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Effects of early resource limitation and compensatory growth on lifetime fitness in the ladybird beetle (<i>Harmonia axyridis</i>)

2007· article· en· W2070235434 on OpenAlexaff
Caitlin Dmitriew, Locke Rowe

Bibliographic record

VenueJournal of Evolutionary Biology · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsToronto ZooUniversity of Toronto
Fundersnot available
KeywordsBiologyCompensatory growth (organ)Harmonia axyridisFecunditySurvivorship curveMatingZoologyEcologyPredationDemographyPredatorEndocrinologyCoccinellidae

Abstract

fetched live from OpenAlex

Acceleration of growth following a period of diet restriction may result in either complete or partial catch-up in size. The existence of such compensatory growth indicates that organisms commonly grow at rates below their physiological maxima and this implies a cost for accelerated growth. We examined patterns of accelerated growth in response to temporary resource limitation, and assayed both short and long-term costs of this growth in the ladybird beetle Harmonia axyridis. Subsequent to the period of food restriction, accelerated growth resulted in complete compensation for body sizes, although we observed greater larval mortality during the period of compensation. There were no effects on female fecundity or survivorship within 3 months of maturation. Females did not discriminate against males that had undergone compensatory growth, nor did we observe effects on male mating behaviour. However, individuals that underwent compensatory growth died significantly sooner when deprived of food late in adult life, suggesting that longer-term costs of compensatory growth may be quite mild and detectable only under stressful conditions.

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 score0.001
Threshold uncertainty score0.002

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 studies0.0000.000
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 head0.014
GPT teacher head0.234
Teacher spread0.220 · 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

Citations92
Published2007
Admission routes1
Has abstractyes

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