholar

66. Mesterton-Gibbons M, Heap SM. Variation between self- and mutual assessment in animal contests. Am Nat. (2014) 183:199–213. doi: 10.1086/674443

PubMed Abstract | CrossRef Full Text | Google Scholar

67. Hsu Y, Lee SP, Chen MH, Yang SY, Cheng KC. Switching assessment strategy during a contest: fighting in killifish Kryptolebias marmoratus. Anim Behav. (2008) 75:1641–9. doi: 10.1016/j.anbehav.2007.10.017

CrossRef Full Text | Google Scholar

68. Camerlink I, Turner SP, Farish M, Arnott G. The influence of experience on contest assessment strategies. Sci Rep. (2017) 7:1–10. doi: 10.1038/s41598-017-15144-8

PubMed Abstract | CrossRef Full Text | Google Scholar

69. Weller JE, Camerlink I, Turner SP, Farish M, Arnott G. Socialisation and its effect on play behaviour and aggression in the domestic pig (Sus scrofa). Sci Rep. (2019) 9:1–11. doi: 10.1038/s41598-019-40980-1

PubMed Abstract | CrossRef Full Text | Google Scholar

70. Arnott G, Elwood RW. Gender differences in aggressive behaviour in convict cichlids. Anim Behav. (2009) 78:1221–7. doi: 10.1016/j.anbehav.2009.08.005

PubMed Abstract | CrossRef Full Text | Google Scholar

71. Elias DO, Botero CA, Andrade MCBB, Mason AC, Kasumovic MM. High resource valuation fuels “desperado” fighting tactics in female jumping spiders. Behav Ecol. (2010) 21:868–75. doi: 10.1093/beheco/arq073

CrossRef Full Text | Google Scholar

72. Reedy AM, Pope BD, Kiriazis NM, Giordano CL, Sams CL, Warner DA, et al. Female anoles display less but attack more quickly than males in response to territorial intrusions. Behav Ecol. (2017) 28:1323–8. doi: 10.1093/beheco/arx095

CrossRef Full Text | Google Scholar

73. Kemp DJ. Ageing, reproductive value, and the evolution of lifetime fighting behaviour. Biol J Linn Soc. (2006) 88:565–78. doi: 10.1111/j.1095-8312.2006.00643.x

CrossRef Full Text | Google Scholar

74. Fawcett TW, Johnstone R a. Learning your own strength: winner and loser effects should change with age and experience. Proc R Soc B. (2010) 277:1427–34. doi: 10.1098/rspb.2009.2088

PubMed Abstract | CrossRef Full Text | Google Scholar

75. Kemp DJ. Twilight fighting in the evening brown butterfly. Melanitis leda (L) (Nymphalidae): age and residency effects. Behav Ecol Sociobiol. (2003) 54:7–13. doi: 10.1007/s00265-003-0602-7

CrossRef Full Text | Google Scholar

76. Hsu Y, Wolf L. The winner and loser effect: integrating multiple experiences. Anim Behav. (1999) 57:903–10. doi: 10.1006/anbe.1998.1049

PubMed Abstract | CrossRef Full Text | Google Scholar

77. Hsu Y, Earley RL, Wolf LL. Modulation of aggressive behaviour by fighting experience: mechanisms and contest outcomes. Biol Rev Camb Philos Soc. (2006) 81:33–74. doi: 10.1017/S146479310500686X

PubMed Abstract | CrossRef Full Text | Google Scholar

78. Oldham L, Camerlink I, Arnott G, Doeschl-Wilson A, Farish M, Turner SP. Winner–loser effects overrule aggressiveness during the early stages of contests between pigs. Sci Rep. (2020) 10:1–13. doi: 10.1038/s41598-020-69664-x

PubMed Abstract | CrossRef Full Text | Google Scholar

79. Briffa M, Sneddon LU, Wilson AJ. Animal personality as a cause and consequence of contest behaviour. Biol Lett. (2015) 11:20141007. doi: 10.1098/rsbl.2014.1007

PubMed Abstract | CrossRef Full Text | Google Scholar

80. Reichert MS, Quinn JL. Cognition in contests: mechanisms, ecology, and evolution. Trends Ecol Evol. (2017) 32:773–85. doi: 10.1016/j.tree.2017.07.003

PubMed Abstract | CrossRef Full Text | Google Scholar

81. Crump A, Bethell EJ, Earley R, Lee VE, Mendl M, Oldham L, et al. Emotion in animal contests. Proc R Soc B. (2020) 287:20201715. doi: 10.1098/rspb.2020.1715

PubMed Abstract | CrossRef Full Text | Google Scholar

82. Mendl M, Burman OHP, Paul ES. An integrative and functional framework for the study of animal emotion and mood. Proc R Soc B Biol Sci. (2010) 277:2895–904. doi: 10.1098/rspb.2010.0303

PubMed Abstract | CrossRef Full Text | Google Scholar

83. Hobson EA. Differences in social information are critical to understanding aggressive behavior in animal dominance hierarchies. Curr Opin Psychol. (2020) 33:209–15. doi: 10.1016/j.copsyc.2019.09.010

PubMed Abstract | CrossRef Full Text | Google Scholar

84. Garnham LC, Porthén SA, Child S, Forslind S, Løvlie H. The role of personality, cognition, and affective state in same-sex contests in the red junglefowl. Behav Ecol Sociobiol. (2019) 73:149. doi: 10.1007/s00265-019-2762-0

