Seasonal dynamics of a population of the aphid <i>Uroleucon rudbeckiae</i> (Hemiptera: Aphididae): implications for population regulation
Bibliographic record
Abstract
Abstract Many aphid species (Hemiptera: Aphididae) that feed on herbaceous crops exhibit a rise and then sudden decline in abundance. Data from a nine-year study of Uroleucon rudbeckiae (Fitch) on Rudbeckia laciniata Linnaeus (Asteraceae) are used to investigate this pattern of seasonal abundance in a non-agricultural aphid. Aphids on a population of tagged and numbered flower stems were counted weekly. Abundance (mean aphids per stem) was partitioned into prevalence (proportion of stems colonised) and mean intensity (aphids per colonised stem), and also considered as the sum of the aphids in individual colonies. Abundance rose in mid-summer to late summer and then declined, peaking between the end of July and mid-September, earlier in years when the peak was higher. Prevalence showed a more uniform and consistent peak than mean intensity. Most of the 949 colonies were small and short-lived, but a small proportion were long-lived and reached 1000 aphids. Large colonies declined more slowly than moderately-sized colonies. Severe weather, shortening day-length, decline in host quality, density-dependent effects on rate of increase, and emigration failed to explain the population decline. An early rise and later decline in immigration, in conjunction with increasing predation through the summer, were consistent with the decline.
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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".