A cross‐seasonal perspective on local adaptation: metabolic plasticity mediates responses to winter in a thermal‐generalist moth
Bibliographic record
Abstract
Summary The physiological and ecological impact of the thermal environment across life stages can result in trade‐offs that determine fitness and population dynamics. Understanding mechanisms and consequences of local adaptation for any organism that overwinters requires taking a cross‐seasonal perspective. We used a trait‐based approach to distinguish variation among ecotypes in ecological and physiological responses to overwintering conditions. We used fall webworms (Hyphantria cunea;Lepidoptera:Arctiidae) fromOttawa,Ontario andColumbusOhio, representing the centre and periphery of the native range. We hypothesized that populations would be locally adapted to their overwintering environments, with fitness maximized under natal overwintering conditions. We predicted that this local adaptation would result from modulation of rates of energy use, growth and development. Each ecotype had higher overwinter survival in their natal compared with non‐natal winter environment, and this was associated with larger pupal mass, size and carbohydrate reserves at the end of winter. This suggests that the ecotypes are locally adapted to winter conditions. Larger adults laid more eggs, but there was no effect of ecotype or environment on fecundity. Pupae overwintering at warm, energetically demanding, southern temperatures suppressed metabolic rates in autumn, and developed more quickly in the spring, compensating for energetic demands of warmer winters. Northern ecotypes had lower thermal sensitivity of metabolism, leading to higher metabolic rates at cool temperatures that correlated with faster post‐winter development. Local adaptation to winter conditions suggests performance of peripheral populations may not be enhanced by warming winters. Decoupling of winter and growing season temperatures may negatively impact ectotherms.
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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".