Life-history adaptation under climate warming magnifies the agricultural footprint of a cosmopolitan insect pest
Bibliographic record
Abstract
Abstract Climate change is affecting population growth rates of ectothermic pests with potentially dire consequences for agriculture, but how rapid genetic adaptation impacts these dynamics remains unclear. To address this challenge, we predicted how climate change adaptation in life-history traits of insect pests may affect future agricultural yields by unifying thermodynamics based on first principles with classic life-history theory. Our model predicts that warming temperatures favour changes in resource allocation decisions coupled with increased larval host consumption, resulting in a predicted double-blow on agricultural yields under future climate change. We find support for these predictions by studying thermal adaptation in life-history traits and underlying gene expression in the wide-spread insect pest, Callosobruchus maculatus , with five years of life-history evolution under experimental warming causing an almost two-fold increase in its predicted agricultural footprint. These results emphasize the need for integrating a mechanistic understanding of life-history evolution into forecasts of pest impact.
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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) | 0.002 | 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".