Consequences of distributional asymmetry in a warming environment: invasion of novel forests by the mountain pine beetle
Bibliographic record
Abstract
Abstract The range of many Holarctic forest insects does not comprise the entire range of their hosts, as they are often limited to more southern latitudes by the adverse effects of cold temperatures. Global climate warming has led to the increased potential for forest insects to invade novel habitats of native hosts within the same landmass. The mountain pine beetle (MPB;Dendroctonus ponderosae) has recently expanded into higher‐latitude forests of the principal host, lodgepole pine (Pinus contortavar.latifolia), and the susceptibility of trees is greater in these systems compared to forests in the native range. We assessed the contribution of the induced defensive response of hosts to this elevated susceptibility, and whether these discrepancies are the result of coevolution with host populations within the historic native range of the insect. We challenged trees using paired treatments of a beetle‐attack simulation and a generic defensive response elicitor (methyl jasmonate) to mitigate variability in the induced response among trees within and among populations, from within and outside the historic range of the beetle. We then assessed the production of monoterpene chemicals by the trees in response to treatments using gas chromatography/mass spectrometry. The differential induction of monoterpenes in response to simulated beetle attack relative to the generic elicitor was highest in populations with the highest putative historic exposure to MPB. Elevated susceptibility and invasion potential of the beetle in novel systems is the proximate result of reduced defensive capacity, ultimately arising from a lack of coevolution with the beetle in novel systems. In forested systems with climate‐driven herbivore–host distributional asymmetry, continued warming will potentially exacerbate the impacts of aggressive insect herbivores as they invade defensively naïve host populations.
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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 | 0.001 |
| 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".