Evidence map›Paper›PMID 42305578›Full record

ArticleiScience2026

Signal brevity and compression in loud calls of the white-headed langur.

Penglai Fan, Yinshu Liu, Guichuan Zeng, Ruoshuang Liu, Michael J Lawes, Qihai Zhou, Ming Li

Abstract read
In one paragraph

Article in iScience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Penglai FanKey Laboratory of Ecology of Rare and Endangered Species and Environmental Protection (Guangxi Normal University), Ministry of Education, Guilin, Guangxi, China.
Yinshu LiuKey Laboratory of Ecology of Rare and Endangered Species and Environmental Protection (Guangxi Normal University), Ministry of Education, Guilin, Guangxi, China.
Guichuan ZengKey Laboratory of Ecology of Rare and Endangered Species and Environmental Protection (Guangxi Normal University), Ministry of Education, Guilin, Guangxi, China.
Ruoshuang LiuKey Laboratory of Ecology of Rare and Endangered Species and Environmental Protection (Guangxi Normal University), Ministry of Education, Guilin, Guangxi, China.
Michael J LawesSchool of Life Sciences, University of KwaZulu-Natal, Scottsville, South Africa.
Qihai ZhouKey Laboratory of Ecology of Rare and Endangered Species and Environmental Protection (Guangxi Normal University), Ministry of Education, Guilin, Guangxi, China.
Ming LiState Key Laboratory of Animal Biodiversity Conservation and Integrated Pest Management, Institute of Zoology, Chinese Academy of Sciences, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Zipf's law of brevity and Menzerath's law are linguistic principles, predicting that coding length is minimized for optimal coding efficiency. We tested whether two linguistic laws apply to vocal communication of white-headed langurs inhabiting karst forests. Adult male white-headed langurs produce three loud call types in long-distance sequences. Frequent call types were shorter in duration, supporting Zipf's law of brevity. Patterns related to Menzerath's law were more nuanced. Inter-call intervals shortened in longer sequences, but only wahoo calls showed duration compression. Physiological constraints caused calls to shorten and intervals to lengthen later in sequences. Longer sequences contained proportionally more short snorts and fewer long roars and wahoos. Signal compression reflects a trade-off between energy cost and communication efficiency. Constant durations of snorts and roars may aid long-distance transmission and caller recognition. These findings provide evidence for signal brevity and compression under physiological limits, offering insights into vocal communication evolution in non-human primates.

Indexed as

evolutionary biologywildlife behaviorzoology

Identifiers

PMID42305578
PMCPMC13266200

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LicenceCC BY-NC
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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.