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The origins of ecotypic variation of rainbow trout: a test of environmental vs. genetically based differences in morphology

2006· article· en· W2081582063 on OpenAlexafffund
Ernest R. Keeley, Eric A. Parkinson, Eric B. Taylor

Bibliographic record

VenueJournal of Evolutionary Biology · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsMinistry of EnvironmentUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsRainbow troutBiologyEcotypePhenotypic plasticityMorphology (biology)EcologyZoologyInvertebrateTroutPopulationFish <Actinopterygii>Fishery

Abstract

fetched live from OpenAlex

Although morphological plasticity has been observed in a variety of taxa, few experimental studies have compared the relative proportion of morphological variability that is accounted for by environmentally induced plasticity, and how much is because of genetically based differences among populations. We compared the morphology of six rainbow trout (Oncorhynchus mykiss) populations from different ecotypic categories that were raised under flowing vs. standing-water conditions. Our data indicate that both environmental conditions and ecotypic differences account for a significant proportion of variation in morphology. Among ecotype effects, however, accounted for a much larger proportion of morphological variability than environmental conditions. Rainbow trout from stream populations had deeper caudal peduncles, and longer fins than lake populations, and rainbow trout from a piscivorous population had larger mouth and head lengths than all other ecotypes. Environmentally induced differences in morphology were primarily related to differences in mouth and head lengths, as well as fin length. Relative to morphometric differences from natural rainbow trout populations, most characteristics deviated in the same direction in our experimental populations. Our data indicate that morphological differences across rainbow trout populations have a genetic basis and may represent locally adaptive characteristics and highlight the role of ecology in promoting 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)0.001
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 score0.002
Threshold uncertainty score0.004

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 studies0.0000.001
Scholarly communication0.0000.000
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 head0.005
GPT teacher head0.191
Teacher spread0.186 · 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

Citations98
Published2006
Admission routes2
Has abstractyes

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