Visual stimuli displayed on traps enhance attraction of longhorn beetles
Bibliographic record
Abstract
Abstract Longhorn beetles (Coleoptera; Cerambycidae) are one of the largest, most diverse, ecologically, and economically important family of beetles in the world. Several longhorn beetles display color patterns on their elytra that have likely evolved as a mechanism to gain protection from natural enemies and which might also be used as visual cues for intraspecific communication. In such cases, copying visual features that are important for mate finding on trapping devices used for monitoring native and non-native species might potentially increase trap efficacy. To test this hypothesis, we carried out four trapping trials in Europe and Canada targeting four longhorn beetle species. In each trapping trial, we compared the efficacy of plain black intercept-panel traps with panel traps displaying visual stimuli mimicking the elytral patterns of the targeted species. As a secondary objective, we also tested the effect of the species-specific visual patterns on non-target longhorn beetle species caught in traps. The presence of visual stimuli on traps enhanced attraction of Neoclytus acuminatus (Fabricius) and Xylotrechus antilope (Schönherr) but not Xylotrechus stebbingi Gahan. Not enough individuals of Sarosesthes fulminans (Fabricius) were caught to run an analysis. Responses of non-target longhorn beetle species to the tested stimuli also indicated that flower-visiting species were generally attracted by traps with plain light-colored panels recalling flower colors and that non-target non-flower visitors were attracted by different visual stimuli depending on the species. Our study showed that the integration of visual stimuli on traps can improve their efficacy toward longhorn beetles, aiding monitoring and survey programs for native and non-native species.
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) | 0.003 | 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".