CrossRef Full Text | Google Scholar

85. Bushby EV, Friel M, Goold C, Gray H, Smith L, Collins LM. Factors influencing individual variation in farm animal cognition and how to account for these statistically. Front Vet Sci. (2018) 5:1–15. doi: 10.3389/fvets.2018.00193

PubMed Abstract | CrossRef Full Text | Google Scholar

86. Sih A, Del Giudice M. Linking behavioural syndromes and cognition: a behavioural ecology perspective. Philos Trans R Soc B. (2012) 367:2762–72. doi: 10.1098/rstb.2012.0216

PubMed Abstract | CrossRef Full Text | Google Scholar

87. Costa JHC, von Keyserlingk MAG, Weary DM. Invited review: Effects of group housing of dairy calves on behavior, cognition, performance, and health. J Dairy Sci. (2016) 99:2453–67. doi: 10.3168/jds.2015-10144

PubMed Abstract | CrossRef Full Text | Google Scholar

88. Gaillard C, Meagher RK, Von Keyserlingk MAG, Weary DM. Social housing improves dairy calves' performance in two cognitive tests. PLoS ONE. (2014) 9:e0090205. doi: 10.1371/journal.pone.0090205

PubMed Abstract | CrossRef Full Text | Google Scholar

89. Martin JE, Ison SH, Baxter EM. The influence of neonatal environment on piglet play behaviour and post-weaning social and cognitive development. Appl Anim Behav Sci. (2015) 163:69–79. doi: 10.1016/j.applanim.2014.11.022

CrossRef Full Text | Google Scholar

90. Meagher RK, Daros RR, Costa JHC, Von Keyserlingk MAG, Hötzel MJ, Weary DM. Effects of degree and timing of social housing on reversal learning and response to novel objects in dairy calves. PLoS ONE. (2015) 10:1–15. doi: 10.1371/journal.pone.0132828

PubMed Abstract | CrossRef Full Text | Google Scholar

91. Weller JE, Turner SP, Futro A, Donbavand J, Brims M, Arnott G. The influence of early life socialisation on cognition in the domestic pig (Sus scrofa domestica). Sci Rep. (2020) 10:1–14. doi: 10.1038/s41598-020-76110-5

PubMed Abstract | CrossRef Full Text | Google Scholar

92. Hellbrügge B, Tölle KH, Bennewitz J, Henze C, Presuhn U, Krieter J. Genetic aspects regarding piglet losses and the maternal behaviour of sows. Part 2 Genetic relationship between maternal behaviour in sows and piglet mortality. Animal. (2008) 2:1281–8. doi: 10.1017/S1751731108002516

PubMed Abstract | CrossRef Full Text | Google Scholar

93. Løvendahl P, Damgaard LH, Nielsen BL, Thodberg K, Su G, Rydhmer L. Aggressive behaviour of sows at mixing and maternal behaviour are heritable and genetically correlated traits. Livest Prod Sci. (2005) 93:73–85. doi: 10.1016/j.livprodsci.2004.11.008

CrossRef Full Text | Google Scholar

94. Scheffler K, Stamer E, Traulsen I, Krieter J. Estimation of genetic parameters for agonistic behaviour of pigs at different ages. J Agric Sci. (2016) 154:732–41. doi: 10.1017/S0021859616000010

CrossRef Full Text | Google Scholar

95. Turner SP, Roehe R, Mekkawy W, Farnworth MJ, Knap PW, Lawrence AB. Bayesian analysis of genetic associations of skin lesions and behavioural traits to identify genetic components of individual aggressiveness in pigs. Behav Genet. (2008) 38:67–75. doi: 10.1007/s10519-007-9171-2

PubMed Abstract | CrossRef Full Text | Google Scholar

96. D'Eath RB. Socialising piglets before weaning improves social hierarchy formation when pigs are mixed post-weaning. Appl Anim Behav Sci. (2005) 93:199–211. doi: 10.1016/j.applanim.2004.11.019

CrossRef Full Text | Google Scholar

97. Weller JE, Camerlink I, Turner SP, Farish M, Arnott G. Playful pigs: early life play-fighting experience influences later life contest dynamics. Anim Behav. (2019) 158:269–79. doi: 10.1016/j.anbehav.2019.09.019

CrossRef Full Text | Google Scholar

98. Jensen P, Yngvesson J. Aggression between unacquainted pigs - sequential assessment and effects of familiarity and weight. Appl Anim Behav Sci. (1998) 58:49–61. doi: 10.1016/S0168-1591(97)00097-X

CrossRef Full Text | Google Scholar

99. Turner SP, Weller JE, Camerlink I, Arnott G, Choi T, Doeschl-Wilson A, et al. Play fighting social networks do not predict injuries from later aggression. Sci Rep. (2020) 10:1–16. doi: 10.1038/s41598-020-72477-7

PubMed Abstract | CrossRef Full Text | Google Scholar

100. Brown SM, Klaffenböck M, Nevison IM, Lawrence AB. Evidence for litter differences in play behaviour in pre-weaned pigs. Appl Anim Behav Sci. (2015) 172:17–25. doi: 10.1016/j.applanim.2015.09.007

PubMed Abstract | CrossRef Full Text | Google Scholar

101. Morrell LJ, Lindström J, Ruxton GD. Why are small males aggressive? Proc R Soc B Biol Sci. (2005) 272:1235–41. doi: 10.1098/rspb.2005.3085

