Factors affecting soldier allocation in clonal aphids: a life-history model and test
Bibliographic record
Abstract
Aphid species using a defensive soldier caste offer us the opportunity to study allocation decisions by eusocial groups, without the hindrance of genetic dissimilarity between colony members, which often impair studies involving Hymenopteran or Isopteran systems. When the entire aphid clone is considered the adaptive unit of organization, understanding soldier allocation strategies is tantamount to understanding the outcome of the tradeoff between clonal growth (i.e., asexual reproduction) and clonal defense. Under this framework, we present the results of a dynamic programming effort aimed at determining the optimal ontogeny of defensive allocation strategies by eusocial clonal organisms. We consider the allocation decision for clones with both obligately and facultatively sterile soldiers, under various levels of predation, and favorable and unfavorable ecological conditions. We test predictions of the model with the eusocial aphid, Pemphigus spyrothecae. Our model predicts that defensive investment should be dependent on the time of the season, with clones discounting defense nearer the end of season. Defensive investment should also vary inversely with clonal productivity and be sensitive to the current state (e.g., level of defense) of the clone. Census data collected in Burnaby, British Columbia, Canada, conform to patterns of clonal composition derived from allocation decisions generated in the model. Finally, qualitative predictions about patterns of clonal organization under “good” and “poor” ecological conditions were upheld by comparing clones in preferred and less-preferred galling sites.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".