MétaCan
Menu
Back to cohort
Record W6929622182 · doi:10.5061/dryad.d7wm37px7

Food quality effects on instar-specific life histories of a holometabolous insect

2020· dataset· en· W6929622182 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueDRYAD · 2020
Typedataset
Languageen
FieldEnvironmental Science
TopicEnvironmental and Biological Research in Conflict Zones
Canadian institutionsQueen's University
Fundersnot available
KeywordsJuvenilePredationFood qualityLarvaInsectPopulationLife history theory

Abstract

fetched live from OpenAlex

It is a long-standing challenge to understand how changes in food resources impact consumer life history traits and, in turn, impact how organisms interact with their environment. To characterize food quality effects on life history, most studies follow organisms throughout their life cycle and quantify major life events, such as age at maturity or fecundity. From these studies, we know that food quality generally impacts body size, juvenile development, and life span. Importantly, throughout juvenile development, many organisms develop through several stages of growth that can have different interactions with their environment. For example, parasitoids typically attack larger instars, whereas larval insect predators typically attack smaller instars. Interestingly, most studies lump all juvenile stages together, which ignores these ecological changes over juvenile development. We combine a cross-sectional experimental approach with a stage-structured population model to estimate instar-specific vital rates in the bean weevil, Callosobruchus maculatus across a food quality gradient. We characterize food quality effects on the bean weevil’s life history traits throughout its juvenile ontogeny to test how food quality impacts instar-specific vital rates. Vital rates differed across food quality treatments within each instar; however, their effect differed with instar. Weevils consuming low quality food spent 38%, 37% and 18% more time, and were 1%, 8% and 60% smaller than weevils consuming high quality food in the second, third and fourth instars, respectively. Overall, our results show that consuming poor food quality means slower growth, but that food quality effects on vital rates, growth and development are not equal across instars. Differences in life history traits over juvenile ontogeny in response to food quality may impact how organisms interact with their environment, including how susceptible they are to predation, parasitism, and their competitive ability.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.103
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.076
GPT teacher head0.287
Teacher spread0.211 · 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