PubMed Abstract | CrossRef Full Text | Google Scholar

102. Just W, Morris MR. The Napoleon complex: why smaller males pick fights. Evol Ecol. (2003) 17:509–22. doi: 10.1023/B:EVEC.0000005629.54152.83

CrossRef Full Text | Google Scholar

103. Grafen A. The logic of divisively asymmetric contests: respect for ownership and the desperado effect. Anim Behav. (1987) 35:462–7. doi: 10.1016/S0003-3472(87)80271-3

CrossRef Full Text | Google Scholar

104. Weller JE, Turner SP, Farish M, Camerlink I, Arnott G. The association between play fighting and information gathering during subsequent contests. Sci Rep. (2020) 10:1133. doi: 10.1038/s41598-020-58063-x

PubMed Abstract | CrossRef Full Text | Google Scholar

105. Tallet C, Brilloüet A, Meunier-Salaün MC, Paulmier V, Guérin C, Prunier A. Effects of neonatal castration on social behaviour, human-animal relationship and feeding activity in finishing pigs reared in a conventional or an enriched housing. Appl Anim Behav Sci. (2013) 145:70–83. doi: 10.1016/j.applanim.2013.03.001

CrossRef Full Text | Google Scholar

106. Cronin GM, Dunshea FR, Butler KL, McCauley I, Barnett JL, Hemsworth PH. The effects of immuno- and surgical-castration on the behaviour and consequently growth of group-housed, male finisher pigs. Appl Anim Behav Sci. (2003) 81:111–26. doi: 10.1016/S0168-1591(02)00256-3

CrossRef Full Text | Google Scholar

107. Camerlink I, Turner SP, Farish M, Arnott G. Aggressiveness as a component of fighting ability in pigs using a game-theoretical framework. Anim Behav. (2015) 108:183–91. doi: 10.1016/j.anbehav.2015.07.032

CrossRef Full Text | Google Scholar

108. Bolhuis JE, Schouten WGP, Schrama JW, Wiegant VM. Individual coping characteristics, aggressiveness and fighting strategies in pigs. Anim Behav. (2005) 69:1085–91. doi: 10.1016/j.anbehav.2004.09.013

CrossRef Full Text | Google Scholar

109. Melotti L, Oostindjer M, Bolhuis JE, Held S, Mendl M. Coping personality type and environmental enrichment affect aggression at weaning in pigs. Appl Anim Behav Sci. (2011) 133:144–53. doi: 10.1016/j.applanim.2011.05.018

CrossRef Full Text | Google Scholar

110. Camerlink I, Arnott G, Farish M, Turner SP. Complex contests and the influence of aggressiveness in pigs. Anim Behav. (2016) 121:71–8. doi: 10.1016/j.anbehav.2016.08.021

CrossRef Full Text | Google Scholar

111. Finkemeier MA, Langbein J, Puppe B. Personality research in mammalian farm animals: concepts, measures, and relationship to welfare. Front Vet Sci. (2018) 5:1–15. doi: 10.3389/fvets.2018.00131

PubMed Abstract | CrossRef Full Text

112. Baciadonna L, McElligott AG. The use of judgement bias to assess welfare in farm livestock. Anim Welf. (2015) 24:81–91. doi: 10.7120/09627286.24.1.081

CrossRef Full Text | Google Scholar

113. Whittaker AL, Barker TH. A. consideration of the role of biology and test design as confounding factors in judgement bias tests. Appl Anim Behav Sci. (2020) 232:105126. doi: 10.1016/j.applanim.2020.105126

CrossRef Full Text | Google Scholar

114. Favati A, Løvlie H, Leimar O. Individual aggression, but not winner-loser effects, predicts social rank in male domestic fowl. Behav Ecol. (2017) 28:874–82. doi: 10.1093/beheco/arx053

CrossRef Full Text | Google Scholar

115. Snyder-Mackler N, Burger JR, Gaydosh L, Belsky DW, Noppert GA, Campos FA, et al. Social determinants of health and survival in humans and other animals. Science. (2020) 368:eaax9553. doi: 10.1126/science.aax9553

PubMed Abstract | CrossRef Full Text | Google Scholar

116. Silk JB, Beehner JC, Bergman TJ, Crockford C, Engh AL, Moscovice LR, et al. The benefits of social capital: close social bonds among female baboons enhance offspring survival. Proc R Soc B Biol Sci. (2009) 276:3099–104. doi: 10.1098/rspb.2009.0681

PubMed Abstract | CrossRef Full Text | Google Scholar

117. Silk JB, Beehner JC, Bergman TJ, Crockford C, Engh AL, Moscovice LR, et al. Strong and consistent social bonds enhance the longevity of female baboons. Curr Biol. (2010) 20:1359–61. doi: 10.1016/j.cub.2010.05.067

PubMed Abstract | CrossRef Full Text | Google Scholar

118. Campbell LAD, Tkaczynski PJ, Lehmann J, Mouna M, Majolo B. Social thermoregulation as a potential mechanism linking sociality and fitness: Barbary macaques with more social partners form larger huddles. Sci Rep. (2018) 8:1–8. doi: 10.1038/s41598-018-24373-4

PubMed Abstract | CrossRef Full Text | Google Scholar

119. Stanton MA, Mann J. Early social networks predict survival in wild bottlenose dolphins. PLoS ONE. (2012) 7:1–6. doi: 10.1371/journal.pone.0047508

