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Record W4415005611 · doi:10.1139/cjfas-2024-0388

Adaptive morphological plasticity foreshadows local adaptation in an invasive freshwater fish ( <i>Salmo trutta</i> ): evidence from reciprocal transplants in nature

2025· article· en· W4415005611 on OpenAlexaffvenueabout
Peter A. H. Westley, Curry J. Cunningham, Ian Fleming

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsSalmoLocal adaptationPhenotypic plasticityBrown troutAdaptation (eye)Freshwater fishFish <Actinopterygii>TroutPlasticity

Abstract

fetched live from OpenAlex

Phenotypic plasticity is a key trait of successful invaders, enabling survival in novel environments during early colonization. This study investigates adaptive morphological plasticity in brown trout ( Salmo trutta), a globally invasive species, established in Newfoundland during the late 1800s using reciprocal transplant experiments. We assessed fitness-linked traits—particularly head and body shape—in both wild and lab-reared F1 fish released into three rivers with contrasting environments. Over 70 days, morphometric analyses revealed substantial shape plasticity. In the small, steep Middle Rocky Brook, fish developed larger heads and streamlined bodies; while in the larger, lower-gradient Rennies and Waterford rivers, fish had smaller heads and deeper bodies. These patterns are consistent with responses to hydrodynamic variation reported in prior work. Reaction norms indicated gene × environment interactions, and transplanted individuals often shifted toward the phenotype of local wild fish. Overall, results support a role for adaptive plasticity in enhancing survival during initial stages of invasion and suggest it may act as a precursor to local genetic adaptation.

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 score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

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 head0.024
GPT teacher head0.229
Teacher spread0.204 · 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

Citations1
Published2025
Admission routes3
Has abstractyes

Explore more

Same venueCanadian Journal of Fisheries and Aquatic Sciences→Same topicFish Ecology and Management Studies→French-language works237,207→