Evidence map›Paper›PMID 24349150›Full record

ArticlePloS one2013

Source-sink estimates of genetic introgression show influence of hatchery strays on wild chum salmon populations in Prince William Sound, Alaska.

James R Jasper, Christopher Habicht, Steve Moffitt, Rich Brenner, Jennifer Marsh, Bert Lewis, Elisabeth Creelman Fox, Zac Grauvogel, Serena D Rogers Olive, W Stewart Grant

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
0.8field-weighted citation impact, top 24% 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

9 citing papers in PubMed, 23 citations in OpenAlex.

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  8. Eco-evolutionary dynamics, density-dependent dispersal and collective behaviour: implications for salmon metapopulation robustness.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2018
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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

10 authors at 2 institutions in 1 country.

James R JasperCommercial Fisheries Division, Alaska Department of Fish and Game, Anchorage, Alaska, United States of America.
Christopher HabichtCommercial Fisheries Division, Alaska Department of Fish and Game, Anchorage, Alaska, United States of America.
Steve MoffittCommercial Fisheries Division, Alaska Department of Fish and Game, Cordova, Alaska, United States of America.
Rich BrennerCommercial Fisheries Division, Alaska Department of Fish and Game, Cordova, Alaska, United States of America.
Jennifer MarshSchool of Fisheries and Ocean Sciences, University of Alaska Fairbanks, Juneau, Alaska, United States of America.
Bert LewisCommercial Fisheries Division, Alaska Department of Fish and Game, Anchorage, Alaska, United States of America.
Elisabeth Creelman FoxCommercial Fisheries Division, Alaska Department of Fish and Game, Anchorage, Alaska, United States of America.
Zac GrauvogelCommercial Fisheries Division, Alaska Department of Fish and Game, Anchorage, Alaska, United States of America.
Serena D Rogers OliveCommercial Fisheries Division, Alaska Department of Fish and Game, Anchorage, Alaska, United States of America.
W Stewart GrantCommercial Fisheries Division, Alaska Department of Fish and Game, Anchorage, Alaska, United States of America.
Alaska Department of Fish and Game · USUniversity of Alaska Fairbanks · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The extent to which stray, hatchery-reared salmon affect wild populations is much debated. Although experiments show that artificial breeding and culture influence the genetics of hatchery salmon, little is known about the interaction between hatchery and wild salmon in a natural setting. Here, we estimated historical and contemporary genetic population structures of chum salmon (Oncorhynchus keta) in Prince William Sound (PWS), Alaska, with 135 single nucleotide polymorphism (SNP) markers. Historical population structure was inferred from the analysis of DNA from fish scales, which had been archived since the late 1960's for several populations in PWS. Parallel analyses with microsatellites and a test based on Hardy-Weinberg proportions showed that about 50% of the fish-scale DNA was cross-contaminated with DNA from other fish. These samples were removed from the analysis. We used a novel application of the classical source-sink model to compare SNP allele frequencies in these archived fish-scales (1964-1982) with frequencies in contemporary samples (2008-2010) and found a temporal shift toward hatchery allele frequencies in some wild populations. Other populations showed markedly less introgression, despite moderate amounts of hatchery straying. The extent of introgression may reflect similarities in spawning time and life-history traits between hatchery and wild fish, or the degree that hybrids return to a natal spawning area. The source-sink model is a powerful means of detecting low levels of introgression over several generations.

Indexed as

Gene FlowAlaskaAnimalsBreedingChimeraConservation of Natural ResourcesFemaleFisheriesGenetics, PopulationGenetic VariationGenotypeMaleMicrosatellite RepeatsModels, GeneticOncorhynchus ketaPhenotype

Identifiers

PMID24349150
PMCPMC3862497
OpenAlexW2040611771

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.