Detecting small‐scale genotype–environment interactions in apomictic dandelion (<i>Taraxacum officinale</i>) populations
Bibliographic record
Abstract
Studies of genotype × environment interactions (G × E) and local adaptation provide critical tests of natural selection's ability to counter opposing forces such as gene flow. Such studies may be greatly facilitated in asexual species, given the possibility for experimental replication at the level of true genotypes (rather than populations) and the possibility of using molecular markers to assess genotype-environment associations in the field (neither of which is possible for most sexual species). Here, we tested for G × E in asexual dandelions (Taraxacum officinale) by subjecting six genotypes to experimental drought, mown and benign (control) conditions and subsequently using microsatellites to assess genotype-environment associations in the field. We found strong G × E, with genotypes that performed poorly under benign conditions showing the highest performance under stressful conditions (drought or mown). Our six focal genotypes comprise > 80% of plants in local populations. The most common genotype in the field showed its highest relative performance under mown conditions (the most common habitat in our study area), and almost all plants of this genotype in the field were found growing in mowed lawns. Genotypes performing best under benign experimental conditions were found most frequently in unmown conditions in the field. These results are strongly indicative of local adaptation at a very small scale, with unmown microsites of only a few square metres typically embedded within larger mown lawns. By studying an asexual species, we were able to map genotypes with known ecological characteristics to environments with high spatial precision.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".