Traumatic resin ducts as indicators of bark beetle outbreaks
Bibliographic record
Abstract
The formation of traumatic resin ducts (TRDs) represents an important induced defense in woody plants that enhances oleoresin production and flow in response to environmental perturbations. In some genera (Pinus), resin ducts are copious and conspicuous; however, in others (Picea), resin ducts are relatively rare. The occurrence and strength of resin ducts, in particular TRDs, in annually resolved rings could be used to reconstruct mechanical damage associated with natural disturbances. We analyzed tree-ring data from paired live and dead Engelmann spruce (Picea engelmannii Parry ex Engelm.) that recently experienced a spruce beetle outbreak. The presence of TRDs, defined as resin ducts aligned tangentially and arranged compactly, indicated mechanical damage associated with epidemic spruce beetle (Dendroctonus rufipennis (Kirby)) populations. TRD prevalence during the outbreak was significantly higher than over tree lifespans. All other metrics characterizing tree vigor (diameter, age, ring width, and basal area increment) were not significantly different between live and dead trees, suggesting that the inherent capability to produce TRDs that can “pitch out” attacking spruce beetles could be the primary mechanism by which Engelmann spruce survived the outbreak. Because TRD production in our Engelmann spruce was exceedingly rare, this discovery represents a new line of tree-ring-based evidence that can be used to reconstruct other spruce beetle outbreaks.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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".