PubMed Abstract | CrossRef Full Text | Google Scholar

120. Frère CH, Krützen M, Mann J, Connor RC, Bejder L, Sherwin WB. Social and genetic interactions drive fitness variation in a free-living dolphin population. Proc Natl Acad Sci. (2010) 107:19949–54. doi: 10.1073/pnas.1007997107

PubMed Abstract | CrossRef Full Text | Google Scholar

121. Brent LJN, Franks DW, Foster EA, Balcomb KC, Cant MA, Croft DP. Ecological knowledge, leadership, and the evolution of menopause in killer whales. Curr Biol. (2015) 25:746–50. doi: 10.1016/j.cub.2015.01.037

PubMed Abstract | CrossRef Full Text | Google Scholar

122. Cameron EZ, Setsaas TH, Linklater WL. Social bonds between unrelated females increase reproductive success in feral horses. Proc Natl Acad Sci. (2009) 106:13850–3. doi: 10.1073/pnas.0900639106

PubMed Abstract | CrossRef Full Text | Google Scholar

123. Seyfarth RM, Cheney DL. The evolutionary origins of friendship. Annu Rev Psychol. (2012) 63:153–77. doi: 10.1146/annurev-psych-120710-100337

PubMed Abstract | CrossRef Full Text | Google Scholar

124. Carter GG, Wilkinson GS. Social benefits of non-kin food sharing by female vampire bats. Proc R Soc B Biol Sci. (2015) 282:20152524. doi: 10.1098/rspb.2015.2524

PubMed Abstract | CrossRef Full Text | Google Scholar

125. Gerber L, Wittwer S, Allen SJ, Holmes KG, King SL, Sherwin WB, et al. Cooperative partner choice in multi-level male dolphin alliances. Sci Rep. (2021) 11:1–10. doi: 10.1038/s41598-021-85583-x

PubMed Abstract | CrossRef Full Text | Google Scholar

126. Riehl C, Strong MJ. Stable social relationships between unrelated females increase individual fitness in a cooperative bird. Proc R Soc B Biol Sci. (2018) 285:20180130. doi: 10.1098/rspb.2018.0130

PubMed Abstract | CrossRef Full Text | Google Scholar

127. Schülke O, Bhagavatula J, Vigilant L, Ostner J. Social bonds enhance reproductive success in male macaques. Curr Biol. (2010) 20:2207–10. doi: 10.1016/j.cub.2010.10.058

PubMed Abstract | CrossRef Full Text | Google Scholar

128. Weidt A, Hofmann SE, König B. Not only mate choice matters: fitness consequences of social partner choice in female house mice. Anim Behav. (2008) 75:801–8. doi: 10.1016/j.anbehav.2007.06.017

CrossRef Full Text | Google Scholar

129. Boissy A, Manteuffel G, Jensen MB, Moe RO, Spruijt B, Keeling LJ, et al. Assessment of positive emotions in animals to improve their welfare. Physiol Behav. (2007) 92:375–97. doi: 10.1016/j.physbeh.2007.02.003

PubMed Abstract | CrossRef Full Text | Google Scholar

130. Wenker ML, Bokkers EAM, Lecorps B, von Keyserlingk MAG, van Reenen CG, Verwer CM, et al. Effect of cow-calf contact on cow motivation to reunite with their calf. Sci Rep. (2020) 10:1–5. doi: 10.1038/s41598-020-70927-w

PubMed Abstract | CrossRef Full Text | Google Scholar

131. Johnsen JF, de Passille AM, Mejdell CM, Bøe KE, Grøndahl AM, Beaver A, et al. The effect of nursing on the cow-calf bond. Appl Anim Behav Sci. (2015) 163:50–7. doi: 10.1016/j.applanim.2014.12.003

CrossRef Full Text | Google Scholar

132. Flower FC, Weary DM. Effects of early separation on the dairy cow and calf: 2. Separation at 1 day and 2 weeks after birth. Appl Anim Behav Sci. (2001) 70:275–84. doi: 10.1016/S0168-1591(00)00164-7

PubMed Abstract | CrossRef Full Text | Google Scholar

133. Wagner K, Barth K, Palme R, Futschik A, Waiblinger S. Integration into the dairy cow herd: Long-term effects of mother contact during the first twelve weeks of life. Appl Anim Behav Sci. (2012) 141:117–29. doi: 10.1016/j.applanim.2012.08.011

CrossRef Full Text | Google Scholar

134. Wagner K, Seitner D, Barth K, Palme R, Futschik A, Waiblinger S. Effects of mother versus artificial rearing during the first 12 weeks of life on challenge responses of dairy cows. Appl Anim Behav Sci. (2015) 164:1–11. doi: 10.1016/j.applanim.2014.12.010

CrossRef Full Text | Google Scholar

135. De Paula Vieira A, de Passillé AM, Weary DM. Effects of the early social environment on behavioral responses of dairy calves to novel events. J Dairy Sci. (2012) 95:5149–55. doi: 10.3168/jds.2011-5073

PubMed Abstract | CrossRef Full Text | Google Scholar

136. Jensen MB, Vestergaard KS, Krohn CC, Munksgaard L. Effect of single versus group housing and space allowance on responses of calves during open-field tests. Appl Anim Behav Sci. (1997) 54:109–21. doi: 10.1016/S0168-1591(96)01183-5

CrossRef Full Text | Google Scholar

137. Raussi S, Lensink BJ, Boissy A, Pyykkönen M, Veissier I. The effect of contact with conspecifics and humans on calves' behaviour and stress responses. Anim Welf. (2003) 12:191–203.

