Data from: Recent non-hybrid origin of sunflower ecotypes in a novel habitat
Bibliographic record
Abstract
The genomics of local adaptation is an increasingly active field, providing insights into the forces driving ecological speciation and the repeatability of evolution. Demography and gene flow play an important role in determining the paths by which parallel evolution occurs and the genomic signatures of adaptation. In the annual sunflowers, hybridization between species has repeatedly led to the colonization of extreme habitats, such as sand dunes. In a new case of adaptation to sand dunes that occurs in populations of H. petiolaris growing at Great Sand Dunes National Park and Preserve (Colorado), we wished to determine the age and long-term migration patterns of the system, as well as its ancestry. We addressed these questions with restriction-associated DNA (RAD) sequence data, aligned to a reference transcriptome. In an isolation with migration model using RAD sequences, coalescent analysis showed that the dune ecotype originated since the last ice age, which is very recent compared with the hybrid dune species, H. anomalus. Large effective population sizes and substantial numbers of gene migrants per generation between dune and nondune ecotypes explained the highly heterogeneous divergence observed among loci. Analysis of RAD-derived SNPs identified heterogeneous divergence between the dune and nondune ecotypes, as well as identifying its nearest relative. Our results did not support the hypothesis that the dune ecotype has hybrid ancestry, suggesting that adaptation of sunflowers to dunes has occurred by multiple mechanisms. The ancestry and long-term history of gene flow between incipient sunflower species provides valuable context for our understanding of ecological speciation and parallel adaptation.
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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 | 0.001 | 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".