A tale of two conifers: Migration across a dispersal barrier outpaced regional expansion from refugia
Bibliographic record
Abstract
Abstract Aim Understanding how climate refugia and migration over great distances have facilitated species survival during past climate changes is crucial for evaluating contemporary threats to biodiversity, particularly in the face of dispersal barriers. We address this longstanding question on the refugial origins and post‐glacial development of mesic forests. Location Pacific Northwest, North America. Taxon Mountain hemlock (Tsuga mertensiana) and western redcedar (Thuja plicata). Methods Range‐wide genotyping‐by‐sequencing (ddRADseq) of both study species and a pollen reconstruction of mountain hemlock presence over the last 20,000 years. Results Mountain hemlock occurred in two coastal populations (Oregon and Washington) during the glacial maximum, each of which dispersed to the interior (Idaho and British Columbia) during the Holocene. These populations spread in the direction of dominant winds across a barrier of dry, rain‐shadowed valleys. In contrast, for western redcedar, we infer four disparate refugia during the glacial maximum: southern (California), central (Washington), interior (Idaho), and northern (Haida Gwaii islands). Main conclusions Despite the presence of pre‐dispersed refugial populations, the majority of the redcedar distribution was colonized by the central population. The history for these two key conifers contrast with many recent studies emphasizing the role of cryptic refugia in colonizing modern species ranges.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".