Evidence map›Paper›PMID 30682060›Full record

ArticlePloS one2019

Simultaneous detection of macroevolutionary patterns in phenotypic means and rate of change with and within phylogenetic trees including extinct species.

S Castiglione, C Serio, A Mondanaro, M Di Febbraro, A Profico, G Girardi, P Raia

Abstract 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 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. True seals achieved global distribution by breaking Bergmann's rule.Evolution; international journal of organic evolution · 2022
    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

7 authors.

S CastiglioneDepartment of Earth Sciences, Environment and Resources, University of Naples Federico II, Napoli, Italy.
C SerioDepartment of Earth Sciences, Environment and Resources, University of Naples Federico II, Napoli, Italy.
A MondanaroDepartment of Earth Sciences, Environment and Resources, University of Naples Federico II, Napoli, Italy.
M Di FebbraroEnvironmetrics Lab, Department of Biosciences and Territory DiBT, University of Molise, Pesche, Italy.
A ProficoDipartimento di Biologia Ambientale, Università di Roma Sapienza, Rome, Italia.
G GirardiDepartment of Earth Sciences, Environment and Resources, University of Naples Federico II, Napoli, Italy.
P RaiaDepartment of Earth Sciences, Environment and Resources, University of Naples Federico II, Napoli, Italy.ORCID 0000-0002-4593-8006

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recognizing evolutionary trends in phenotypic means and rates requires the application of phylogenetic comparative methods (PCMs). Most PCMs are unsuited to make full use of fossil information, which is a drawback, given the inclusion of such data improves, and in some cases even corrects, the proper understanding of trait evolution. Here we present a new computer application, written in R, that allows the simultaneous computation of temporal trends in phenotypic mean and evolutionary rate along a phylogeny, and to contrast such patterns among different clades within the tree. By using simulation experiments, we show the new implementation, names search.trend is as powerful as existing PCM tools in discerning macroevolutionary patterns in phenotypic means and rates, but differently from any other PCM allows comparing individual clades to each other, and provides rich information about trait evolution for all lineages in the tree.

Indexed as

Biological EvolutionExtinction, BiologicalFossilsPhylogenyAlgorithmsComputational BiologyPhenotypeSoftware

Identifiers

PMID30682060
PMCPMC6347132

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.