Evidence map›Paper›PMID 31827838›Full record

ArticleRoyal Society open science2019

The effects of vessel noise on the communication network of humpback whales.

Rebecca A Dunlop

Open access · goldAbstract read
In one paragraph

Article in Royal Society open science, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.4field-weighted citation impact, top 11% 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

6 citing papers in PubMed, 29 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

1 author at 1 institution in 1 country.

Rebecca A DunlopCetacean Ecology and Acoustics Laboratory, School of Veterinary Science, University of Queensland, Gatton Campus, Gatton, Queensland 4343, Australia.ORCID 0000-0002-0427-6317
The University of Queensland · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Humpback whales rely on acoustic communication to mediate social interactions. The distance to which these social signals propagate from the signaller defines its communication space, and therefore communication network (number of potential receivers). As humpback whales migrate along populated coastlines, they are likely to encounter noise from vessel traffic which will mask their social signals. Since no empirical data exist on baleen whale hearing, the consequences of this are usually assumed, being the modelled reduction in their communication space. Here, the communication space and network of migrating humpback whales was compared in increasing wind-dominated and vessel-dominated noise. Behavioural data on their social interactions were then used to inform these models. In typical wind noise, a signaller's communication space was estimated to extend to 4 km, which agreed with the maximum separation distance between groups that socially interacted. An increase in vessel noise reduced the modelled communication area, along with a significant reduction in group social interactions, probably due to a reduction in their communication network. However, signal masking did not fully explain this change in social behaviour, implying there was also an additional effect of the physical presence of the vessel on signaller and receiver behaviour. Though these observed changes in communication space and social behaviour were likely to be short term and localized, an increase in vessel activity due to tourism and coastal population growth may cause more sustained changes along the humpback whale migration paths.

Indexed as

acoustic communicationactive spaceanthropogenic noisehumpback whalemasking

Identifiers

PMID31827838
PMCPMC6894609
OpenAlexW2990931177

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.