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Record W2006565037 · doi:10.1111/nph.12733

<i><scp>C</scp>onyza canadensis</i> suppresses plant diversity in its nonnative ranges but not at home: a transcontinental comparison

2014· article· en· W2006565037 on OpenAlexaff
Manzoor A. Shah, Ragan M. Callaway, Tabasum Shah, Gregory R. Houseman, Róbert W. Pál, Sa Xiao, Wenbo Luo, Christoph Rosche, Zafar A. Reshi, Damase P. Khasa, Shuyan Chen

Bibliographic record

VenueNew Phytologist · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsSpecies richnessBiologyIntroduced speciesInvasive speciesEcologyRange (aeronautics)Native plantBiomass (ecology)Abundance (ecology)Solidago canadensisCompetition (biology)

Abstract

fetched live from OpenAlex

The impact of invasive species across their native and nonnative ranges is poorly quantified and this impedes a complete understanding of biological invasions. We compared the impact of the native North American plant, Conyza canadensis, which is invasive to Eurasia, on species richness at home and in a number of introduced regions through well replicated transcontinental field studies, glasshouse experiments and individual-based models. Our results demonstrated mostly negative relationships between C. canadensis abundance and native species richness in nonnative ranges, but either positive or no relationships in its native North American range. In glasshouse experiments, the total biomass of Conyza was suppressed more by species from its native range than by species from regions where it is nonnative, but the effects of Conyza on other species did not show a consistent biogeographical pattern. Finally, individual-based models led to the exclusion of Conyza from North American scenarios but to high abundances in scenarios with species from the nonnative ranges of Conyza. We illustrate biogeographical differences in the impact of an invader across regional scales and suggest that inherent differences in one specific aspect of competitive ability, tolerance to the effects of other species, may play some role in these differences.

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 score0.240
Threshold uncertainty score0.769

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 studies0.0000.000
Scholarly communication0.0000.000
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 head0.024
GPT teacher head0.238
Teacher spread0.214 · 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

Citations67
Published2014
Admission routes1
Has abstractyes

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