Chemical similarity between historical and novel host plants promotes range and host expansion of the mountain pine beetle in a naïve host ecosystem
Bibliographic record
Abstract
Host plant secondary chemistry can have cascading impacts on host and range expansion of herbivorous insect populations. We investigated the role of host secondary compounds on pheromone production by the mountain pine beetle (Dendroctonus ponderosae) (MPB) and beetle attraction in response to a historical (lodgepole pine, Pinus contorta var. latifolia) and a novel (jack pine, Pinus banksiana) hosts, as pheromones regulate the host colonization process. Beetles emit the same pheromones from both hosts, but more trans-verbenol, the primary aggregation pheromone, was emitted by female beetles on the novel host. The phloem of the novel host contains more α-pinene, a secondary compound that is the precursor for trans-verbenol production in beetle, than the historical host. Beetle-induced emission of 3-carene, another secondary compound found in both hosts, was also higher from the novel host. Field tests showed that the addition of 3-carene to the pheromone mixture mimicking the aggregation pheromones produced from the two host species increased beetle capture. We conclude that chemical similarity between historical and novel hosts has facilitated host expansion of MPB in jack pine forests through the exploitation of common host secondary compounds for pheromone production and aggregation on the hosts. Furthermore, broods emerging from the novel host were larger in terms of body size.
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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".