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Hybridization effects on phenotypic plasticity: experimental compensatory growth in farmed‐wild Atlantic salmon

2010· article· en· W2143879451 on OpenAlexafffund
Matthew Morris, Dylan J. Fraser, James D. Eddington, Jeffrey A. Hutchings

Bibliographic record

VenueEvolutionary Applications · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsDalhousie UniversityConcordia UniversityUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaDalhousie UniversityUniversities Space Research Association
KeywordsBiologyPhenotypic plasticityPlasticityEcologyPhenotypeZoologyFisheryGeneGenetics

Abstract

fetched live from OpenAlex

Compensatory growth (CG) is a means by which organisms can increase their growth rate above their routine growth rate after a period of environmentally induced growth depression. Despite a focus on the implications of CG for aquaculture, little research has evaluated the effect of domesticated-wild hybridization on CG. Any deviation in the mean compensatory ability of hybrids relative to their wild progenitors, or any notable costs to compensation in terms of body morphology, could affect the ability of hybrids to persist in changing environments. We compared CG of farmed, wild and hybrid (F1, F2, wild backcross) juvenile Atlantic salmon (Salmo salar). Wild salmon experienced both lower routine and CG rates relative to farmed salmon, while hybrids were intermediate. However, the compensatory responses (slopes of the reaction norms) for each cross were parallel, indicating that hybridization did not affect the CG response itself. Morphological costs to compensation were not detected. In addition to contributing to risk assessments of the consequences of interbreeding between wild and escaped domesticated organisms, we conclude that plasticity studies on domesticated-wild hybrids and their progenitors are useful for testing basic predictions about the evolution of phenotypic plasticity, as well as understanding the evolutionary significance of hybrids.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.099
Threshold uncertainty score0.999

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.005
GPT teacher head0.209
Teacher spread0.205 · 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

Citations21
Published2010
Admission routes2
Has abstractyes

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