Google Scholar

138. Toinon C, Waiblinger S, Rault JL. Maternal deprivation affects goat kids' stress coping behaviour. Physiol Behav. (2021) 239:113494. doi: 10.1016/j.physbeh.2021.113494

PubMed Abstract | CrossRef Full Text | Google Scholar

139. Takeda KI, Sato S, Sugawara K. Familiarity and group size affect emotional stress in Japanese Black heifers. Appl Anim Black heifers. (2003) 82:1–11. doi: 10.1016/S0168-1591(03)00039-X

CrossRef Full Text | Google Scholar

140. Færevik G, Jensen MB, Bøe KE. Dairy calves social preferences and the significance of a companion animal during separation from the group. Appl Anim Behav Sci. (2006) 99:205–21. doi: 10.1016/j.applanim.2005.10.012

CrossRef Full Text | Google Scholar

141. Foris B, Zebunke M, Langbein J, Melzer N. Comprehensive analysis of affiliative and agonistic social networks in lactating dairy cattle groups. Appl Anim Behav Sci. (2019) 210:60–7. doi: 10.1016/j.applanim.2018.10.016

CrossRef Full Text | Google Scholar

142. Val-Laillet D, Guesdon V, von Keyserlingk MAG, de Passillé AM, Rushen J. Allogrooming in cattle: relationships between social preferences, feeding displacements and social dominance. Appl Anim Behav Sci. (2009) 116:141–9. doi: 10.1016/j.applanim.2008.08.005

CrossRef Full Text | Google Scholar

143. Stanley CR, Dunbar RIM. Consistent social structure and optimal clique size revealed by social network analysis of feral goats, Capra hircus. Anim Behav. (2013) 85:771–9. doi: 10.1016/j.anbehav.2013.01.020

CrossRef Full Text | Google Scholar

144. Durrell JL, Sneddon IA, O'Connell NE, Whitehead H. Do pigs form preferential associations? Appl Anim Behav Sci. (2004) 89:41–52. doi: 10.1016/j.applanim.2004.05.003

CrossRef Full Text | Google Scholar

145. Newberry RC, Wood-Gush DGM. Social relationships of piglets in a semi-natural environment. Anim Behav. (1986) 34:1311–8. doi: 10.1016/S0003-3472(86)80202-0

CrossRef Full Text | Google Scholar

146. Goumon S, Illmann G, Leszkowová I, Dostalová A, Cantor M. Dyadic affiliative preferences in a stable group of domestic pigs. Appl Anim Behav Sci. (2020) 230:105045. doi: 10.1016/j.applanim.2020.105045

CrossRef Full Text | Google Scholar

147. Ozella L, Langford J, Gauvin L, Price E, Cattuto C, Croft DP. The effect of age, environment and management on social contact patterns in sheep. Appl Anim Behav Sci. (2020) 225:104964. doi: 10.1016/j.applanim.2020.104964

CrossRef Full Text | Google Scholar

148. Camerlink I, Bijma P, Kemp B, Bolhuis JE. Relationship between growth rate and oral manipulation, social nosing, and aggression in finishing pigs. Appl Anim Behav Sci. (2012) 142:11–7. doi: 10.1016/j.applanim.2012.09.004

CrossRef Full Text | Google Scholar

149. Rault JL. Be kind to others: Prosocial behaviours and their implications for animal welfare. Appl Anim Behav Sci. (2019) 210:113–23. doi: 10.1016/j.applanim.2018.10.015

CrossRef Full Text | Google Scholar

150. Šárová R, Gutmann AK, Špinka M, Stěhulová I, Winckler C. Important role of dominance in allogrooming behaviour in beef cattle. Appl Anim Behav Sci. (2016) 181:41–8. doi: 10.1016/j.applanim.2016.05.017

CrossRef Full Text | Google Scholar

151. Gygax L, Neisen G, Wechsler B. Socio-spatial relationships in dairy cows. Ethology. (2010) 116:10–23. doi: 10.1111/j.1439-0310.2009.01708.x

CrossRef Full Text | Google Scholar

152. Camerlink I, Turner SP, Ursinus WW, Reimert I, Bolhuis JE. Aggression and affiliation during social conflict in pigs. PLoS ONE. (2014) 9:1–21. doi: 10.1371/journal.pone.0113502

PubMed Abstract | CrossRef Full Text | Google Scholar

153. Biondo C, Izar P, Miyaki CY, Bussab VSR. Social structure of collared peccaries (Pecari tajacu): does relatedness matter? Behav Processes. (2014) 109:70–8. doi: 10.1016/j.beproc.2014.08.018

PubMed Abstract | CrossRef Full Text | Google Scholar

154. Podgórski T, Lusseau D, Scandura M, Sönnichsen L, J?drzejewska B. Long-lasting, kin-directed female interactions in a spatially structured wild boar social network. PLoS ONE. (2014) 9:1–11. doi: 10.1371/journal.pone.0099875

PubMed Abstract | CrossRef Full Text | Google Scholar

155. Ramos A, Manizan L, Rodriguez E, Kemp YJM, Sueur C. The social network structure of a semi-free roaming European bison herd (Bison bonasus). Behav Processes. (2019) 158:97–105. doi: 10.1016/j.beproc.2018.11.005

