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Record W2098481715 · doi:10.2980/19-2-3468

Coexistence of introduced and native common reed (<i>Phragmites australis</i>) in freshwater wetlands

2012· article· en· W2098481715 on OpenAlexafffundvenueabout
Sophie Taddeo, Sylvie de Blois

Bibliographic record

VenueEcoscience · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicCoastal wetland ecosystem dynamics
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaFonds Québécois de la Recherche sur la Nature et les Technologies
KeywordsPhragmitesEcological nicheWetlandIntroduced speciesEcologyInvasive speciesGeographyNative plantBiodiversityMarshCompetition (biology)NicheBiologyHabitat

Abstract

fetched live from OpenAlex

Abstract: Invasive species are especially problematic when introduced into ecosystems with native congeners. The extent to which niches overlap in space determines whether the introduced species threatens the native one or the native species can escape competition or the effect of control. We compared the spatial distribution in relation to landscape and land-use/ land-cover variables of introduced and native Phragmites australis (common reed) in a landscape of protected freshwater wetlands in Quebec, Canada. Results showed that the wetlands still serve as refuges for native P. australis. At this stage of invasion, native and introduced P. australis occupy distinct spatial niches, the more abundant native type in low marsh and areas of lesser human impacts, the introduced one closer to roads and drier land covers. For now, native P. australis largely escapes competition, and the lack of spatial overlap could reduce opportunities for hybridization. Our study also suggests that invasion foci could still be controlled without endangering the native type. Whether the heterogeneous wetland conditions and the different spatial niches will be sufficient to allow long-term coexistence of native and introduced P. australis remains to be seen, but the situation needs to be closely monitored, especially in wetlands protected for biodiversity conservation.

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)0.001
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 score0.015
Threshold uncertainty score0.911

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.010
GPT teacher head0.230
Teacher spread0.220 · 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

Citations15
Published2012
Admission routes4
Has abstractyes

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