An experimental application of <i>Hypena opulenta</i> as a biocontrol agent for the invasive vine <i>Vincetoxicum rossicum</i>
Bibliographic record
Abstract
Abstract 1. Pre‐release testing for biological control agents is focused primarily on assessment of host‐range specificity and safety of potential agents. Agent impact is considered pre‐release; however, the ultimate assessment of an agent must occur following release in the field under the target population levels and conditions of the invaded ecosystems. The invasive Eurasian vine, Vincetoxicum rossicum, has spread aggressively through its invaded range of eastern North America since its initial introduction in the late 1800s. In laboratory tests, the Eurasian moth Hypena opulenta has shown great promise as a potential control agent for V. rossicum. 2. We were interested in the defoliating ability of H. opulenta and its subsequent effect on the seed production of V. rossicum under field conditions. To examine this, we established a field site near Kirkfield, Ontario, that consisted of meadow and forest understory plots, both of which were highly invaded by V. rossicum. 3. We report highly significant feeding by H. opulenta in both light conditions. Unexpectedly, we observed a significant increase in seed production following folivory in shade conditions. We observed no significant effect of larval folivory on seed production under sun conditions, where V. rossicum seed production is greater by a factor of 10 as compared to shade conditions. 4. It is unclear how continuous exposure to folivory by H. opulenta will affect mature V. rossicum stands, although it might be expected that such populations would invest in defenses to herbivory, possibly at the expense of reproductive output. In order to better understand if V. rossicum populations in either light condition could exhibit longer‐term compensatory growth in response to folivory, further experimental work is needed that examines inter‐annual variability in V. rossicum reproduction at variable H. opulenta densities.
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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) | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".