Evidence map›Paper›PMID 33514174›Full record

ArticleThe Journal of the Acoustical Society of America2021

Reduction of roadway noise in a coastal city underwater soundscape during COVID-19 confinement.

Braulio Leon-Lopez, Eduardo Romero-Vivas, Lorena Viloria-Gomora

Abstract read
In one paragraph

Article in The Journal of the Acoustical Society of America, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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.

Braulio Leon-LopezAcoustics and Signal Processing Research Group, Centro de Investigaciones Biológicas del Noroeste (CIBNOR), Avenida IPN 195, Playa Palo de Santa Rita Sur, C.P. 23096 La Paz, Baja California Sur, Mexico, USA.
Eduardo Romero-VivasAcoustics and Signal Processing Research Group, Centro de Investigaciones Biológicas del Noroeste (CIBNOR), Avenida IPN 195, Playa Palo de Santa Rita Sur, C.P. 23096 La Paz, Baja California Sur, Mexico, USA.
Lorena Viloria-GomoraPrograma de Investigación en Mamíferos Marinos, Universidad Autónoma de Baja California Sur (UABCS), Carretera al Sur km 5.5, Mezquitito, C.P. 23080 La Paz, Baja California Sur, Mexico, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Confinement due to the COVID-19 pandemic drastically reduced human activities. Underwater soundscape variations are discussed in this study, comparing a typical and confinement day in a coastal lagoon near a popular tourist city in Mexico. Recording devices were located at 2 m in depth and 430 m away from the main promenade-a two-way avenue for light vehicle traffic-where main tourist infrastructure is located. The nearby marine environment is habitat to birds and dolphins as well as fish and invertebrates of commercial importance. Medium and small boats usually transit the area. The main underwater sound level reduction was measured at low frequencies (10-2000 Hz) because of the decrease in roadway noise. Vessel traffic also decreased by almost three quarters, although the level reduction due to this source was less noticeable. As typical day levels in the roadway noise band can potentially mask fish sounds and affect other low frequency noise-sensitive marine taxa, this study suggests that comprehensive noise analysis in coastal marine environments should consider the contribution from nearby land sources.

Indexed as

Motor VehiclesAnimalsCOVID-19Environmental MonitoringFishesHumansMexicoNoiseOceans and SeasQuarantineSound Spectrography

Identifiers

PMID33514174
PMCPMC7857497

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.