Evidence map›Paper›PMID 40078690›Full record

ReviewCambridge prisms. Extinction2023

Extinction and morphospace occupation: A critical review.

P David Polly

Abstract readReview
In one paragraph

Review in Cambridge prisms. Extinction, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. 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

1 author.

P David PollyEarth & Atmospheric Sciences, Biology, and Anthropology, Indiana University, Bloomington, IN 47405, USA.ORCID https://orcid.org/0000-0001-7338-8526

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Processes of extinction, especially selectivity, can be studied using the distribution of species in morphospace. Random extinction reduces the number of species but has little effect on the range of morphologies or ecological roles in a fauna or flora. In contrast, selective extinction culls species based on their functional relationship to the altered environment and, therefore, to their position within a morphospace. Analysis of the distribution of extinctions within morphospaces can thus help understand whether the drivers of the extinction are linked to functional traits. Current approaches include measuring changes in disparity, mean morphology, or evenness between pre- and post-extinction morphologies. Not all measurements are straightforward, however, because morphospaces may be non-metric or non-linear in ways that can mislead interpretation. Dimension-reduction techniques like principal component analysis - commonly used with highly multivariate geometric morphometric data sets - have properties that can make the center of morphospace falsely appear to be densely populated, can make selective extinctions appear randomly distributed, or can make a group of non-specialized morphologies appear to be extreme outliers. Applying fully multivariate metrics and statistical tests will prevent most misinterpretations, as will making explicit functional connections between morphology and the underlying extinction processes.

Indexed as

Background extinctionbiodiversityextinction riskfunctional extinctionmass extinction

Identifiers

PMID40078690
PMCPMC11895730

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.