An alpine plant shows no decrease in genetic diversity associated with rapid post-glacial range expansion
Bibliographic record
Abstract
Abstract While range expansion is hypothesized to be a mechanism for species persistence under climate change, many eco-evolutionary models describe demographic and genetic processes during range expansion that may decrease genetic variation and increase genetic load at the leading edge (i.e., expansion load). These predictions are related to dispersal limitation at the leading edge driving colonization dynamics, a scenario common in post-glacial range expansion at the continental scale (∼20,000 years ago). However, post-glacial range expansion can also occur on contemporary time scales, such as alpine glacier recession following the end of The Little Ice Age (∼150 years ago) and our understanding of dispersal limitation structuring these instances of rapid range expansion are relatively understudied. Here, we test whether there is evidence supporting the role of dispersal limitation during range expansion following alpine glacier retreat using the native alpine plant Erythranthe (Mimulus) lewisii by examining patterns of neutral genetic diversity (single nucleotide polymorphisms) across the history of glacier recession (i.e., glacier chronosequence) across two glacier forelands in Garibaldi Provincial Park, BC. We find weak support for the prediction of increasing clines in genetic differentiation towards the range edge, and no support for decreasing clines in genetic diversity, suggesting dispersal limitation is not characterizing colonization during range expansion, with the implication that the accumulation of expansion load at the range edge is likely not applicable on these spatiotemporal scales. Together, our results suggest that loss of genetic diversity for range-shifting species in the alpine is likely not a key contributing factor to any decreased fitness over time.
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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 | 0.001 | 0.001 |
| 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) | 0.002 | 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".