Dispersal to predator‐free space counterweighs fecundity costs in alate aphid morphs
Bibliographic record
Abstract
1. Specialisation in dispersal by alate aphids often imposes constraints on other functions, particularly a reduction in fecundity due to wing development. Short‐distance flight from patches of high population density to uninfested plants may provide temporary predator‐free space, compensating for low fecundity. However, this theoretical prediction has not been explored experimentally. 2. To test this hypothesis, a field cage experiment was conducted in which A phis glycines populations initiated with controlled proportions of apterous and alate individuals were exposed to predation, while predator‐free space was accessible only through flight. It was predicted that an investment in alate individuals would benefit a population under predation, regardless of associated costs to fecundity. 3. As expected, a strong trade‐off was observed between fecundity and wing development. However, populations initiated with a fixed proportion of alate and apterous individuals showed no reductions in final population size compared with populations initiated with apterous individuals exclusively. Moreover, the initial presence of alate individuals in the populations increased aphid prevalence (i.e. proportion of plants colonised). Similarly, both increased population size and prevalence were observed when predator‐free space was accessible through flight, as opposed to when it was inaccessible. 4. These results show that despite high costs to fecundity, an investment in alate individuals is neither beneficial nor detrimental to population size when predator‐free space is accessible, but increases aphid prevalence. It is concluded that prevalence might provide an ecological advantage important enough to warrant the production of alate morphs under intense predation.
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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".