Remarkable life history polymorphism may be evolving under divergent selection in the silverleaf sunflower
Bibliographic record
Abstract
Substantial intraspecific variation in life history is rare and potentially a signal of incipient ecological speciation, if variation is driven by geographically heterogenous natural selection. We present the first report of extensive life history polymorphism in Helianthus argophyllus, the silverleaf sunflower, and examine evidence for its evolution by divergent selection. In 18 populations sampled from across the species range and grown in a common garden, most quantitative traits covaried such that individuals could be assigned to two distinct life history syndromes: tall and late flowering with small initial flowerheads, or short and early flowering with larger initial flowerheads. Helianthus argophyllus exhibits regional genetic structure, but this population structure does not closely correspond with patterns of phenotypic variation. The early-flowering syndrome is primarily observed in populations from coastal barrier islands, while populations from the nearby mainland coast, although geographically and genetically close, are primarily late flowering. Additionally, several traits are more differentiated among regions than expected based on neutral genetic divergence (QST > FST ), including the first principal component score corresponding with life history syndrome. This discordance between patterns of phenotypic and genetic variation suggests that divergent selection is driving genetic differences in life history across the species range. If so, the silverleaf sunflower may be in early stages of ecological speciation.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".