Evidence map›Paper›PMID 40251203›Full record

ArticleScientific reports2025

Fin whale song recordings by onshore seismometers open new horizons for cetacean coastal monitoring.

Martin Möllhoff, Christopher J Bean

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

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

2 authors.

Martin MöllhoffGeophysics Section, School of Cosmic Physics, Dublin Institute for Advanced Studies, 5 Merrion Square, Dublin, D02 Y006, Ireland. martin@dias.ie.
Christopher J BeanGeophysics Section, School of Cosmic Physics, Dublin Institute for Advanced Studies, 5 Merrion Square, Dublin, D02 Y006, Ireland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Fin whales, the second largest animal on Earth, produce one of the most intense vocalisations in the animal kingdom. Monitoring these songs using ocean-deployed hydrophones plays an important role in the study of fin whale distribution and social behaviour, though obtaining real-time data remains challenging. In this feasibility study we investigate if vocalising near-coastal fin whales can be widely detected and located with onshore seismometers. Inspecting data from pre-existing seismic installations we establish that fin whale song can be detected with onshore seismometers up to 5.5 km inland, across multiple marine environments, globally. Individual creatures can be located and tracked through the analysis of seismic wave properties. Furthermore, we show that citizen science seismometers, such as the affordable and widely deployed 'Raspberry Shake' devices, can reliably detect fin whale song. These instruments, often placed in coastal areas, provide real-time data, offering a cost-effective and accessible method for monitoring coastal fin whale activity. The revelation that human living spaces are ensonified by fin whale song offers the potential to enhance public engagement with the oceans and presents new opportunities for global monitoring. Fin whales are vulnerable to noise pollution, shipping strikes and entanglement in fishing gear. The use of terrestrial seismometers could improve early warning systems and contribute to richer datasets on near coastal whale vocalisations. This study demonstrates that, globally, seismic data holds significant untapped potential for near-coastal fin whale monitoring.

Indexed as

Environmental MonitoringFin WhaleVocalization, AnimalAcousticsAnimals

Identifiers

PMID40251203
PMCPMC12008217

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LicenceCC BY-NC-ND
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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.