PubMed Abstract | CrossRef Full Text | Google Scholar

156. Kaiser S, Kirtzeck M, Hornschuh G, Sachser N. Sex-specific difference in social support - a study in female guinea pigs. Physiol Behav. (2003) 79:297–303. doi: 10.1016/S0031-9384(03)00091-X

PubMed Abstract | CrossRef Full Text | Google Scholar

157. Scheiber IBR, Kotrschal K, Weiß BM. Benefits of family reunions: social support in secondary greylag goose families. Horm Behav. (2009) 55:133–8. doi: 10.1016/j.yhbeh.2008.09.006

PubMed Abstract | CrossRef Full Text | Google Scholar

158. Schneider G, Krueger K. Third-party interventions keep social partners from exchanging affiliative interactions with others. Anim Behav. (2012) 83:377–87. doi: 10.1016/j.anbehav.2011.11.007

CrossRef Full Text | Google Scholar

159. Westenbroek C, Ter Horst GJ, Roos MH, Kuipers SD, Trentani A, Den Boer JA. Gender-specific effects of social housing in rats after chronic mild stress exposure. Prog Neuro-Psychopharmacology Biol Psychiatry. (2003) 27:21–30. doi: 10.1016/S0278-5846(02)00310-X

PubMed Abstract | CrossRef Full Text | Google Scholar

160. Brent LJN, Ruiz-Lambides A, Platt ML. Family network size and survival across the lifespan of female macaques. Proc R Soc B Biol Sci. (2017) 284:20170515. doi: 10.1098/rspb.2017.0515

PubMed Abstract | CrossRef Full Text | Google Scholar

161. Liao Z, Sosa S, Wu C, Zhang P. The influence of age on wild rhesus macaques' affiliative social interactions. Am J Primatol. (2018) 80:1–10. doi: 10.1002/ajp.22733

PubMed Abstract | CrossRef Full Text | Google Scholar

162. Norton E, Benaben S, Mbotha D, Schley D. Seasonal variations in physical contact amongst domestic sheep and the implications for disease transmission. Livest Sci. (2012) 145:34–43. doi: 10.1016/j.livsci.2011.12.017

CrossRef Full Text | Google Scholar

163. Swain DL, Patison KP, Heath BM, Bishop-Hurley GJ, Finger A. Pregnant cattle associations and links to maternal reciprocity. Appl Anim Behav Sci. (2015) 168:10–7. doi: 10.1016/j.applanim.2015.04.008

CrossRef Full Text | Google Scholar

164. Croft DP, Krause J, Darden SK, Ramnarine IW, Faria JJ, James R. Behavioural trait assortment in a social network: patterns and implications. Behav Ecol Sociobiol. (2009) 63:1495–503. doi: 10.1007/s00265-009-0802-x

CrossRef Full Text | Google Scholar

165. Díaz López B. When personality matters: personality and social structure in wild bottlenose dolphins, Tursiops truncatus. Anim Behav. (2020) 163:73–84. doi: 10.1016/j.anbehav.2020.03.001

CrossRef Full Text | Google Scholar

166. Massen JJM, Koski SE. Chimps of a feather sit together: chimpanzee friendships are based on homophily in personality. Evol Hum Behav. (2014) 35:1–8. doi: 10.1016/j.evolhumbehav.2013.08.008

CrossRef Full Text | Google Scholar

167. Morton FB, Weiss A, Buchanan-Smith HM, Lee PC. Capuchin monkeys with similar personalities have higher-quality relationships independent of age, sex, kinship and rank. Anim Behav. (2015) 105:163–71. doi: 10.1016/j.anbehav.2015.04.013

CrossRef Full Text | Google Scholar

168. Friel M, Kunc HP, Griffin K, Asher L, Collins LM. Acoustic signalling reflects personality in a social mammal. R Soc Open Sci. (2016) 3:1–9. doi: 10.1098/rsos.160178

PubMed Abstract | CrossRef Full Text

169. Turner JW, Bills PS, Holekamp KE. Ontogenetic change in determinants of social network position in the spotted hyena. Behav Ecol Sociobiol. (2018) 72:10. doi: 10.1007/s00265-017-2426-x

CrossRef Full Text | Google Scholar

170. Croft DP, Madden JR, Franks DW, James R. Hypothesis testing in animal social networks. Trends Ecol Evol. (2011) 26:502–7. doi: 10.1016/j.tree.2011.05.012

PubMed Abstract | CrossRef Full Text | Google Scholar

171. Firth JA, Sheldon BC. Experimental manipulation of avian social structure reveals segregation is carried over across contexts. Proc R Soc B. (2015) 282:20142350. doi: 10.1098/rspb.2014.2350

PubMed Abstract | CrossRef Full Text | Google Scholar

172. Firth JA, Voelkl B, Farine DRR, Sheldon BCC. Experimental evidence that social relationships determine individual foraging behavior. Curr Biol. (2015) 25:3138–43. doi: 10.1016/j.cub.2015.09.075

PubMed Abstract | CrossRef Full Text | Google Scholar

173. Firth JA, Voelkl B, Crates RA, Aplin LM, Biro D, Croft DP, et al. Wild birds respond to flockmate loss by increasing their social network associations to others. Proc R Soc B. (2017) 284:20170299. doi: 10.1098/rspb.2017.0299

