Landscape‐scale genetic variation in a forest outbreak species, the mountain pine beetle (<i>Dendroctonus ponderosae</i>)
Bibliographic record
Abstract
The mountain pine beetle Dendroctonus ponderosae is a native species currently experiencing large-scale outbreaks in western North American pine forests. We sought to describe the pattern of genetic variation across the range of this species, to determine whether there were detectable genetic differences between D. ponderosae occupying different host trees in common localities, and to determine whether there was molecular evidence for a past demographic expansion. Using a combination of amplified fragment length polymorphism (AFLP) and mitochondrial sequencing analyses, we found evidence of genetic structuring among populations that followed a broad isolation-by-distance pattern. Our results suggest that the geographical pattern of gene flow follows the core distribution of the principal D. ponderosae host species, around rather than across the Great Basin and Mojave Deserts. Patterns of haplotype diversity and divergence were consistent with a range-wide population expansion. This signal was particularly pronounced in the northern part of the species' range, where outbreak activity is currently increasing. Using AFLP markers, we were unable to detect significant differences among groups of insects sampled from different host trees in common locations. Incidentally, we found that a large proportion of the polymorphic AFLP markers were gender-specific, occurring only in males. While we did not include these markers in our analyses, this finding warrants further investigation.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".