Detection and landing behavior of emerald ash borer, <i>Agrilus planipennis</i>, at low population density
Bibliographic record
Abstract
The exotic emerald ash borer, Agrilus planipennis Fairmaire (Coleoptera: Buprestidae), was first discovered in North America in southeastern Michigan, USA, and Windsor, Ontario, Canada in 2002. Significant ash (Fraxinus spp.) mortality has been caused in areas where this insect has become well established, and new infestations continue to be discovered in several states in the United States and in Canada. This beetle is difficult to detect when it invades new areas or occurs at low density. Girdled trap tree and ground surveys have been important tools for detecting emerald ash borer populations, and more recently, purple baited prism traps have been used in detection efforts. Girdled trap trees were found to be more effective than purple prism traps at detecting emerald ash borer as they acted as sinks for larvae in an area of known low density emerald ash borer infestation. The canopy condition of the trap trees was not predictive of whether they were infested or not, indicating that ground surveys may not be effective for detection in an area of low density emerald ash borer population. When landing rates of low density emerald ash borer populations were monitored on non-girdled ash trees, landing rates were higher on larger, open grown trees with canopies that contain a few dead branches. As a result of these studies, we suggest that the threshold for emerald ash borer detection using baited purple prism traps hung at the canopy base of trees is higher than for girdled trap trees. In addition, detection of developing populations of EAB may be possible by selectively placing sticky trapping surfaces on non-girdled trap trees that are the larger and more open grown trees at a site.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".