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dc.contributor.authorFoister, Simone
dc.contributor.authorDoeschl-Wilson, Andrea
dc.contributor.authorRoehe, Rainer
dc.contributor.authorArnott, Gareth
dc.contributor.authorBoyle, Laura
dc.contributor.authorTurner, Simon
dc.date.accessioned2019-09-17T16:22:32Z
dc.date.available2019-09-17T16:22:32Z
dc.date.issued2018-10-04
dc.identifier.citationFoister S, Doeschl-Wilson A, Roehe R, Arnott G, Boyle L, Turner S (2018) Social network properties predict chronic aggression in commercial pig systems. PLoS ONE 13(10): e0205122. https://doi.org/10.1371/journal.pone.0205122en_US
dc.identifier.issn1932-6203
dc.identifier.urihttp://hdl.handle.net/11019/1791
dc.descriptionpeer-revieweden_US
dc.description.abstractPost-mixing aggression in pigs is a harmful and costly behaviour which negatively impacts both animal welfare and farm efficiency. There is vast unexplained variation in the amount of acute and chronic aggression that dyadic behaviours do not fully explain. This study hypothesised that certain pen-level network properties may improve prediction of lesion outcomes due to the incorporation of indirect social interactions that are not captured by dyadic traits. Utilising current SNA theory, we investigate whether pen-level network properties affect the number of aggression-related injuries at 24 hours and 3 weeks post-mixing (24hr-PM and 3wk-PM). Furthermore we compare the predictive value of network properties to conventional dyadic traits. A total of 78 pens were video recorded for 24hr post-mixing. Each aggressive interaction that occurred during this time period was used to construct the pen-level networks. The relationships between network properties at 24hr and the pen level injuries at 24hr-PM and 3wk-PM were analysed using mixed models and verified using permutation tests. The results revealed that network properties at 24hr could predict long term aggression (3wk-PM) better than dyadic traits. Specifically, large clique formation in the first 24hr-PM predicted fewer injuries at 3wk-PM and high betweenness centralisation at 24hr-PM predicted increased rates of injury at 3wk-PM. This study demonstrates that network properties present during the first 24hr-PM have predictive value for chronic aggression, and have potential to allow identification and intervention for at risk groups.en_US
dc.language.isoenen_US
dc.publisherPublic Library of Science (PLoS)en_US
dc.relation.ispartofseriesPLoS ONE;Vol. 13 (10)
dc.rightsAttribution-NonCommercial-ShareAlike 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/us/*
dc.subjectpig systemsen_US
dc.subjectaggressionen_US
dc.subjectSNA theoryen_US
dc.subjectSwineen_US
dc.subjectAnimal behaviouren_US
dc.subjectpen-level network propertiesen_US
dc.titleSocial network properties predict chronic aggression in commercial pig systemsen_US
dc.typeArticleen_US
dc.identifier.doihttps://doi.org/10.1371/journal.pone.0205122
dc.contributor.sponsorTeagasc Walsh Fellowship Programmeen_US
dc.contributor.sponsorScottish Governmenten_US
dc.contributor.sponsorGrantNumber2015004en_US
dc.source.volume13
dc.source.issue10
dc.source.beginpagee0205122
refterms.dateFOA2019-09-17T16:22:33Z


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