Phylogeography of<i>Camassia quamash</i>in western North America: postglacial colonization and transport by indigenous peoples
Bibliographic record
Abstract
Recent human activities have spread numerous plant species across the globe, yet it is unclear to what degree historical human activities influenced plant dispersal. In western North America, Camassia quamash was one of the most important food plants for indigenous peoples, who transported its propagules either intentionally or accidentally. We investigated how human and natural dispersal might have contributed to the current pattern of spatial genetic structure in C. quamash by performing phylogeographical surveys at two geographical scales. We sequenced two noncoding regions of chloroplast deoxyribonucleic acid (DNA) in 226 individuals from 53 populations of C. quamash as well as 126 individuals from 21 populations of the non-food plant Zigadenus venenosus. Contrary to the expectation of anthropogenic transport, C. quamash populations did not exhibit weaker genetic structure than Z. venenosus populations. We also failed to find convincing evidence for signatures of transport. Instead, our data showed strong effects of past glaciation and geographical barriers of the mountains in the Cascade Range, Olympic Peninsula and Vancouver Island. West of the Cascades, the species appears to have largely migrated northward from a southern refugium after deglaciation, whereas few populations having a highly divergent haplotype might have survived in southwestern Washington. Our data suggest that despite substantial ethnobotanical evidence for anthropogenic transport, the current pattern of genetic structure of C. quamash does not show any detectable signatures of transport by indigenous peoples and is better understood as the result of natural dispersal processes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".