Evidence map›Paper›PMID 34772963›Full record

ArticleScientific reports2021

Acoustic differentiation and classification of wild belugas and narwhals using echolocation clicks.

Marie J Zahn, Shannon Rankin, Jennifer L K McCullough, Jens C Koblitz, Frederick Archer, Marianne H Rasmussen, Kristin L Laidre

Abstract readComparative Study
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
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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

7 authors.

Marie J ZahnSchool of Aquatic and Fishery Sciences, University of Washington, 1122 NE Boat Street, Seattle, WA, 98105, USA. mzahn@uw.edu.ORCID 0000-0001-5522-8254
Shannon RankinSouthwest Fisheries Science Center, NOAA, 8901 La Jolla Shores Drive, La Jolla, CA, 92037, USA.ORCID 0000-0002-8405-5169
Jennifer L K McCulloughPacific Islands Fisheries Science Center, NOAA, 1845 Wasp Boulevard, Building 176, Honolulu, HI, 96818, USA.ORCID 0000-0003-4212-7846
Jens C KoblitzMax Planck Institute of Animal Behavior, Advanced Research Technology Unit, Konstanz, Germany.
Frederick ArcherSouthwest Fisheries Science Center, NOAA, 8901 La Jolla Shores Drive, La Jolla, CA, 92037, USA.ORCID 0000-0002-3179-4769
Marianne H RasmussenThe University of Iceland's Research Center in Húsavík, Húsavík, Iceland.ORCID 0000-0002-6887-8616
Kristin L LaidreSchool of Aquatic and Fishery Sciences, University of Washington, 1122 NE Boat Street, Seattle, WA, 98105, USA.ORCID 0000-0002-2787-650X

Funding

Office of Naval Research N00014-11-1-0201
6 · The paper itself

Abstract

Belugas (Delphinapterus leucas) and narwhals (Monodon monoceros) are highly social Arctic toothed whales with large vocal repertoires and similar acoustic profiles. Passive Acoustic Monitoring (PAM) that uses multiple hydrophones over large spatiotemporal scales has been a primary method to study their populations, particularly in response to rapid climate change and increasing underwater noise. This study marks the first acoustic comparison between wild belugas and narwhals from the same location and reveals that they can be acoustically differentiated and classified solely by echolocation clicks. Acoustic recordings were made in the pack ice of Baffin Bay, West Greenland, during 2013. Multivariate analyses and Random Forests classification models were applied to eighty-one single-species acoustic events comprised of numerous echolocation clicks. Results demonstrate a significant difference between species' acoustic parameters where beluga echolocation was distinguished by higher frequency content, evidenced by higher peak frequencies, center frequencies, and frequency minimums and maximums. Spectral peaks, troughs, and center frequencies for beluga clicks were generally > 60 kHz and narwhal clicks < 60 kHz with overlap between 40-60 kHz. Classification model predictive performance was strong with an overall correct classification rate of 97.5% for the best model. The most important predictors for species assignment were defined by peaks and notches in frequency spectra. Our results provide strong support for the use of echolocation in PAM efforts to differentiate belugas and narwhals acoustically.

Indexed as

AcousticsAnimalsBeluga WhaleEcholocationGreenlandSpecies SpecificityVocalization, AnimalWhales

Identifiers

PMID34772963
PMCPMC8589986

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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.