Enantiospecific response of <i>Ips avulsus</i> (Coleoptera: Curculionidae: Scolytinae) to ipsdienol depends on semiochemical context
Bibliographic record
Abstract
Colonization of hosts by bark beetles is generally mediated by aggregation pheromones. Species competing for the same resource can limit interspecific interactions and maintain reproductive isolation by using different pheromones. In the southern United States, 3 sympatric species of Ips breed in pine hosts, each with a different pheromone blend. Ips avulsus (Eichhoff) uses ipsdienol and lanierone; Ips calligraphus (Germar) uses ipsdienol, cis-verbenol, and trans-verbenol; and Ips grandicollis (Eichhoff) uses ipsenol. Different species can also minimize cross-attraction by using different enantiomeric ratios of the same pheromones. Studies on the enantiomeric ratio of ipsdienol used by I. avulsus have come to contradictory conclusions in part because of geographic and seasonal variation. There is growing evidence that semiochemical context, in the form of different co-baits used in trapping experiments, may also play a role in the responses of I. avulsus to enantiomeric ratios of ipsdienol. We conducted a trapping study at 2 locations with traps baited with (+)-ipsdienol or racemic ipsdienol and co-baited with ipsenol, lanierone, or both ipsenol and lanierone. We found context-dependent effects of both lanierone and ipsenol on the response of I. avulsus to ipsdienol. We suggest that responses to different bait and co-bait combinations may have been shaped by different types of interactions such as the absence of conspecifics or a related species, or the presence of beneficial or antagonistic interspecific interactions.
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) | 0.002 | 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".