Complex contests and the influence of aggressiveness in pigs

Camerlink, Irene; Arnott, Gareth; Farish, Marianne; Turner, Simon P.

doi:10.1016/j.anbehav.2016.08.021

Cited by 47 publications

(42 citation statements)

References 40 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Within contests, recent studies in juvenile pigs Sus scrofa indicate that individual aggressiveness may be a signal of intent to escalate interactions to fighting, but is not always a predictor of who “wins” in contests, and, therefore, not necessarily a component of resource holding potential (Camerlink et al., ). Aggression is also not necessary to “win” a competitive interaction, as many other non‐contact agonistic behaviours, such as displays, can be involved (Camerlink, Arnott, Farish, & Turner, ). Alternatively, different environments may select for different phenotypes depending on resource attributes.…”

Section: Discussionmentioning

confidence: 99%

“…While aggression may reflect competitive ability, the increasing costs associated with increasing density ultimately lead to reduced survival. Additionally, given the other factors that can influence aggression, such as an individual's personality (Bell et al., ; Briffa, Sneddon, & Wilson, ) and the social environment (Camerlink et al., ; Farine et al., ), the hypotheses derived from resource defence theory may offer an oversimplified understanding of aggression. Although changes in density and frequency of strains occurred over the duration of the period of limited resources, it is the density and frequency at the beginning that was most important.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Experimental evidence that density mediates negative frequency‐dependent selection on aggression

Kilgour

McAdam

Betini

et al. 2018

Journal of Animal Ecology

View full text Add to dashboard Cite

Aggression can be beneficial in competitive environments if aggressive individuals are more likely to access resources than non-aggressive individuals. However, variation in aggressive behaviour persists within populations, suggesting that high levels of aggression might not always be favoured. The goal of this study was to experimentally assess the effects of population density and phenotypic frequency on selection on aggression in a competitive environment. We compared survival of two strains of Drosophila melanogaster that differ in aggression across three density treatments and five frequency treatments (single strain groups, equal numbers of each strain and strains mixed at 3:1 and 1:3 ratios) during a period of limited resources. While there was no difference in survival across single-strain treatments, survival was strongly density dependent, with declining survival as density increased. Furthermore, at medium and high densities, there was evidence of negative frequency-dependent selection, where rare strains experienced greater survival than common strains. However, there was no evidence of negative frequency-dependent selection at low density. Our results indicate that the benefits of aggression during periods of limited resources can depend on the interaction between the phenotypic composition of populations and population density, both of which are mechanisms that could maintain variation in aggressive behaviours within natural populations.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Experimental evidence that density mediates negative frequency‐dependent selection on aggression

Kilgour

McAdam

Betini

et al. 2018

Journal of Animal Ecology

View full text Add to dashboard Cite

show abstract

“…In addition to the different approaches to define significant dyadic interactions, it also has to be considered that different behaviours also have a different meaning during the establishment of social relationships between animals. In literature, different levels of contest escalation are defined in order to evaluate the intensity of the aggressive behaviour: from display or threat to pushing without damaging, followed by biting which then escalates to fights illustrating the highest level of escalation (Ewbank and Bryant, 1972;Camerlink et al, 2016). Especially threatening behaviour without physical contact between the contestants is often excluded from the analyses as it was done in the present study.…”

Section: Determination Of Significant Dyadsmentioning

confidence: 99%

“…Here, agonistic interactions may end without escalating into a severe fight or even before the opponents have physical contact with each other (i.e. non-damaging threat) (Jensen, 1982;Camerlink et al, 2016). Hence, it might be advantageous to include more subtle behavioural patterns in the ethogram for a more detailed picture of the behaviour.…”

Section: Determination Of Significant Dyadsmentioning

confidence: 99%

Social network analysis in pigs: impacts of significant dyads on general network and centrality parameters

