Evidence map›Paper›PMID 31430331›Full record

ArticlePloS one2019

Resource polymorphism in European whitefish: Analysis of fatty acid profiles provides more detailed evidence than traditional methods alone.

Stephen M Thomas, Martin J Kainz, Per-Arne Amundsen, Brian Hayden, Sami J Taipale, Kimmo K Kahilainen

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2019. 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
2.8field-weighted citation impact, top 10% 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

3 citing papers in PubMed, 16 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

6 authors at 6 institutions in 5 countries.

Stephen M ThomasDepartment of Fish Ecology and Evolution, EAWAG Swiss Federal Institute of Aquatic Science and Technology, Center for Ecology, Evolution and Biogeochemistry, Kastanienbaum, Switzerland.ORCID 0000-0001-5125-691X
Martin J KainzWasserCluster Lunz - Inter-University Centre for Aquatic Ecosystem Research, Aquatic Lipid and Ecotoxicology Research Group (LIPTOX), Lunz am See, Austria.ORCID 0000-0002-2388-1504
Per-Arne AmundsenFaculty of Biosciences, Fisheries and Economics, Department of Arctic and Marine Biology, UiT The Arctic University of Norway, Tromsø, Norway.
Brian HaydenCanadian Rivers Institute, Biology Department, University of New Brunswick, Fredericton, New Brunswick, Canada.
Sami J TaipaleDepartment of Biological and Environmental Science, University of Jyväskylä, Jyväskylä, Finland.
Kimmo K KahilainenInland Norway University of Applied Sciences, Department of Forestry and Wildlife Management, Koppang, Norway.
Swiss Federal Institute of Aquatic Science and Technology · CHUiT The Arctic University of Norway · NOUniversity of Inland Norway · NOUniversity of Jyväskylä · FIUniversity of New Brunswick · CAWasser Cluster Lunz · AT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Resource polymorphism-whereby ancestral generalist populations give rise to several specialised morphs along a resource gradient-is common where species colonise newly formed ecosystems. This phenomenon is particularly well documented in freshwater fish populations inhabiting postglacial lakes formed at the end of the last ice age. However, knowledge on how such differential exploitation of resources across contrasting habitats might be reflected in the biochemical compositions of diverging populations is still limited, though such patterns might be expected. Here, we aimed to assess how fatty acids (FA)-an important biochemical component of animal tissues-diverged across a polymorphic complex of European whitefish (Coregonus lavaretus) and their closely related monomorphic specialist congener vendace (Coregonus albula) inhabiting a series of six subarctic lakes in northern Fennoscandia. We also explored patterns of FA composition in whitefish's predators and invertebrate prey to assess how divergence in trophic ecology between whitefish morphs would relate to biochemical profiles of their key food web associates. Lastly, we assessed how information on trophic divergence provided by differential FA composition compared to evidence of resource polymorphism retrieved from more classical stomach content and stable isotopic (δ13C, δ15N) information. Examination of stomach contents provided high-resolution information on recently consumed prey, whereas stable isotopes indicated broad-scale patterns of benthic-pelagic resource use differentiation at different trophic levels. Linear discriminant analysis based on FA composition was substantially more successful in identifying whitefish morphs and their congener vendace as distinct groupings when compared to the other two methods. Three major FA (myristic acid, stearic acid, and eicosadienoic acid) proved particularly informative, both in delineating coregonid groups, and identifying patterns of pelagic-benthic feeding throughout the wider food web. Myristic acid (14:0) content and δ13C ratios in muscle tissue were positively correlated across fish taxa, and together provided the clearest segregation of fishes exploiting contrasting pelagic and benthic niches. In general, our findings highlight the potential of FA analysis for identifying resource polymorphism in animal populations where this phenomenon occurs, and suggest that this technique may provide greater resolution than more traditional methods typically used for this purpose.

Indexed as

Food ChainAnimalsFatty AcidsFeeding BehaviorGastrointestinal ContentsLakesNutritive ValueSalmonidaeScandinavian and Nordic CountriesFatty Acids

Identifiers

PMID31430331
PMCPMC6701781
OpenAlexW2969258598

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.