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Record W4308438683 · doi:10.1139/cjb-2022-0076

Allelopathy by the invasive garden lupine inhibits the germination of native herbs

2022· article· en· W4308438683 on OpenAlexvenueno aff
Aino Kalske, Emilia A. Mäkinen, Satu Ramula

Bibliographic record

VenueBotany · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAllelopathy and phytotoxic interactions
Canadian institutionsnot available
Fundersnot available
KeywordsAllelopathyGerminationFabaceaeBiologyShootBotanyInvasive speciesCaryophyllaceaeIntroduced species

Abstract

fetched live from OpenAlex

Allelopathy is the stimulatory or inhibitory effect of one plant on another plant by release of phytochemicals. It can affect the competitive interactions between plants, but the strength of the effect may depend on the tissue of the donor plant and the phylogenetic relatedness of the interacting species. Here, we examined the allelopathic effects of the invasive garden lupine Lupinus polyphyllus Lindl. (Fabaceae) on six native herbs from three families (Asteraceae, Caryophyllaceae, Fabaceae). We exposed the test species to aqueous leachates prepared from root or shoot tissue of L. polyphyllus and measured germination rate and germination time. Both leachates inhibited germination in all species (13%–84%), but shoot leachate was more allelopathic than root leachate in case of Fabaceae and Caryophyllaceae. Plants from closely related Fabaceae were least affected by L. polyphyllus leachates in terms of germination rate, but leachates delayed their germination. These results demonstrate that the invasive L. polyphyllus can inhibit the germination of co-occurring native species and suggest that allelopathy likely contributes to its invasion success. Our results have implications for management of invasive L. polyphyllus populations, emphasising the importance of the removal of mown plant material to diminish inhibitory allelopathic effects on local 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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.820
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.215
Teacher spread0.202 · 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 designBench or experimental
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

Citations10
Published2022
Admission routes1
Has abstractyes

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