Evidence map›Paper›PMID 29551763›Full record

ReviewZoological research2018

Species delimitation based on diagnosis and monophyly, and its importance for advancing mammalian taxonomy.

Eliécer E Gutiérrez, Guilherme S T Garbino

Abstract readReview
In one paragraph

Review in Zoological research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–field-weighted citation impact
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

13 citing papers in PubMed.

  1. Article
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  9. Deep Genotypic Species Delimitation ofJournal of fungi (Basel, Switzerland) · 2022
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  11. Article
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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.

Eliécer E GutiérrezPós-Graduação em Biodiversidade Animal, Departamento de Ecologia e Evolução, Centro de Ciências Naturais e Exatas, Universidade Federal de Santa Maria, Santa Maria, RS 97105-900, Brazil; E-mail: ee.gutierrez.bio@gmail.com.
Guilherme S T GarbinoPós-graduação, Departamento de Zoologia, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais 31270-901, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A recently proposed taxonomic classification of extant ungulates sparked a series of publications that criticize the Phylogenetic Species Concept (PSC) claiming it to be a particularly poor species concept. These opinions reiteratively stated that (1) the two fundamental elements of the "PSC", i.e., monophyly and diagnosability, do not offer objective criteria as to where the line between species should be drawn; and (2) that extirpation of populations can lead to artificial diagnosability and spurious recognitions of species. This sudden eruption of criticism against the PSC is misleading. Problems attributed to the PSC are common to most approaches and concepts that modern systematists employ to establish species boundaries. The controversial taxonomic propositions that sparked criticism against the PSC are indeed highly problematic, not because of the species concept upon which they are based, but because no evidence (whatsoever) has become public to support a substantial portion of the proposed classification. We herein discuss these topics using examples from mammals. Numerous areas of biological research rest upon taxonomic accuracy (including conservation biology and biomedical research); hence, it is necessary to clarify what are (and what are not) the real sources of taxonomic inaccuracy.

Indexed as

AnimalsExtinction, BiologicalMammalsPhylogenySpecies SpecificityAlpha taxonomyPhylogenetic Species ConceptSpecies conceptsTaxonomic inertiaTaxonomic inflation

Identifiers

PMID29551763
PMCPMC6102684

What OpenQuestion holds

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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.