Assessment of pupal mortality in <i>Hypena opulenta</i> : An obstacle for establishment of a classical biological control agent against invasive swallow‐worts
Bibliographic record
Abstract
Abstract Common obstacles for establishment of newly‐introduced biological control agents include climate and the activity of native antagonists. In temperate climates, these obstacles can disproportionately affect overwintering life‐stages because they are exposed to low winter temperatures, and may rely on passive defence from predators. We conducted a series of field exposure experiments with predator‐exclusion treatments, in Ontario, Canada, to identify mortality factors for the pupae of Hypena opulenta , a biological control agent for invasive swallow‐worts in North America. During two winters, predation rates in containers with large holes, that enabled predation, were relatively low (mean: 23.75%) but non‐predation mortality in closed containers was high (mean: 66.25%), particularly during the colder of the two winters (87.5% vs. 52.5%). During the summer, non‐predation mortality in closed containers was low (mean: 7.5%) but predation rates in containers with large holes were higher than during the winter (mean: 53.33%), increasing as the summer progressed. Predation in containers with large holes was 70% during late summer, compared with 25% during the spring. Across all seasons, pupal predation was dominated by large non‐arthropod predators. Hypena opulenta can complete 2 generations per year. Photoperiods that induce diapause occur earlier in the introduced range than in the native range, however, and H. opulenta individuals in parts of the introduced range are likely to enter diapause early after a single generation. Our results highlight additional vulnerabilities encountered by such individuals, and can contribute to models predicting population dynamics of H. opulenta across its introduced range.
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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".