Evidence map›Paper›PMID 21455608›Full record

ArticleEcotoxicology (London, England)2011

Directional genetic selection by pulp mill effluent on multiple natural populations of three-spined stickleback (Gasterosteus aculeatus).

Emma E Lind, Mats Grahn

Abstract read
In one paragraph

Article in Ecotoxicology (London, England), 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

12 citing papers in PubMed.

  1. Long-term environmental stability does not erode plasticity in nest building responses to changing ambient conditions.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2023
    Article
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  5. Adaptive capabilities and fitness consequences associated with pollution exposure in fish.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2017
    Review
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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

2 authors.

Emma E LindSchool of Life Sciences, Södertörn University, 141 89 Huddinge, Sweden. emma.lind@sh.se
Mats Grahn

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Contamination can cause a rapid environmental change which may require populations to respond with evolutionary changes. To evaluate the effects of pulp mill effluents on population genetics, we sampled three-spined sticklebacks (Gasterosteus aculeatus) near four pulp mills and four adjacent reference sites and analyzed Amplified Fragment Length Polymorphism (AFLP) to compare genetic variability. A fine scale genetic structure was detected and samples from polluted sites separated from reference sites in multidimensional scaling plots (P<0.005, 1000 permutations) and locus-by-locus Analysis of Molecular Variance (AMOVA) further confirmed that habitats are significantly separated (F(ST)=0.021, P<0.01, 1023 permutations). The amount of genetic variation between populations did not differ between habitats, and populations from both habitats had similar levels of heterozygosity (polluted sites Nei's Hs=0.11, reference sites Nei's Hs=0.11). Still, pairwise F(ST): s between three, out of four, pairs of polluted-reference sites were significant. A F(ST)-outlier analysis showed that 21 (8.4%) loci were statistically different from a neutral distribution at the P<0.05 level and therefore indicated to be under divergent selection. When removing 13 F(ST)-outlier loci, significant at the P<0.01 level, differentiation between habitats disappeared in a multidimensional scaling plot. In conclusion, pulp mill effluence has acted as a selective agent on natural populations of G. aculeatus, causing a convergence in genotype composition change at multiple sites in an open environment.

Indexed as

Genetic VariationSelection, GeneticAmplified Fragment Length Polymorphism AnalysisAnalysis of VarianceAnimalsBiological EvolutionEcosystemGenotypeSmegmamorphaSwedenWater Pollutants, ChemicalWater Pollutants, Chemical

Identifiers

PMID21455608
PMCPMC3081435

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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.