Evidence map›Paper›PMID 32879314›Full record

ArticleNature communications2020

Rare and common vertebrates span a wide spectrum of population trends.

Gergana N Daskalova, Isla H Myers-Smith, John L Godlee

Abstract read
In one paragraph

Article in Nature communications, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.

0numbers the graph read from it
0cells of the map it votes in
35citing 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

35 citing papers in PubMed.

  1. Article
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  14. Maximum temperatures determine the habitat affiliations of North American mammals.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  15. Article
  16. Article
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  18. Looking back on biodiversity change: lessons for the road ahead.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2023
    Review
  19. Article
  20. Review
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

3 authors.

Gergana N DaskalovaSchool of GeoSciences, University of Edinburgh, Edinburgh, EH9 3FF, Scotland, UK. gndaskalova@gmail.com.ORCID http://orcid.org/0000-0002-5674-5322
Isla H Myers-SmithSchool of GeoSciences, University of Edinburgh, Edinburgh, EH9 3FF, Scotland, UK.ORCID http://orcid.org/0000-0002-8417-6112
John L GodleeSchool of GeoSciences, University of Edinburgh, Edinburgh, EH9 3FF, Scotland, UK.ORCID http://orcid.org/0000-0001-5595-255X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Earth's biota is changing over time in complex ways. A critical challenge is to test whether specific biomes, taxa or types of species benefit or suffer in a time of accelerating global change. We analysed nearly 10,000 abundance time series from over 2000 vertebrate species part of the Living Planet Database. We integrated abundance data with information on geographic range, habitat preference, taxonomic and phylogenetic relationships, and IUCN Red List Categories and threats. We find that 15% of populations declined, 18% increased, and 67% showed no net changes over time. Against a backdrop of no biogeographic and phylogenetic patterning in population change, we uncover a distinct taxonomic signal. Amphibians were the only taxa that experienced net declines in the analysed data, while birds, mammals and reptiles experienced net increases. Population trends were poorly captured by species' rarity and global-scale threats. Incorporation of the full spectrum of population change will improve conservation efforts to protect global biodiversity.

Indexed as

BiodiversityVertebratesAmphibiansAnimalsClimate ChangeConservation of Natural ResourcesEcosystemExtinction, BiologicalPopulation Dynamics

Identifiers

PMID32879314
PMCPMC7468135

What OpenQuestion holds

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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.