Data from: A scenario for the evolution of selective egg colouration: the roles of enemy-free space, camouflage, thermoregulation, and pigment limitation
Bibliographic record
Abstract
Behavioural plasticity can drive the evolution of new traits in animals. In oviparous species, plasticity in oviposition behaviour could promote the evolution of new egg traits by exposing them to different selective pressures in novel oviposition sites. Individual females of the predatory stink bug Podisus maculiventris are able to selectively colour their eggs depending on leaf side, laying lightly pigmented eggs on leaf undersides and more pigmented eggs, which are more resistant to ultraviolet (UV) radiation damage, on leaf tops. Here, we propose an evolutionary scenario for P. maculiventris egg pigmentation and its selective application. We experimentally tested the influence of several ecological factors that: (i) could have favoured a behavioural shift towards laying eggs on leaf tops and thus the evolution of a UV-protective egg pigment (i.e. exploitation of enemy-reduced space or a thermoregulatory benefit) and (ii) could have subsequently led to the evolution of selective pigment application (i.e. camouflage or costly pigment production). We found evidence that a higher predation pressure on leaf undersides could have caused a shift in oviposition effort towards leaf tops. We also found the first evidence of an insect egg pigment providing a thermoregulatory advantage. Our study contributes to an understanding of how plasticity in oviposition behaviour could shape the responses of organisms to ecological factors affecting their reproductive success, spurring the evolution of new morphological traits.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.005 | 0.003 |
| 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".