Aphid genotypes vary in their response to the presence of fungal endosymbionts in host plants
Bibliographic record
Abstract
Genetic variation for fitness-relevant traits may be maintained in natural populations by fitness differences that depend on environmental conditions. For herbivores, plant quality and variation in chemical plant defences can maintain genetic variation in performance. Apart from plant secondary compounds, symbiosis between plants and endosymbiotic fungi (endophytes) can produce herbivore-toxic compounds. We show that there is significant variation among aphid genotypes in response to endophytes by comparing life-history traits of 37 clones of the bird cherry-oat aphid Rhopalosiphum padi feeding on endophyte-free and endophyte-infected tall fescue Lolium arundinaceum. Clonal variation for life-history traits was large, and most clones performed better on endophyte-free plants. However, the clones differed in the relative performance across the two environments, resulting in significant genotype x environment interactions for all reproductive traits. These findings suggest that natural variation in prevalence of endophyte infection can contribute to the maintenance of genetic diversity in aphid populations.
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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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".