Trap Height Affects Catches of Bark and Woodboring Beetles (Coleoptera: Curculionidae, Cerambycidae) in Baited Multiple-Funnel Traps in Southeastern United States
Bibliographic record
Abstract
In north-central Georgia, trap height affected catches of some species of bark and woodboring beetles (Coleoptera) in traps baited with lures used in surveillance programs to detect non-native forest insects. Traps were placed within the canopy and understory of mature oak trees (Quercus spp.) with collection cups placed 18-23 m above ground level (AGL), and 0.3-0.5 m AGL, respectively. Traps were baited with ethanol to target ambrosia beetles (Curculionidae: Scolytinae) in one experiment, ethanol + syn-2,3-hexanediol + racemic 3-hydroxyhexan-2-one + racemic 3-hydroxyoctan-2-one to target hardwood woodborers (Cerambycidae) in a second experiment, and α-pinene + racemic ipsenol + racemic ipsdienol to target pine bark beetles (Curculionidae) and woodborers (Cerambycidae) in a third experiment. Canopy traps were more effective than understory traps for detecting Cnestus mutilatus (Blandford) (Curculionidae), Neoclytus scutellaris (Olivier), and Monochamus titillator (F.) (Cerambycidae). The reverse was true for Xylosandrus crassiusculus (Motschulsky), Dendroctonus terebrans (Olivier) (Curculionidae), and Neoclytus acuminatus (F.) (Cerambycidae). Catches of a third group which included Hylobius pales (Herbst), Ips grandicollis (Eichhoff) (Curculionidae), Neoclytus mucronatus (F.), and Anelaphus pumilus (Newman) (Cerambycidae) were largely unaffected by trap height. Similar patterns were noted for species of Cleridae, Scarabaeidae, Trogossitidae, and Zopheridae but not Histeridae or Tenebrionidae (Coleoptera). Catches of the bee assassin Apiomerus crassipes (F.) (Hemiptera: Reduviidae) in traps baited with the hardwood borer blend were greater in canopy traps than in understory traps.
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".