Evidence map›Paper›PMID 35003932›Full record

ArticlePeerJ2021

Variation in global distribution, population structures, and demographic history for four

Hsiu-Chin Lin, Chia-Jung Tsai, Hui-Yu Wang

Open access · goldAbstract read
In one paragraph

Article in PeerJ, 2021. 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
1.9field-weighted citation impact, top 15% 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, 12 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

3 authors at 2 institutions in 1 country.

Hsiu-Chin LinDepartment of Marine Biotechnology and Resources, National Sun Yat-sen University, Kaohsiung, Taiwan.
Chia-Jung TsaiDepartment of Marine Biotechnology and Resources, National Sun Yat-sen University, Kaohsiung, Taiwan.
Hui-Yu WangInstitute of Oceanography, National Taiwan University, Taipei, Taiwan.
National Sun Yat-sen University · TWNational Taiwan University · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSpecies-specific information on distribution and demographic patterns provides important implications for conservation and fisheries management. However, such information is often lacking for morphologically-similar species, which may lead to biases in the assessments of these species and even decrease effort towards sustainable management. Here, we aimed to uncover the distribution range, population structure and demographic history for four exploited

methodsWe chose the widely available mitochondrial 16S ribosomal RNA (16S) as the genetic marker for cutlassfishes. We compiled the 16S sequence data from both the GenBank and a survey of trawler catch samples along the NW Pacific coasts 22-39°N. Genealogical relationships within each species was visualized with haplotype networks and potential population differentiations were further evaluated with AMOVA. Demographic histories were estimated using neutrality test, mismatch analysis, and the Bayesian skyline plot. The reconstructed phylogenetic trees were used to delimit and estimate the divergence time of species and included populations.

resultsIn each of two cosmopolitan species, MAIN

conclusionsThe demographic history revealed by our genetic analyses advances understanding of the current distribution and population structure for these congeneric species. Moreover, the uncovered population structure provides insight into the assessment and management of these species. Such information complements contemporary knowledge about these species and enables us to forecast their ability to resist future environmental and anthropogenic disturbances.

Indexed as

16SBentho-pelagicCutlassfishFish stockNW PacificPleistocenePopulation expansion

Identifiers

PMID35003932
PMCPMC8684317
OpenAlexW4200213007

What OpenQuestion holds

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LicenceCC BY
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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.