Attack and Reproductive Success of Mountain Pine Beetles (Coleoptera: Scolytidae) in Fire-Damaged Lodgepole Pines
Why this work is in the frame
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Bibliographic record
Abstract
High-intensity fires are known to kill adult and larval bark beetles, but it is unclear how mountain pine beetles (Dendroctonus ponderosae Hopkins) respond to trees that have been damaged by lower-intensity ground fires at the periphery of burns. We conducted an experiment to determine whether mountain pine beetles preferentially attack trees that have been damaged by fire and to determine how fire damage affects beetles’ reproductive success. We simulated different intensities of ground fires by artificially burning a strip of bark that extended zero-thirds, one-third, two-thirds, or three-thirds around a tree’s circumference. Burn treatments were applied ∼7 wk before beetles emerged from surrounding trees. We found that beetles did not preferentially attack fire-damaged trees; fire damage had no effect on the number of beetles landing on a tree, which trees were attacked, attack rate, attack density, or the body size of beetles attacking a tree. Beetle reproductive success (number and condition of offspring) was also not affected by fire damage. Beetles were more likely to overcome tree defenses and produce successful egg galleries on fire-damaged trees than on undamaged trees, but this was only observed on trees with low beetle attack densities. If beetle attack density was high, trees were successfully attacked irrespective of burn treatment. Our results suggest that fire damage only affects mountain pine beetle reproduction and population growth in areas where attack densities are low. In other situations, fire damage will have negligible effects on beetle attack and reproductive success.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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 it