Attraction of the emerald ash borer to ash trees stressed by girdling, herbicide treatment, or wounding
Bibliographic record
Abstract
New infestations of emerald ash borer, Agrilus planipennis Fairmaire, an invasive pest native to Asia, are difficult to detect until densities build and symptoms appear on affected ash ( Fraxinus spp). We compared the attraction of A. planipennis to ash trees stressed by girdling (bark and phloem removed from a 15 cm wide band around the tree (2003–2005)), vertical wounding (same area of bark and phloem removed in a vertical strip (2004)), herbicide treatment (Pathway applied with a Hypo-Hatchet tree injector (2003) or basal bark application of Garlon 4 (2004, 2005)), exposure to the volatile stress elicitor methyl jasmonate (2005), or left untreated (2003–2005). The number and density of captured adults and density of larvae were recorded for 24, 18, and 18 replicates of each treatment at four, three, and five sites in 2003, 2004, and 2005, respectively. Girdled trees generally captured more adult A. planipennis and consistently had higher larval densities than untreated trees, and at most sites, than trees stressed by other treatments. Differential attraction to girdled trees was more pronounced at sites with lower densities of A. planipennis. Rates of capture of adults and densities of larvae were higher on trees in full or nearly full sun than on shaded trees. Girdled trees could be a useful tool for use in operational programs to detect or manage localized A. planipennis infestations.
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".