Bibliographic record
Abstract
Across diverse taxa, animals produce infertile trophic eggs that are consumed by offspring.The objective of this thesis research was to establish a behavioural ecology framework for the study of trophic eggs; to model their evolution; and to investigate their adaptive function, if any, in the ladybird beetle Harmonia axyridis.Current trophic egg hypotheses suggest two adaptive functions: provisioning offspring or reducing parent-offspring conflict over sibling cannibalism.On the other hand, trophic eggs may simply represent infertility -they may not be an adaptation at all, a distinction given insufficient attention in the literature.I consider trophic egg laying in the context of sibling cannibalism behaviour.A frequency-independent analysis of sibling cannibalism suggests that there is a critical value of increase in offspring survival above which cannibalism benefits both parents and offspring; then mothers should adopt tactics (e.g., trophic egg laying) to facilitate cannibalism.However, the frequency-independent approach does not incorporate game interactions.I used a genetic algorithm approach to model the co-evolution of trophic eggs, sibling cannibalism, and hatching synchrony.Results suggest that, when game interactions occur or when infertile eggs are present, cannibalistic tendencies increase dramatically, as does the maternal response to limit cannibalism.Furthermore, trophic egg laying and hatch synchrony appear to be viable tactics for facilitating egg-eating.We tested trophic egg function in H. axyridis, predicting that mothers should lay fewer trophic eggs in food-rich environments and more in low food environments where offspring gain a larger relative benefit from eating an egg.As predicted, ladybirds produced 64% more trophic eggs when provided with information that they were in a low vs. high food environment (P = 0.0093).This result demonstrates that ladybirds produce trophic eggs to increase the chance that offspring survive starvation.In a second observation set, I tested whether the spatial distribution and oviposition sequence pattern of trophic eggs is over-or under-dispersed compared to random.There was no indication of a non-random distribution.In conclusion, this research is of interest in behavioural ecology because it shows that an unusual parenting strategy, killing off some offspring to benefit others, can be adaptive.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".