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Record W1549853551 · doi:10.22621/cfn.v128i4.1629

Use of a marsh dominated by the introduced European Lake Sedge, <em>Carex acutiformis</em>, by highly localized native butterflies

2015· article· en· W1549853551 on OpenAlexaffvenueabout
Paul M. Catling, Brenda Kostiuk

Bibliographic record

VenueThe Canadian Field-Naturalist · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBotany, Ecology, and Taxonomy Studies
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsCarexDominance (genetics)BiologyInvasive speciesIntroduced speciesMarshEcologyHabitatEndangered speciesCyperaceaeWetlandNative plantPoaceae

Abstract

fetched live from OpenAlex

To determine whether native butterflies had colonized a marsh in Ottawa that was entirely dominated by the invasive alien European Lake Sedge (Carex acutiformis), we surveyed two adjacent stands of the sedge and surrounding habitats. Dion Skipper (Euphyes dion), Mulberry Wing (Poanes massasoit), Broad-winged Skipper (P. viator), and browns (Lethe spp.) were all abundant in the introduced sedge, but absent from surrounding habitats. This is the first report of the use of invasive-dominated wetland by native Canadian butterflies. Reduced nectar resources because of dominance of the invasive species over native nectar-producing plants did not prevent significant colonization. The known restriction of the butterflies to native Lakebank Sedge (Carex lacustris) as a larval host plant, but its absence in the area, coupled with dominance of its close relative, European Lake Sedge, provides strong circumstantial evidence of the use of the latter as larval food. This report doubles the number of recently localized native butterflies that have been able to increase their distribution by switching to habitat dominated by invasive 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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.644
Threshold uncertainty score0.707

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.028
GPT teacher head0.214
Teacher spread0.187 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2015
Admission routes3
Has abstractyes

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