Data and code from: Decades of historical outbreak cycles in a multivoltine insect reveal a plastic phenological response to climate change
Bibliographic record
Abstract
Many organisms overwinter in a specific life stage, which means their phenology must be well-timed with seasonal changes in the environment. As environments warm, we expect a delay in the onset of winter. For organisms where temperature is the primary driver of development rate, warming environments also mean faster development. If temperature dependence in the development rate of individuals does not also change, this will cause a mismatch between seasonal timing of the critical overwintering stage and the onset of winter. There are two biological mechanisms by which ectotherms can adapt their phenology in the face of climate change to maintain correct timing: i) organisms undergo evolution of the development thermal reaction norm, and ii) organisms have a plastic response in their development to multiple environmental cues. Here we use high resolution records of densities of the smaller tea tortrix (Adoxophyes honmai) over multiple decades across 9 locations in Japan to infer temperature-dependent changes in development rates over both time and space. The pest insect displays regular single-generation limit cycles, which provides a unique opportunity to infer changes in developmental rates directly from historical records of natural populations. The last half century has seen a temperature increase of about 1 ℃ across Japan, and our analyses show that populations slowed development on average by 16% to maintain the correct timing of the overwintering stage. Development rates measured from common garden experiments reveal that the change is not due to evolution. Our results build on recent laboratory studies to suggest that there is substantial plasticity in developmental thermal reaction norms that may explain how the phenology of ectotherms will respond to climate warming in natural systems.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.078 | 0.050 |
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".