PubMed Abstract | CrossRef Full Text | Google Scholar

174. Salau J, Krieter J. Analysing the space-usage-pattern of a cow herd using video surveillance and automated motion detection. Biosyst Eng. (2020) 197:122–34. doi: 10.1016/j.biosystemseng.2020.06.015

CrossRef Full Text | Google Scholar

175. Ren K, Bernes G, Hetta M, Karlsson J. Tracking and analysing social interactions in dairy cattle with real-time locating system and machine learning. J Syst Archit. (2021) 116:102139. doi: 10.1016/j.sysarc.2021.102139

CrossRef Full Text | Google Scholar

176. Oczak M, Viazzi S, Ismayilova G, Sonoda LT, Roulston N, Fels M, et al. Classification of aggressive behaviour in pigs by activity index and multilayer feed forward neural network. Biosyst Eng. (2014) 119:89–97. doi: 10.1016/j.biosystemseng.2014.01.005

CrossRef Full Text | Google Scholar

177. Fadul-Pacheco L, Liou M, Reinemann DJ, Cabrera VE. A preliminary investigation of social network analysis applied to dairy cow behavior in automatic milking system environments. Animals. (2021) 11:1229. doi: 10.3390/ani11051229

PubMed Abstract | CrossRef Full Text | Google Scholar

178. Proudfoot KL, Weary DM, LeBlanc SJ, Mamedova LK, von Keyserlingk MAG. Exposure to an unpredictable and competitive social environment affects behavior and health of transition dairy cows. J Dairy Sci. (2018) 101:9309–20. doi: 10.3168/jds.2017-14115

PubMed Abstract | CrossRef Full Text | Google Scholar

179. Jensen MB, Pedersen LJ. Using motivation tests to assess ethological needs and preferences. Appl Anim Behav Sci. (2008) 113:340–56. doi: 10.1016/j.applanim.2008.02.001

CrossRef Full Text | Google Scholar

180. Søndergaard E, Jensen MB, Nicol CJ. Motivation for social contact in horses measured by operant conditioning. Appl Anim Behav Sci. (2011) 132:131–7. doi: 10.1016/j.applanim.2011.04.007

CrossRef Full Text | Google Scholar

181. Nuñez CMV, Adelman JS, Rubenstein DI. Sociality increases juvenile survival after a catastrophic event in the feral horse (Equus caballus). Behav Ecol. (2015) 26:138–47. doi: 10.1093/beheco/aru163

CrossRef Full Text | Google Scholar

182. Büttner K, Scheffler K, Czycholl I, Krieter J. Social network analysis - centrality parameters and individual network positions of agonistic behavior in pigs over three different age levels. Springerplus. (2015) 4:1–13. doi: 10.1186/s40064-015-0963-1

PubMed Abstract | CrossRef Full Text | Google Scholar

183. Cañon Jones HA, Noble C, Damsgård B, Pearce GP. Social network analysis of the behavioural interactions that influence the development of fin damage in Atlantic salmon parr (Salmo salar) held at different stocking densities. Appl Anim Behav Sci. (2011) 133:117–26. doi: 10.1016/j.applanim.2011.05.005

CrossRef Full Text | Google Scholar

184. Foister S, Doeschl-Wilson A, Roehe R, Arnott G, Boyle L, Turner SP. Social network properties predict chronic aggression in commercial pig systems. PLoS ONE. (2018) 13:e0205122. doi: 10.1371/journal.pone.0205122

PubMed Abstract | CrossRef Full Text | Google Scholar

185. Li Y, Zhang H, Johnston LJ, Martin W. Understanding tail-biting in pigs through social network analysis. Animals. (2018) 8:1–13. doi: 10.3390/ani8010013

PubMed Abstract | CrossRef Full Text | Google Scholar

186. Duve LR, Weary DM, Halekoh U, Jensen MB. The effects of social contact and milk allowance on responses to handling, play, and social behavior in young dairy calves. J Dairy Sci. (2012) 95:6571–81. doi: 10.3168/jds.2011-5170

PubMed Abstract | CrossRef Full Text | Google Scholar

187. De Paula Vieira A, von Keyserlingk MAG, Weary DM. Presence of an older weaned companion influences feeding behavior and improves performance of dairy calves before and after weaning from milk. J Dairy Sci. (2012) 95:3218–24. doi: 10.3168/jds.2011-4821

PubMed Abstract | CrossRef Full Text | Google Scholar

188. Cloutier S, Newberry RC, Honda K, Alldredge JR. Cannibalistic behaviour spread by social learning. Anim Behav. (2002) 63:1153–62. doi: 10.1006/anbe.2002.3017

CrossRef Full Text | Google Scholar

189. Zeltner E, Klein T, Huber-Eicher B. Is there social transmission of feather pecking in groups of laying hen chicks? Anim Behav. (2000) 60:211–6. doi: 10.1006/anbe.2000.1453

PubMed Abstract | CrossRef Full Text | Google Scholar

190. Edgar JL, Paul ES, Nicol CJ. Protective mother hens: cognitive influences on the avian maternal response. Anim Behav. (2013) 86:223–9. doi: 10.1016/j.anbehav.2013.05.004

CrossRef Full Text | Google Scholar

191. Marchant-Forde JN, Marchant-Forde RM, Weary DM. Responses of dairy cows and calves to each other's vocalisations after early separation. Appl Anim Behav Sci. (2002) 78:19–28. doi: 10.1016/S0168-1591(02)00082-5

