Evidence map›Paper›PMID 30242533›Full record

ArticlePrimates; journal of primatology2019

Social style and resilience of macaques' networks, a theoretical investigation.

Ivan Puga-Gonzalez, Sebastian Sosa, Cedric Sueur

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Article in Primates; journal of primatology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Ivan Puga-GonzalezInstitute for Religion, Philosophy and History, University of Agder, Kristiansand, Norway. ivanpuga@gmail.com.ORCID http://orcid.org/0000-0003-2510-6760
Sebastian SosaSchool of Sociology and Anthropology, Sun Yat-sen University, Guangzhou, 510275, China.
Cedric SueurUniversité de Strasbourg, CNRS, IPHC, UMR 7178, Strasbourg, France.

Funding

ANR programme Blanc ANR-15-CE36-0005-01ANR programme Blanc HANCCNRS PICS program 7455
6 · The paper itself

Abstract

Group-living animals rely on efficient transmission of information for optimal exploitation of their habitat. How efficient and resilient a network is depend on its structure, which is a consequence of the social interactions of the individuals that comprise the network. In macaques, network structure differs according to dominance style. Networks of intolerant species are more modular, more centralized, and less connected than those of tolerant ones. Given these structural differences, networks of intolerant species are potentially more vulnerable to fragmentation and decreased information transmission when central individuals disappear. Here we studied network resilience and efficiency in artificial societies of macaques. The networks were produced with an individual-based model that has been shown to reproduce the structural features of networks of tolerant and intolerant macaques. To study network resilience, we deleted either central individuals or individuals at random and studied the effects of these deletions on network cohesiveness and efficiency. The deletion of central individuals had more negative effects than random deletions from the networks of both tolerant and intolerant artificial societies. Central individuals thus appeared to aid in the maintenance of network cohesiveness and efficiency. Further, the networks of both intolerant and tolerant societies appeared to be robust to the loss of individuals, as network fragmentation was never observed. Our results suggest that despite differences in network structure, networks of tolerant and intolerant macaques may be equally resilient.

Indexed as

Behavior, AnimalMacacaSocial BehaviorSocial NetworkingAggressionAnimalsFemaleMaleSocial DominanceDespoticEgalitarianIndividual-based modelsMacaquesNetwork resilienceSocial networks

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.