Clear effects of population and sex but not rearing temperature on stress tolerance in a temperate butterfly
Bibliographic record
Abstract
With temperatures rising globally due to climate change, an organism's survival depends both on its direct tolerance to rising temperatures and its tolerance to indirect effects of warming, such as resource shortage. Genetic background and phenotypic plasticity in the form of acclimation are known to affect stress tolerance, but much about genetic variation in plasticity is still unknown, especially in insects other than Drosophila . Here we aim to study the effect of population of origin, developmental temperature, and their interaction on heat and starvation tolerance. We test the beneficial acclimation hypothesis and how it is influenced by intraspecific differences. For this, we reared Glanville fritillary butterfly Melitaea cinxia larvae originating from Finland, where the climatic conditions experienced are relatively cool, and Spain, where the climate is relatively warm, at high and standard temperatures. In the adult stage, we measured stress tolerance as time until heat knockdown at a constant 45°C and lifespan under resource limitation. To assess other effects of thermal acclimation we also measured performance traits such as larval developmental time, survival, and adult lifespan. We found no significant effect of rearing temperature on heat or starvation tolerance, and heat tolerance also did not differ directly between sex or population of origin. In contrast, we found interacting effects of population and sex on adult starvation tolerance, with females originating from Spain outperforming other groups. Spanish female butterflies also had a longer lifespan under non‐stressful conditions, and we found significant G×E interactions in other performance traits. Even though our study provides no clear evidence for the beneficial acclimation hypothesis, it highlights the importance of considering population and sex differences in stress tolerance. Recognising these differences in tolerance across populations and sex will help to finetune and prioritise conservation efforts.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| 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 | 0.000 | 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".