CrossRef Full Text | Google Scholar

192. Weary DM, Ross S, Fraser D. Vocalizations by isolated piglets: a reliable indicator of piglet need directed towards the sow. Appl Anim Behav Sci. (1997) 53:249–57. doi: 10.1016/S0168-1591(96)01173-2

CrossRef Full Text | Google Scholar

193. Favati A, Løvlie H, Leimar O. Effects of social experience, aggressiveness and comb size on contest success in male domestic fowl. R Soc Open Sci. (2021) 8:201213. doi: 10.1098/rsos.201213

PubMed Abstract | CrossRef Full Text | Google Scholar

194. Salazar LC, Ko HL, Yang CH, Llonch L, Manteca X, Camerlink I, et al. Early socialisation as a strategy to increase piglets' social skills in intensive farming conditions. Appl Anim Behav Sci. (2018) 206:25–31. doi: 10.1016/j.applanim.2018.05.033

CrossRef Full Text | Google Scholar

195. Ko HL, Chong Q, Escribano D, Camerlink I, Manteca X, Llonch P. Pre-weaning socialization and environmental enrichment affect life-long response to regrouping in commercially-reared pigs. Appl Anim Behav Sci. (2020) 229:105044. doi: 10.1016/j.applanim.2020.105044

CrossRef Full Text | Google Scholar

196. Lagisz M, Zidar J, Nakagawa S, Neville V, Sorato E, Paul ES, et al. Optimism, pessimism and judgement bias in animals: a systematic review and meta-analysis. Neurosci Biobehav Rev. (2020) 118:3–17. doi: 10.1016/j.neubiorev.2020.07.012

PubMed Abstract | CrossRef Full Text | Google Scholar

197. Kleinhappel TK, John EA, Pike TW, Wilkinson A, Burman OHP. Animal welfare: a social networks perspective. Sci Prog. (2016) 99:68–82. doi: 10.3184/003685016X14495640902331

PubMed Abstract | CrossRef Full Text | Google Scholar

198. Makagon MM, McCowan B, Mench JA. How can social network analysis contribute to social behavior research in applied ethology? Appl Anim Behav Sci. (2012) 138:152–61. doi: 10.1016/j.applanim.2012.02.003

PubMed Abstract | CrossRef Full Text | Google Scholar

199. Leliveld LMC, Düpjan S, Tuchscherer A, Puppe B. Behavioural and physiological measures indicate subtle variations in the emotional valence of young pigs. Physiol Behav. (2016) 157:116–24. doi: 10.1016/j.physbeh.2016.02.002

PubMed Abstract | CrossRef Full Text | Google Scholar

200. Herborn KA, McElligott AG, Mitchell MA, Sandilands V, Bradshaw B, Asher L. Spectral entropy of early-life distress calls as an iceberg indicator of chicken welfare. J R Soc Interface. (2020) 17:20200086. doi: 10.1098/rsif.2020.0086

PubMed Abstract | CrossRef Full Text | Google Scholar

201. Briefer EF, Sypherd CC-R, Linhart P, Leliveld LMC, padilla de. la Torre M, Read ER, Guérin C, Deiss V, Monestier C, Rasmussen JH, et al. Classification of pig calls produced from birth to slaughter according to their emotional valence and context of production. Sci Rep. (2022) 12:1–10. doi: 10.1038/s41598-022-07174-8

PubMed Abstract | CrossRef Full Text | Google Scholar

202. Camerlink I, Proßegger C, Kubala D, Galunder K, Rault JL. Keeping littermates together instead of social mixing benefits pig social behaviour and growth post-weaning. Appl Anim Behav Sci. (2021) 235:105230. doi: 10.1016/j.applanim.2021.105230

CrossRef Full Text | Google Scholar

203. Fredriksen B, Lium BM, Marka CH, Mosveen B, Nafstad O. Entire male pigs in farrow-to-finish pens-effects on animal welfare. Appl Anim Behav Sci. (2008) 110:258–68. doi: 10.1016/j.applanim.2007.04.007

CrossRef Full Text | Google Scholar

204. Desire S, Turner SP, D'Eath RB, Doeschl-Wilson AB, Lewis CRG, Roehe R. Analysis of the phenotypic link between behavioural traits at mixing and increased long-term social stability in group-housed pigs. Appl Anim Behav Sci. (2015) 166:52–62. doi: 10.1016/j.applanim.2015.02.015

CrossRef Full Text | Google Scholar

205. Scott JP. Critical periods in behavioral development. Science. (1962) 138:949–58. doi: 10.1126/science.138.3544.949

PubMed Abstract | CrossRef Full Text | Google Scholar

Keywords: social behavior, welfare, contest behavior, social relationships, livestock

Citation: Lee VE, Arnott G and Turner SP (2022) Social behavior in farm animals: Applying fundamental theory to improve animal welfare. Front. Vet. Sci. 9:932217. doi: 10.3389/fvets.2022.932217

Received: 29 April 2022; Accepted: 13 July 2022;
Published: 12 August 2022.

Edited by:

T. Bas Rodenburg, Utrecht University, Netherlands

Reviewed by:

Monica Padilla De La Torre, Norwegian University of Life Sciences, Norway
Jean-Loup Rault, University of Veterinary Medicine Vienna, Austria

Copyright © 2022 Lee, Arnott and Turner. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Victoria E. Lee, Victoria.Lee@sruc.ac.uk

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