In-Flights of Outbreak Populations of Mountain Pine Beetle Alter the Local Genetic Structure of Established Populations a Decade After Range Expansion
Bibliographic record
Abstract
Abstract Mountain pine beetles began to appear at epidemic levels in Alberta, Canada, in 2006, following six years of extensive outbreaks in neighboring British Columbia. We assessed the effect of genetic MPB in-flights from the peak of the outbreak on the genetic structure of established populations of MPB and the change over time in novel regions colonized by these inflights. We used five locations sampled during the peak of the outbreak (2005/2007) and re-sampled in 2016. We performed a ddRADseq protocol to generate a SNP dataset via single-end Illumina sequencing. We detected a northern and southern genetic cluster in both sampling sets (2005/2007 and 2016) and a demographic shift in cluster assignment after ∼10 generations from south to north in two of the sites in the path of the northern outbreak. Fst values were significantly different between most sites in the same years and between the same sites at different years, with some exceptions for northern sites established by inflights. Overall, sites in the spreading path of the MPB outbreak have taken on the genetic structure of the contiguous northern outbreak except for an isolated site in Golden, BC, and in Mount Robson Provincial Park where populations are admixed between north and south. Our results suggest that range expansion during insect outbreaks can alter the genetic structure of established populations and lead to interbreeding between populations.
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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 | 0.001 | 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) | 0.001 | 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".