Plant domestication slows pest evolution
Bibliographic record
Abstract
Agricultural practices such as breeding resistant varieties and pesticide use can cause rapid evolution of pest species, but it remains unknown how plant domestication itself impacts pest contemporary evolution. Using experimental evolution on a comparative phylogenetic scale, we compared the evolutionary dynamics of a globally important economic pest - the green peach aphid (Myzus persicae) - growing on 34 plant taxa, represented by 17 crop species and their wild relatives. Domestication slowed aphid evolution by 13.5%, maintained 10.4% greater aphid genotypic diversity and 5.6% higher genotypic richness. The direction of evolution (i.e. which genotypes increased in frequency) differed among independent domestication events but was correlated with specific plant traits. Individual-based simulation models suggested that domestication affects aphid evolution directly by reducing the strength of selection and indirectly by increasing aphid density and thus weakening genetic drift. Our results suggest that phenotypic changes during domestication can alter pest evolutionary dynamics.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".