Dispersal and re-capture of marked, overwintering Tomicus piniperda (Coleoptera: Scolytidae) from Scotch pine bolts.
Bibliographic record
Abstract
The pine shoot beetle (PSB), Tomicus piniperda is a recently established exotic pest of live pine in the southern Great Lakes region of the U.S. and Canada. Scotch pine, Pinus sylvestris L. is the most susceptible pine species, but the adult also attacks several other North American species of Pinus, This research investigated the dispersal behavior of beetles emerging from overwintering sites to aid in the development of effective monitoring and management practices. Scotch pine logs with overwintering PSB were sprayed with fluorescent pigments to mark dispersing beetles. These logs were placed in piles in the centers of three circular trap arrays of 8-unit Lindgren traps, baited with α-pinene, and placed at distances of 50, 100, 200, 300 and 400 meters from the center along equally spaced radii. An estimated average of 393 PSB, or 23.4% of the overwintering PSB, dispersed from each of three log piles during the initial spring dispersal flight, and 21.9% of these were captured in traps. Traps within 100 meters caught 56.0 to 67.8% of the marked PSB recovered. Most (95.3%) marked PSB were trapped within 400 meters, but 12 beetles (4.7%) were trapped 780-2,000 meters away in adjacent trap arrays. The dispersal pattern of the population, as indicated by trap catch, was to the northeast, in the direction of prevailing westerly/ southerly winds up to 4.77 m/s daily average during beetle flight. Regression analysis suggests that the PSB within the experimental area had a predicted dispersal distance of 900 meters in an area that contained numerous traps. Dispersal distances may be greater under of conditions of strong and steady winds or if traps or abundant host material removed fewer PSB from the dispersing population. The use of traps to monitor specific sites should consider the direction of prevailing winds. Trap catches of wild PSB suggest that optimal inter-trap spacing for efficient detection could be about 78 m.
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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) | 0.000 | 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".