Show simple item record

Files in this item


Item metadata

dc.contributor.authorMielke, Alexander
dc.contributor.authorCrockford, Catherine
dc.contributor.authorWittig, Roman M
dc.identifier.citationMielke , A , Crockford , C & Wittig , R M 2020 , ' Predictability and variability of association patterns in sooty mangabeys ' , Behavioral Ecology and Sociobiology , vol. 74 , no. 4 , 46 .
dc.identifier.otherPURE: 276614348
dc.identifier.otherPURE UUID: 9c24daf6-c612-4b0d-8793-88dbc12a0360
dc.identifier.otherBibtex: mielke2020predictability
dc.identifier.otherScopus: 85082529305
dc.descriptionOpen access funding provided by Projekt DEAL. AM, CC, and RMW were supported by the Max Planck Society; AM was supported by the Wenner Gren Foundation (Grant Number 9095); CC was supported by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement no. 679787). Research at the Taï Chimpanzee Project has been funded by the Max Planck Society since 1997.en
dc.description.abstractIn many group-living animal species, interactions take place in changing social environments, increasing the information processing necessary to optimize social decision-making. Communities with different levels of spatial and temporal cohesion should differ in the predictability of association patterns. While the focus in this context has been on primate species with high fission-fusion dynamics, little is known about the variability of association patterns in species with large groups and high temporal cohesion, where group size and the environment create unstable subgroups. Here, we use sooty mangabeys as a model species to test predictability on two levels: on the subgroup level and on the dyadic level. Our results show that the entirety of group members surrounding an individual is close to random in sooty mangabeys; making it unlikely that individuals can predict the exact composition of bystanders for any interaction. At the same time, we found predictable dyadic associations based on assortative mixing by age, kinship, reproductive state in females, and dominance rank; potentially providing individuals with the ability to partially predict which dyads can be usually found together. These results indicate that animals living in large cohesive groups face different challenges from those with high fission-fusion dynamics, by having to adapt to fast-changing social contexts, while unable to predict who will be close-by in future interactions. At the same time, entropy measures on their own are unable to capture the predictability of association patterns in these groups.
dc.relation.ispartofBehavioral Ecology and Sociobiologyen
dc.rightsCopyright The Author(s) 2020. Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.en
dc.subjectSocial systemen
dc.subjectFission fusionen
dc.subjectSooty Mangabeyen
dc.subjectSocial complexityen
dc.subjectBF Psychologyen
dc.titlePredictability and variability of association patterns in sooty mangabeysen
dc.typeJournal articleen
dc.description.versionPublisher PDFen
dc.contributor.institutionUniversity of St Andrews. School of Psychology and Neuroscienceen
dc.description.statusPeer revieweden

This item appears in the following Collection(s)

Show simple item record