Evidence map›Paper›PMID 35802740›Full record

ArticlePloS one2022

An integrative phylogenetic approach for inferring relationships of fossil gobioids (Teleostei: Gobiiformes).

Christoph Gierl, Martin Dohrmann, Philippe Keith, William Humphreys, Hamid R Esmaeili, Jasna Vukić, Radek Šanda, Bettina Reichenbacher

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
5.0field-weighted citation impact, top 4% 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

1 citing paper in PubMed, 19 citations in OpenAlex.

  1. 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

8 authors at 6 institutions in 5 countries.

Christoph GierlDepartment of Earth and Environmental Sciences, Palaeontology & Geobiology, Ludwig-Maximilians-Universität München, Munich, Germany.
Martin DohrmannDepartment of Earth and Environmental Sciences, Palaeontology & Geobiology, Ludwig-Maximilians-Universität München, Munich, Germany.
Philippe KeithUMR 8067 Biologie des Organismes et Ecosystèmes Aquatiques (BOREA), Muséum National d'Histoire Naturelle, CNRS, IRD, SU, Paris, France.
William HumphreysSchool of Biological Sciences, University of Western Australia, Crawley, WA, Australia.
Hamid R EsmaeiliIchthyology and Molecular Systematics Research Laboratory, Zoology Section, Department of Biology, College of Sciences, Shiraz University, Shiraz, Iran.
Jasna VukićDepartment of Ecology, Charles University, Prague, Czech Republic.
Radek ŠandaDepartment of Zoology, National Museum, Prague, Czech Republic.
Bettina ReichenbacherDepartment of Earth and Environmental Sciences, Palaeontology & Geobiology, Ludwig-Maximilians-Universität München, Munich, Germany.ORCID 0000-0001-6678-5080
Ludwig-Maximilians-Universität München · DEAustralian Museum · AUCentre National de la Recherche Scientifique · FRCharles University · CZNational Museum · CZShiraz University · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The suborder Gobioidei is among the most diverse groups of vertebrates, comprising about 2310 species. In the fossil record gobioids date back to the early Eocene (c. 50 m.y. ago), and a considerable increase in numbers of described species is evident since the middle Miocene (c. 16 m.y. ago). About 40 skeleton-based gobioid species and > 100 otolith-based species have been described until to date. However, assignment of a fossil gobioid species to specific families has often remained tentative, even if well preserved complete specimens are available. The reasons are that synapomorphies that can be recognized in a fossil skeleton are rare (or absent) and that no phylogenetic framework applicable to gobioid fossils exists. Here we aim to overcome this problem by developing a phylogenetic total evidence framework that is suitable to place a fossil skeleton-based gobioid at family level. Using both literature and newly collected data we assembled a morphological character matrix (48 characters) for 29 extant species, representing all extant gobioid families, and ten fossil gobioid species, and we compiled a multi-gene concatenated alignment (supermatrix; 6271 bp) of published molecular sequence data for the extant species. Bayesian and Maximum Parsimony analyses revealed that our selection of extant species was sufficient to achieve a molecular 'backbone' that fully conforms to previous molecular work. Our data revealed that inclusion of all fossil species simultaneously produced very poorly resolved trees, even for some extant taxa. In contrast, addition of a single fossil species to the total evidence data set of the extant species provided new insight in its possible placement at family level, especially in a Bayesian framework. Five out of the ten fossil species were recovered in the same family as had been suggested in previous works based on comparative morphology. The remaining five fossil species had hitherto been left as family incertae sedis. Now, based on our phylogenetic framework, new and mostly well supported hypotheses to which clades they could belong can be presented. We conclude that the total evidence framework presented here will be beneficial for all future work dealing with the phylogenetic placement of a fossil skeleton-based gobioid and thus will help to improve our understanding of the evolutionary history of these fascinating fishes. Moreover, our data highlight that increased sampling of fossil taxa in a total-evidence context is not universally beneficial, as might be expected, but strongly depends on the study group and peculiarities of the morphological data.

Indexed as

FishesFossilsPhylogenyAnimalsBayes TheoremBiological EvolutionOtolithic Membrane

Identifiers

PMID35802740
PMCPMC9269936
OpenAlexW4284963606

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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.