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Microhabitat selection by the invasive amphipod <i>Echinogammarus ischnus</i> and native <i>Gammarus fasciatus</i> in laboratory experiments and in Lake Erie

2003· article· en· W2014065770 on OpenAlexafffund
Colin D. A. van Overdijk, Igor A. Grigorovich, Tracy Mabee, William J. Ray, Jan J. H. Ciborowski, Hugh J. MacIsaac

Bibliographic record

VenueFreshwater Biology · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Invertebrate Ecology and Behavior
Canadian institutionsUniversity of Windsor
FundersNatural Sciences and Engineering Research Council of CanadaAmerican Academy of Sleep Medicine
KeywordsDreissenaGammarusAmphipodaEcologyBiologyCladophoraGammarus pulexHabitatAlgaeCrustaceanMolluscaBivalvia

Abstract

fetched live from OpenAlex

SUMMARY 1. The amphipod Echinogammarus ischnus was first reported in the Laurentian Great Lakes during 1995. However, analysis of archived samples revealed the presence of the species from western Lake Erie in 1994 and possibly as early as 1993. 2. Surveys conducted in Lake Erie between 1995 and 1998 revealed that Echinogammarus was the dominant amphipod on rocks covered by Dreissena molluscs compared with those fouled by the filamentous alga Cladophora , while Gammarus fasciatus used both Dreissena and Cladophora substrata extensively. 3. In laboratory habitat selection studies, Echinogammarus chose Dreissena ‐ over Cladophora ‐encrusted rocks and bare rocks, while Gammarus occupied the more complex substrata equally. 4. Field colonisation experiments demonstrated that the densities of Echinogammarus and Gammarus were positively correlated when the total density of the species was low, in contrast to the large‐scale natural distribution of the species that revealed a strong inverse relationship. 5. The on‐going replacement of Gammarus by Echinogammarus in the Laurentian Great Lakes may be related to the stronger affinity of the latter for substrata fouled by Dreissena , a genus with which it co‐evolved.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.573
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 studies0.0000.001
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 head0.007
GPT teacher head0.219
Teacher spread0.212 · 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 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

Citations72
Published2003
Admission routes2
Has abstractyes

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