Pre- and post-oviposition behavioural strategies to protect eggs against extreme winter cold in an insect with maternal care
Bibliographic record
Abstract
Depositing eggs in an area with adequate temperature is often crucial for mothers and their offspring, as the eggs are immobile and therefore cannot avoid exposure to sub-optimal temperatures. However, the importance of temperature on oviposition site selection is less clear when mothers can avoid these potential adverse effects by both moving their eggs after oviposition and providing other forms of egg care. In this study, we addressed this question in the European earwig, an insect in which mothers care for the eggs during several months in winter, frequently moving them during this period. We set up 60 females from two random natural populations (as this species often exhibits population-specific life-history traits and behaviours) under controlled thermal gradients, and recorded the temperature at which they built their nests, tested whether they moved their eggs after an experimental temperature change, and measured the effects on egg development and hatching rate. Our results demonstrate that females indeed select oviposition sites according to temperature, and can move their eggs to reach warmer temperatures. We also show that these warmer temperatures are necessary to ensure egg hatching. Although this set of behavioural thermoregulations is present in the two tested populations, we found a population-specific modality of expression. These included the range of temperatures explored before oviposition, temperature selected at oviposition and dynamics of egg transport following a temperature change. Overall, our study sheds light on a new post-oviposition strategy in female insects that overwinter with their eggs for coping with temperature changes. More generally, it also reveals that egg care and/or egg transport do not prevent behavioural thermoregulation via oviposition site selection and highlights the diversity of behaviours that insects can adopt to enhance their tolerance to global climate change.
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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 | 0.001 |
| 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".