Integration of visual and olfactory cues of hosts and non‐hosts by three bark beetles (Coleoptera: Scolytidae)
Bibliographic record
Abstract
Abstract 1. There has been a long‐standing pre‐occupation with how phytophagous insects use olfactory cues to discriminate hosts from non‐hosts. Foragers, however, should use whatever cues are accurate and easily assessed, including visual cues. 2. It was hypothesised that three bark beetles, the mountain pine beetle (MPB), Dendroctonus ponderosae Hopkins, the Douglas‐fir beetle (DFB), D. pseudotsugae Hopkins, and the western balsam bark beetle (WBBB), Dryocoetes confusus Swaine, integrate visual and olfactory information to avoid non‐host angiosperms (e.g. paper birch, trembling aspen), that differ in visual and semiochemical profile from their respective host conifers (lodgepole pine, Douglas‐fir, interior fir), and tested this hypothesis in a series of field trapping experiments. 3. All three species avoided attractant‐baited, white (non‐host simulating) multiple‐funnel traps, and preferred attractant‐baited black (host‐simulating) traps. In experiments combining white, non‐host traps with non‐host angiosperm volatiles, bark beetles were repelled by these stimuli in an additive or redundant manner, confirming that these species could integrate visual and olfactory information to avoid non‐host angiosperms while flying. 4. When antiaggregation pheromones were released from white traps, the DFB and MPB were repelled in an additive‐redundant manner, suggesting that beetles can integrate diverse and potentially anomalous stimuli. 5. The MPB demonstrated the most consistent visual preferences, suggesting that it may be more of a ‘visual specialist’ than the DFB or WBBB, for which visual responses may be more contingent on olfactory inputs.
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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".