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An experimental study of the multiple effects of brown trout<i>Salmo trutta</i>on the bioenergetics of two Arctic charr<i>Salvelinus alpinus</i>morphs

2012· article· en· W2150856779 on OpenAlexaff
Guillaume Guénard, Daniel Boisclair, Ola Ugedal, Torbjørn Forseth, Bror Jönsson, Ian Fleming

Bibliographic record

VenueJournal of Fish Biology · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsMemorial University of NewfoundlandUniversité du Québec à MontréalUniversité de Montréal
Fundersnot available
KeywordsSalvelinusSalmoBiologyBrown troutInterspecific competitionSympatric speciationEcologyCompetition (biology)SalmonidaeZoologyTroutAllopatric speciationFisheryFish <Actinopterygii>Population

Abstract

fetched live from OpenAlex

This study investigated the importance of competition with brown trout Salmo trutta as a driver of the morphological and behavioural divergence of two morphs of Arctic charr Salvelinus alpinus. The morphs originated from two lakes differing in absence or presence of the competitor. The bioenergetics and behaviour of S. alpinus were quantified in replicate experimental enclosures (mean volume: 150 m(3)) stocked with 15 S. alpinus of one morph or the other and in the absence or presence of nine S. trutta. The presence of S. trutta decreased growth rate, affected food consumption and increased activity costs in S. alpinus, but provided little support for the hypothesis that competition with S. trutta is a major driver of the divergence of the two S. alpinus morphs. Both morphs responded similarly in terms of mean growth and consumption rates per enclosure, but the association between individual morphology and growth rate reversed between allopatric and sympatric enclosures. While the activity patterns of the two morphs were unaffected by the presence of S. trutta, their swimming speed and activity rate differed. Since the profound differences in the structure of the physical habitat of the source lakes provided a more likely explanation for the difference observed among these two morphs than interspecific competition, it is hypothesized that physical habitat may sometimes be a significant driving force of the phenotypic divergence.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.014
GPT teacher head0.256
Teacher spread0.243 · 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

Citations5
Published2012
Admission routes1
Has abstractyes

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