Morphological variation in a biotically patchy environment : evidence from a pasture population of Trifolium repens l.
Bibliographic record
Abstract
The relationship between morphological variability and biotic environmental heterogeneity was studied in a pasture population of Trifolium repens. It had been argued that the unexpectedly high levels of variation in T. repens could be maintained by diversifying selection. The mosaic of neighbours (perennial grasses) with which T. repens coexists constitutes a prominent element of biotic patchiness that may lead to sorting among T. repens genotypes on the basis of neighbour-specific compatibilities. A variation study was conducted on a set of 400 individuals of T. repens collected on a neighbour-specific basis from a 43 year old pasture and grown for one season under common garden conditions. A significant proportion of the variation in a set of twelve morphological characters was accounted for by the neighbour with which the individual of T. repens had been growing in the field. The actual amount of variation accounted for, however, was low (6-19%). It was concluded that although diversifying selection could be operating in the pasture, it is not of primary importance in the maintenance of variation in this population. A repeat study was carried out after the plants had spent two years in the common garden. None of the earlier among-neighbour differences in morphology were retained. I concluded that the original results reflected developmental differences carried over from the pasture.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".