Efficacy of tree defense physiology varies with bark beetle population density: a basis for positive feedback in eruptive species
Bibliographic record
Abstract
We evaluated the ability of constitutive and inducible defenses to protect trees and restrict herbivore reproduction across the endemic, incipient (i.e., transitory), and eruptive phases of a native bark beetle species. Host defenses were major constraints when mountain pine beetle (Dendroctonus ponderosae Hopkins) populations were low, but inconsequential after stand-level densities surpassed a critical threshold. We annually examined all lodgepole pines (Pinus contorta Douglas var. latifolia) in six 12–18 ha stands for 3–6 years for beetle attack and establishment as beetle densities progressed through various population phases. We also assayed a suite of tree physiological and chemical attributes and related them to subsequent attacks during that year. Rapidly inducible defenses appeared more important than constitutive defenses, and total monoterpenes were more important than particular constituents. Trees that exude more resin and accumulate higher monoterpene concentrations in response to simulated attack largely escaped natural attacks when populations were low. In stands where beetles had reached incipient densities, these defenses were ineffective. Larger diameter trees had more pronounced defenses than smaller diameter trees. As populations increased, beetles selected increasingly larger, more resource-rich trees, despite their better defenses. When populations were too low for cooperative attack, beetles exploited trees weakened by lower-stem insects. Behavioral plasticity allows beetles to persist at endemic levels until conditions shift, after which positive feedbacks predominate.
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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 | 0.000 | 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".