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Record W2156178874 · doi:10.1139/f05-012

Community interactions affecting the relative abundances of native and invasive amphipods in the St. Lawrence River

2005· article· en· W2156178874 on OpenAlexfundvenueno aff
Michelle E. Palmer, Anthony Ricciardi

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Invertebrate Ecology and Behavior
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaMcGill University
KeywordsDreissenaPredationEcologyBiologyGammarusCompetition (biology)Zebra musselHabitatAmphipodaInvasive speciesIntroduced speciesInterspecific competitionCrustaceanBivalviaMolluscaMussel

Abstract

fetched live from OpenAlex

The Eurasian amphipod Echinogammarus ischnus is reportedly replacing the common native amphipod Gammarus fasciatus in the Great Lakes – St. Lawrence River system. A potential mechanism for this replacement is competition mediated by resident species. Other Eurasian invaders, dreissenid mussels (Dreissena polymorpha and Dreissena bugensis), dominate rocky substrates throughout the system and might be promoting the rapid expansion of E. ischnus by providing habitat and refugia from predation. Using an in-situ predator-exclusion experiment, we tested the hypothesis that E. ischnus is better able than G. fasciatus to use Dreissena spp. colonies as refugia and thus is less susceptible to predators in the St. Lawrence River. Co-occurring E. ischnus and G. fasciatus showed similar increases in density in the presence of Dreissena spp., in spite of E. ischnus having evolutionary experience with Dreissena spp. Predators reduced the density of both amphipod species, but E. ischnus was more susceptible to predation on dreissenid substrates, which suggests that predation mediates the coexistence of G. fasciatus and E. ischnus in the river.

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)0.001
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 score0.083
Threshold uncertainty score0.165

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.033
GPT teacher head0.257
Teacher spread0.223 · 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

Citations27
Published2005
Admission routes2
Has abstractyes

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Same venueCanadian Journal of Fisheries and Aquatic SciencesSame topicAquatic Invertebrate Ecology and BehaviorFrench-language works237,207