Genetic differentiation is determined by geographic distance in <i>Clarkia pulchella</i>
Bibliographic record
Abstract
Abstract Both environmental differences and geographic distances may contribute to the genetic differentiation of populations on the landscape. Understanding the relative importance of these drivers is of particular interest in the context of geographic range limits, as both swamping gene flow and lack of genetic diversity are hypothesized causes of range limits. We investigated the landscape genetic structure of 32 populations of the annual wildflower Clarkia pulchella from across the species’ geographic range in the interior Pacific North-west. We tested whether climatic differences between populations influenced the magnitude of their genetic differentiation. We also investigated patterns of population structure and geographic gradients in genetic diversity. Contrary to our expectations, we found an increase in genetic diversity near the species’ northern range edge. We found no notable contribution of climatic differences to genetic differentiation, indicating that any processes that might operate to differentiate populations based on temperature or precipitation are not affecting the putatively neutral loci in these analyses. Rather, these results support seed and pollen movement at limited distances relative to the species’ range and that this movement and the subsequent incorporation of immigrants into the local gene pool are not influenced by temperature or precipitation similarities among populations. We found that populations in the northern and southern parts of the range tended to belong to distinct genetic groups and that central and eastern populations were admixed between these two groups. This pattern could be the result of a past or current geographic barrier associated with the Columbia Plateau, or it could be the result of spread from separate sets of refugia after the last glacial maximum.
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 | 0.000 |
| 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) | 0.001 | 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".