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Condition dependence of sexually dimorphic colouration and longevity in the ambush bug <i>Phymata americana</i>

2008· article· en· W1974969763 on OpenAlexafffund
David Punzalan, Mohan Cooray, F. Helen Rodd, Locke Rowe

Bibliographic record

VenueJournal of Evolutionary Biology · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsUniversity of Toronto
FundersUniversity of Toronto
KeywordsBiologyLongevityTraitSexual dimorphismDemographyZoologyGenetics

Abstract

fetched live from OpenAlex

Sexually selected traits that are costly are predicted to be more condition dependent than nonsexually selected traits. Assuming resource limitation, increased allocation to a sexually selected trait may also come at a cost to other fitness components. To test these predictions, we varied adult food ration to manipulate condition in the colour dimorphic bug, Phymata americana. We compared the degree of condition dependence in a sexually selected trait expressed in males to a nonsexually selected trait expressed in males and females. We also evaluated the effects of condition on longevity of both sexes. We found that the expression of these colour pattern traits was strongly influenced by both diet and age. As expected, the strength of condition dependence was much more pronounced in the sexually selected, male-limited trait but the nonsexual trait also exhibited significant condition dependence in both sexes. The sexually selected male trait also exhibited a higher coefficient of phenotypic variation than the nonsexually selected trait in males and females. Diet had contrasting effects on male and female longevity; increased food availability had positive effects on female lifespan but these effects were not detected in males, suggesting that males allocated limited resources preferentially to sexually selected traits. These results are consistent with the expectation that optimal allocation to various fitness components differs between the sexes.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.434
Threshold uncertainty score0.102

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 head0.029
GPT teacher head0.252
Teacher spread0.223 · 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

Citations60
Published2008
Admission routes2
Has abstractyes

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