A funnel trap for the detection of hemlock woolly adelgid (Hemiptera: Adelgidae) and a method of extracting crawlers from trap samples
Bibliographic record
Abstract
Eastern hemlock, Tsuga canadensis (L.) Carr., in eastern Canada is under threat from the invasive hemlock woolly adelgid, Adelges tsugae Annand (Hemiptera: Adelgidae). Early detection is a key feature to the management of A. tsugae because the impacts of this pest accrue quickly due to its bivoltine life cycle, and treatments can take a year or more to become effective. We tested a novel funnel trap design to collect the mobile first instar nymphs (crawlers) as a tool for early detection of adelgid infestations prior to host symptoms. The funnel traps performed better at detecting A. tsugae crawlers at very low abundance in a stand compared to vertically oriented sticky traps or to canopy branch tip sampling. Satisfactory detection rates for operational surveys were achieved using one or two funnel traps per site deployed for 2 wk during each of the two generations of A. tsugae and moving traps to new locations in the stand-between generations. We also optimized a protocol for extracting crawlers from trap samples, using stacked sieves (425 and 100 µm) to remove debris and retain crawlers, respectively, with the probability of detecting at least one crawler unaffected by the presence of debris. The improved trapping and extraction technique is aimed at stand-level early detection of this destructive pest and could be adapted to other similar, cryptic insect pests.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".