Establishment of the biological control agent <i>Aphalara itadori</i> is limited by native predators and foliage age
Bibliographic record
Abstract
Abstract The knotweed psyllid, Aphalara itadori, is a biological control agent for invasive knotweed species in North America and Europe. Initial releases were conducted in Canada in 2014 but establishment has been slow, seemingly as a result of low nymphal survival. We conducted two field experiments in Ontario, Canada, to explore the effects of native predators and the age of knotweed (Fallopia japonica) foliage on nymphal survival in A. itadori. Survival of A. itadori nymphs was significantly reduced on potted plants that were exposed to native predators in the field, compared to plants from which predators were excluded. The number of surviving nymphs was also significantly reduced on older F. japonica foliage, compared to recent regrowth after a summer cutting treatment. We discuss our findings in the context of biological invasion theory and emphasize the potential for increased overlap between the fields of invasion ecology and biological control. Finally, we advocate the use of A. itadori in combination with other control measures as part of an integrated pest management programme, rather than as a solitary measure. Specifically, we recommend that future releases of A. itadori be concentrated shortly after cutting or herbicide treatments in order to maximize the availability of young tender foliage.
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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) | 0.002 | 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".