Anatomical defences against bark beetles relate to degree of historical exposure between species and are allocated independently of chemical defences within trees
Bibliographic record
Abstract
Conifers possess chemical and anatomical defences against tree-killing bark beetles that feed in their phloem. Resins accumulating at attack sites can delay and entomb beetles while toxins reach lethal levels. Trees with high concentrations of metabolites active against bark beetle-microbial complexes, and more extensive resin ducts, achieve greater survival. It is unknown if and how conifers integrate chemical and anatomical components of defence or how these capabilities vary with historical exposure. We compared linkages between phloem chemistry and tree ring anatomy of two mountain pine beetle hosts. Lodgepole pine, a mid-elevation species, has had extensive, continual contact with this herbivore, whereas high-elevation whitebark pines have historically had intermittent exposure that is increasing with warming climate. Lodgepole pine had more and larger resin ducts. In both species, anatomical defences were positively related to tree growth and nutrients. Within-tree constitutive and induced concentrations of compounds bioactive against bark beetles and symbionts were largely unrelated to resin duct abundance and size. Fewer anatomical defences in the semi-naïve compared with the continually exposed host concurs with directional differences in chemical defences. Partially uncoupling chemical and morphological antiherbivore traits may enable trees to confront beetles with more diverse defence permutations that interact to resist attack.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".