Büttner

Czycholl

Mees

et al. 2020

Animal

View full text Add to dashboard Cite

In general, one animal is considered dominant over another animal if it has won more fights than its opponent. Whether this difference in won and lost fights is significant is neglected in most studies. Thus, the present study evaluates the impact of two different calculation methods for dyadic interactions with a significant asymmetric outcome on the results of social network analysis regarding agonistic interactions of pigs in three different mixing events (weaned piglets, fattening pigs and gilts). Directly after mixing, all animals were video recorded for 17 (fattening pigs, gilts) and 28 h (weaned piglets), documenting agonistic interactions. Two calculation methods for significant dyads, that is, dyadic interactions with a clear dominant subordinate relationship in which one animal has won significantly more fights than its encounter, were proposed: pen individual limits were calculated by a sign test considering the differences of won and lost fights of all dyadic interactions in each pen; dyad individual limits were determined by a one-sided sign test for each individual dyad. For all data sets (ALL, including all dyadic interactions; PEN or DYAD, including only significant dyads according to pen or dyad individual limits), networks were built based on the information of initiator and receiver with the pigs as nodes and the edges between them illustrating attacks. General network parameters describing the whole network structure and centrality parameters describing the position of each animal in the network were calculated. Both pen and dyad individual limits revealed only a small percentage of significant dyads for weaned piglets (12.4% or 8.8%), fattening pigs (4.2% or 0.6%) and gilts (3.6% or 0.4%). The comparison between the data sets revealed only high Spearman’s rank correlation coefficients (rS) for the density, that is, percentage of possible edges that were actually present in the network, whereas the centrality parameters showed only moderate rS values (0.37 to 0.75). Thus, the rank order of the animals changed due to the exclusion of insignificant dyads, which shows that the results obtained from social network analysis are clearly influenced if insignificant dyads are excluded from the analyses. Due to the fact that the pen individual limits consider the overall level of agonistic interactions within each pen, this calculation method should be preferred over the dyad individual limits. Otherwise, too many animals in the group became isolated nodes with zero centrality for which no statement about their position within the network can be made.

show abstract

“…Two typical behavioural coping styles are observed: an aggressive and (pro)active coping style, and a non-aggressive and passive coping style (e.g. Bolhuis et al, 2005b;Camerlink et al, 2016;Koolhaas et al, 1999). Although the effect of coping styles on feeding patterns in pigs has hardly been studied, typical behaviour associated with coping styles might explain variation in feeding, social interaction and growth patterns in pigs.…”

Section: Introductionmentioning

confidence: 99%

Simulating pigs : Understanding their motivations, behaviour, welfare and productivity

Boumans¹

View full text Add to dashboard Cite

The transition towards sustainable pig production systems is receiving increasing attention nowadays. Pig behaviour plays a central role in sustainability, as it is an important indicator for pig welfare and can also affect other sustainability issues. Understanding behaviour and related welfare consequences requires to understand motivations underlying behaviour. The two aims of this thesis were: 1) to assess the use of agent-based modelling for understanding pig behaviour and underlying motivation, and 2) to apply agent-based modelling for increasing our understanding of pig behaviour, and related animal welfare and productivity performance. We first explored the use of agent-based modelling with tail biting behaviour in pigs as a case study. An agent-based model was developed to understand the causation of tail biting behaviour. Subsequently, we developed a mechanistic and dynamic simulation model to gain more understanding of feeding behaviour and internal (physiological) factors. The model integrates knowledge from physiology and ethology, and combines growth with a behavioural decision model based on motivation. This model included motivations underlying feeding behaviour and various feeding patterns of an individually housed growing pig. To deepen our understanding of mechanisms underlying feeding patterns of pigs within 24 hours, hormonal circadian rhythms were included in the model in a follow-up study. The circadian rhythms of cortisol and melatonin explained the alternans pattern, a small peak of feed intake at the beginning of the day and a larger peak at the end of the day, of feeding in pigs. Next, an agent-based model of feeding and social interaction in commercially group-housed pigs was developed to deepen our understanding of the complex interaction between internal physiological factors and external social factors. Social factors (e.g. competition level and social facilitation) and behavioural strategies (e.g. avoidance and approach) affected social interactions among pigs and feeding behaviour. The causation of variation among pigs was further explored in this model. Pig characteristics were important in various feeding, social interaction and growth patterns in pigs. In general, agent-based modelling proved to be a useful method to understand animal behaviour and underlying motivations. It contributed to further understanding of tail biting, feeding and social behaviour in pigs. Furthermore, agent-based modelling showed to be a novel method to find and assess behaviours as welfare indicators, and to contribute to understanding trade-offs and synergies between sustainability issues, such as animal welfare and productivity. Contents Chapter 1 General introduction Chapter 2 Agent-based modelling in applied ethology: An exploratory case study of behavioural dynamics in tail biting in pigs Chapter 3 Understanding feeding patterns in growing pigs by modelling growth and motivation Chapter 4 The importance of hormonal circadian rhythms in daily feeding patterns: An illustration in simulated pigs Cha...

show abstract

Complex contests and the influence of aggressiveness in pigs

Cited by 47 publications

References 40 publications

Experimental evidence that density mediates negative frequency‐dependent selection on aggression

Experimental evidence that density mediates negative frequency‐dependent selection on aggression

Social network analysis in pigs: impacts of significant dyads on general network and centrality parameters

Simulating pigs : Understanding their motivations, behaviour, welfare and productivity

Contact Info

Product

Resources

About