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Record W4412841005 · doi:10.3390/plants14152369

The Remarkable Increase in the Invasive Autumn Fern, Dryopteris erythrosora, One of the World’s Most Marketed Ferns, in Eastern North America

2025· article· en· W4412841005 on OpenAlexaboutno aff
Robert W. Pemberton, Eduardo José Campechano Escalona

Bibliographic record

VenuePlants · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFern and Epiphyte Biology
Canadian institutionsnot available
Fundersnot available
KeywordsFernDryopterisAlienHerbariumGeographyBotanyNaturalizationTemperate climateBiologyCensusPopulationDemography

Abstract

fetched live from OpenAlex

, is the most marketed temperate fern in the world. The rapid increase and spread of this recently naturalized fern in North America was determined and mapped using 76 herbarium specimen records and 2553 Research Grade iNaturalist posts. In 2008, it was recorded in two states, but by 2025, it was found in 25 states in the eastern United States and Ontario, Canada. At the end of 2017, there had been only 23 iNaturalist posts, but this grew to 511 by the end of 2020 and 2553 by May 2025. The great increase in the number of iNaturalist posts is thought to be due to the real geographic spread and an actual increase in the abundance of the fern, as well as recognition of the fern by iNaturalists, and the increase in the number of iNaturalists. The spread and great increase are probably related to the high level of marketing, which introduces plants to the environment, and to biological characteristics of the fern, including apogamy and polyploidy, and possibly natural enemy release, which allows it to flourish in new environments and to displace native plants. This novel study demonstrated citizen science's (iNaturalist's) great value in detecting the naturalization and spread of alien plants.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.198
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.015
GPT teacher head0.211
Teacher spread0.197 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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