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Record W2161205105 · doi:10.1139/f07-092

Stream ecosystems respond to riparian invasion by Japanese knotweed (<i>Fallopia japonica</i>)

2007· article· en· W2161205105 on OpenAlexvenueno aff
Antoine Lecerf, Denise Patfield, Anatole Boiché, Miira P. Riipinen, Éric Chauvet, Michael Dobson

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicFreshwater macroinvertebrate diversity and ecology
Canadian institutionsnot available
Fundersnot available
KeywordsRiparian zoneBiologyPlant litterEcologyInvertebrateIntroduced speciesSTREAMSAquatic ecosystemInvasive speciesRiparian forestEcosystemHabitat

Abstract

fetched live from OpenAlex

There are growing concerns about the rapid spread of exotic plants into riparian zones, yet little information is currently available on their influence on stream ecosystems. This study assessed the impact of riparian invasion by Japanese knotweed (Fallopia japonica), an aggressive invader, on leaf litter breakdown and its associated biota (aquatic hyphomycete fungi and benthic invertebrates) in heterotrophic, low-order streams in The Pennines (England) and the Pyrenees (France). Our results suggest that leaf consumers (aquatic hyphomycetes and invertebrate shredders) can readily use knotweed leaf litter even in stream sites where it was not previously present. However, aquatic hyphomycete and invertebrate assemblages differed between stream sites with and without knotweed. Leaf litter breakdown rate and relative abundance of large invertebrate shredders (mainly Trichoptera) were enhanced in the Pyrenean invaded site, whose channel contained a high proportion of knotweed leaf litter, whereas no such effects were observed in The Pennines, possibly because of the less extensive knotweed invasion. Alteration of riparian vegetation by plant invaders could therefore increasingly influence instream community and ecological functions as the severity of invasion rises.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.513
Threshold uncertainty score1.000

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 studies0.0010.001
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 head0.013
GPT teacher head0.198
Teacher spread0.185 · 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.

Study designNot applicable
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

Citations97
Published2007
Admission routes1
Has abstractyes

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