Evidence map›Paper›PMID 29563949›Full record

ArticleFrontiers in zoology2018

Raven food calls indicate sender's age and sex.

Markus Boeckle, Georgine Szipl, Thomas Bugnyar

Abstract read
In one paragraph

Article in Frontiers in zoology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Article
  5. Waste Disposal Sites as All-You-Can Eat Buffets for Carrion Crows (Animals : an open access journal from MDPI · 2019
    Article
  6. Review
  7. Article
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.

Markus Boeckle1Department of Cognitive Biology, University of Vienna, Vienna, Austria.ORCID 0000-0002-0738-2764
Georgine Szipl1Department of Cognitive Biology, University of Vienna, Vienna, Austria.
Thomas Bugnyar1Department of Cognitive Biology, University of Vienna, Vienna, Austria.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAcoustic parameters of animal signals have been shown to correlate with various phenotypic characteristics of the sender. These acoustic characteristics can be learned and categorized and thus are a basis for perceivers' recognition abilities. One of the most demanding capacities is individual recognition, achievable only after repeated interactions with the same individual. Still, class-level recognition might be potentially important to perceivers who have not previously encountered callers but can classify unknown individuals according to the already learned categories. Especially for species with high fission-fusion dynamics that repeatedly encounter unknown individuals it may be advantageous to develop class-level recognition. We tested whether frequency-, temporal-, and amplitude-related acoustic parameters of vocalizations emitted by ravens, a species showing high fission-fusion dynamics in non-breeder aggregations, are connected to phenotypic characteristics and thus have the potential for class-level recognition.

resultsThe analysis of 418 food calls revealed that some components summarizing acoustic parameters were differentiated by age-classes and sex.

conclusionsTogether, the results provide evidence for the co-variation of vocal characteristics and respective sex and age categories, a prerequisite for class-level recognition in perceivers. Perceivers that are ignorant of the caller's identity can thus potentially recognize these class-level differences for decision-making processes in feeding contexts.

Indexed as

Acoustic characteristicsAgeBioacousticsCall productionCorvidCorvus coraxFood callRavenSexVocalization

Identifiers

PMID29563949
PMCPMC5848575

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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.