Evidence map›Paper›PMID 36381396›Full record

ArticleEcology and evolution2022

Modeling the extinction risk of European butterflies and odonates.

Sophia Franke, Stefan Pinkert, Roland Brandl, Simon Thorn

Abstract read
In one paragraph

Article in Ecology and evolution, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 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

4 authors.

Sophia FrankeDepartment of Animal Ecology, Faculty of Biology Philipps-Universität Marburg Marburg Germany.ORCID https://orcid.org/0000-0002-4898-1798
Stefan PinkertDepartment of Conservation Ecology, Faculty of Biology Philipps-Universität Marburg Marburg Germany.ORCID https://orcid.org/0000-0002-8348-2337
Roland BrandlDepartment of Animal Ecology, Faculty of Biology Philipps-Universität Marburg Marburg Germany.
Simon ThornHessian Agency for Nature Conservation, Environment and Geology State Institute for the Protection of Birds Gießen Germany.ORCID https://orcid.org/0000-0002-3062-3060

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Insect populations have become increasingly threatened during the last decades due to climate change and landuse intensification. Species characteristics driving these threats remain poorly understood. Trait-based analyses provide a straight-forward approach to gain a mechanistic understanding of species' extinction risk, guiding the development of conservation strategies. We combined morphological traits and phylogenetic relationship for 332 European species of butterflies and 115 species of odonates (dragon and damselflies) to model their red list status via phylogenetically controlled ordered logistic regression. We hypothesized that extinction risk increases with increasing body volume and wing area, decreasing range size, and is larger for brighter species. All investigated traits exhibited a strong phylogenetic signal. When controlling for phylogenetic relationship, we found that extinction risk of butterflies increased with decreasing range size. The extinction risk of odonates showed no relationship with the selected traits. Our results show that there is no universal trait defining the extinction risk of our investigated insect taxa. Furthermore, evolutionary history, measured as the phylogenetically predicted part of our analyzed traits, poorly predicted extinction risk. Our study confirms the focus of conservation measures on European butterfly species with small range sizes.

Indexed as

European red listfreshwaterphylogenetic signalterrestrialtrait‐based analyses

Identifiers

PMID36381396
PMCPMC9643075

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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.