The dynamics of a changing Lutz spruce (<i>Picea</i> × <i>lutzii</i>) hybrid zone on the Kenai Peninsula, Alaska
Bibliographic record
Abstract
We investigated the genetic makeup of Lutz spruce, a natural hybrid between white and Sitka spruce on the Kenai Peninsula, Alaska. Microsatellites indicate 72% of individuals sampled had predominantly white spruce ancestry, whereas 14% had predominantly Sitka spruce ancestry; some individuals classified as white spruce had Sitka spruce plastid genotypes. As Picea mitochondria are maternally inherited and plastids are paternally inherited, it appears that white spruce was the ancestral seed parent of nearly all spruce on the western peninsula, whereas Sitka spruce alleles originated from pollen. Pollen records show that white spruce colonized the western peninsula ∼8500 YBP from glacial refugium, whereas Sitka spruce arrived on the eastern peninsula ∼4000 YBP after migrating up the Pacific coast. Our data suggest that Sitka spruce colonization west of the Kenai Mountains may have occurred not via seed dispersal but by long distance transport of wind-borne pollen and subsequent hybridization with established white spruce populations. Hybridization was an important mechanism that allowed Sitka spruce to expand the leading edge of its range in response to historical climate change. As the climate continues to warm, climate envelope modeling suggests Lutz spruce may ultimately displace white spruce on the western peninsula even as Sitka spruce is constrained to the eastern peninsula where it will continue to hybridize.
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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 | 0.001 | 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".