Selection pressures have caused genome‐wide population differentiation of<i>Anthoxanthum odoratum</i>despite the potential for high gene flow
Bibliographic record
Abstract
The extent to which divergent selection can drive genome-wide population differentiation remains unclear. Theory predicts that in the face of ongoing gene flow, population differentiation should be apparent only at those markers that are directly or indirectly (i.e. through linkage) under selection. However, if reproductive barriers limit gene flow, genome-wide population differentiation may occur even in geographically proximate populations. Some insight into the link between selection and genetic differentiation in the presence of ongoing gene flow can come from long-term experiments such as The Park Grass Experiment, which has been running for over 150 years, and provides a unique example of a heterogeneous environment with a long and detailed history. Fertilizer treatments applied in the Park Grass Experiment have led to rapid evolutionary change in sweet vernal grass Anthoxanthum odoratum, but until now, nothing was known of how these changes would be reflected in neutral molecular markers. We have genotyped ten A. odoratum populations from the Park Grass Experiment using Amplified Fragment Length Polymorphisms (AFLPs). Our data show that nutrient additions have resulted in genome-wide divergence among plots despite the high potential for ongoing gene flow. This provides a well-documented example of concordance between genomes and environmental conditions that has arisen in continuous populations across a time span of fewer than 75 generations.
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 | 0.001 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".