Evidence map›Paper›PMID 35577907›Full record

ArticleScientific reports2022

Intolerant baboons avoid observer proximity, creating biased inter-individual association patterns.

Andrew T L Allan, Amy F White, Russell A Hill

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2022. 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
1.6field-weighted citation impact, top 19% of its field
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, 10 citations in OpenAlex.

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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 at 2 institutions in 2 countries.

Andrew T L AllanDepartment of Anthropology, Durham University, Dawson Building, South Road, Durham, DH1 3LE, UK. andrew.allan@durham.ac.uk.
Amy F WhitePrimate and Predator Project, Lajuma Research Centre, PO Box 522, Louis Trichardt, 0920, South Africa.
Russell A HillDepartment of Anthropology, Durham University, Dawson Building, South Road, Durham, DH1 3LE, UK.
Durham University · GBUniversity of Venda · ZA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Social network analysis is an increasingly popular tool for behavioural ecologists exploring the social organisation of animal populations. Such analyses require data on inter-individual association patterns, which in wild populations are often collected using direct observations of habituated animals. This assumes observers have no influence on animal behaviour; however, our previous work showed that individuals in a habituated group of chacma baboons (Papio ursinus griseipes) displayed consistent and individually distinct responses to observer approaches. We explored the implications of our previous findings by measuring the inter-individual association patterns of the same group of chacma baboons at different observer distances. We found a strong positive association between individual tolerance levels (towards observers) and how often an animal appeared as a neighbour to focal animals when observers were nearer, and a neutral relationship between the same variables when the observer was further away. Additionally, association matrices constructed from different observation distances were not comparable within any proximity buffer, and neither were the individual network metrics generated from these matrices. This appears to be the first empirical evidence that observer presence and behaviour can influence the association patterns of habituated animals and thus have potentially significant impacts on measured social networks.

Indexed as

Papio ursinusAnimalsPapio

Identifiers

PMID35577907
PMCPMC9110335
OpenAlexW4280642683

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

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.