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Record W2138195758 · doi:10.1111/ele.12412

Differential effects of genetic vs. environmental quality in <i>Drosophila melanogaster</i> suggest multiple forms of condition dependence

2015· article· en· W2138195758 on OpenAlexafffund
Russell Bonduriansky, Martin A. Mallet, Devin Arbuthnott, Vera Pawlowsky‐Glahn, Juan José Egozcue, Howard D. Rundle

Bibliographic record

VenueEcology Letters · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsUniversity of OttawaQueen's University
FundersAustralian Research CouncilNatural Sciences and Engineering Research Council of CanadaCanada Foundation for Innovation
KeywordsDrosophila melanogasterBiologyEvolutionary biologyDrosophila (subgenus)EcologyQuality (philosophy)GeneticsGenePhysics

Abstract

fetched live from OpenAlex

Condition is a central concept in evolutionary ecology, but the roles of genetic and environmental quality in condition-dependent trait expression remain poorly understood. Theory suggests that condition integrates genetic, epigenetic and somatic factors, and therefore predicts alignment between the phenotypic effects of genetic and environmental quality. To test this key prediction, we manipulated both genetic (mutational) and environmental (dietary) quality in Drosophila melanogaster and examined responses in morphological and chemical (cuticular hydrocarbon, CHC) traits in both sexes. While the phenotypic effects of diet were consistent among genotypes, effects of mutation load varied in magnitude and direction. Average effects of diet and mutation were aligned for most morphological traits, but non-aligned for the male sexcombs and CHCs in both sexes. Our results suggest the existence of distinct forms of condition dependence, one integrating both genetic and environmental effects and the other purely environmental. We propose a model to account for these observations.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.423
Threshold uncertainty score0.147

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)0.0000.000

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 head0.013
GPT teacher head0.222
Teacher spread0.208 · 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.

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

Citations50
Published2015
Admission routes2
Has abstractyes

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