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Record W1979861192 · doi:10.3897/neobiota.25.8316

Comparing functional similarity between a native and an alien slug in temperate rain forests of British Columbia

2015· article· en· W1979861192 on OpenAlexaffabout
Mariano A. Rodríguez‐Cabal, Taylor C. Gibbons, Patricia M. Schulte, M. Noelia Barrios‐García, Gregory M. Crutsinger

Bibliographic record

VenueNeoBiota · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMollusks and Parasites Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsAlienEcologyIntroduced speciesBiologyGeneralist and specialist speciesSlugHabitatHerbivoreContext (archaeology)Invasive speciesEcosystemAbundance (ecology)Population

Abstract

fetched live from OpenAlex

The impacts of invasive alien species are greatest when they become dominant members of a community, introduce novel traits, and displace native species. Invasions by alien mollusks represent a novel context by which to compare trait differences between generalist native and introduced herbivores in terrestrial ecosystems. Here, we determined the abundance, habitat, feeding preferences, as well as the metabolic rate of the native Pacific banana slug (Ariolimax columbianus) and the alien black slug (Arion rufus) in the coastal forests of British Columbia, Canada. Through a series of observational and experimental studies, we found that alien slugs are more abundant, differ in their habitat preferences, and consumed more fungi (mushrooms) than native banana slugs. Conversely, in an enclosures experiment we found that herbivory damage by native slugs was higher compared to enclosures with alien only and control enclosures. Finally, metabolic rates were similar for both slug species. These results suggest that alien black slugs possess a suite of traits that make them functionally different from native banana slugs.

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 score0.170
Threshold uncertainty score0.341

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
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 head0.086
GPT teacher head0.268
Teacher spread0.182 · 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

Citations6
Published2015
Admission routes2
Has abstractyes

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