Evidence map›Paper›PMID 42127082›Full record

ArticlePloS one2026

Ecological strategies and extinction risk in butterflies and macro-moths of Great Britain and Ireland: A trait similarity network approach.

Lacey Boltz, Kaitlyn Kelble, Janice Tsogbe, John Matta

Abstract read
In one paragraph

Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Lacey BoltzDepartment of Computer Science, Southern Illinois University Edwardsville, Edwardsville, Illinois, United States of America.
Kaitlyn KelbleDepartment of Computer Science, Southern Illinois University Edwardsville, Edwardsville, Illinois, United States of America.
Janice TsogbeDepartment of Computer Science, Southern Illinois University Edwardsville, Edwardsville, Illinois, United States of America.
John MattaDepartment of Computer Science, Southern Illinois University Edwardsville, Edwardsville, Illinois, United States of America.ORCID https://orcid.org/0000-0002-7666-1409

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Trait-based analyses of extinction risk often examine individual traits independently, which can obscure how combinations of traits define broader ecological strategies. Here, we apply a network-based representation of trait similarity to analyze how extinction risk is distributed across combinations of ecological traits, extending an approach previously applied to seabirds. Using a curated species-level trait dataset for butterflies and macro-moths (order Lepidoptera), we constructed a species similarity network for 968 species and identified nine ecological communities using unsupervised community detection. The resulting communities were structured primarily by phenology and life-cycle characteristics. Although conservation status was not used in clustering, threatened species were unevenly distributed across communities, with the multivoltine, externally developing strategy group containing nearly six times the expected number of threatened species relative to background prevalence in both Great Britain and Ireland. These results show that extinction risk in Lepidoptera is structured by integrated ecological strategies, with patterns of vulnerability emerging from multivariate trait configurations. Trait similarity networks therefore provide a scalable approach for identifying strategy-level patterns of conservation vulnerability beyond single-species assessments, particularly in data-limited taxa such as insects where long-term population monitoring is often incomplete.

Indexed as

ButterfliesExtinction, BiologicalMothsAnimalsConservation of Natural ResourcesEcosystemEndangered SpeciesIrelandUnited Kingdom

Identifiers

PMID42127082
PMCPMC13170849

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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.