Landscape patterns of phenotypic variation and population structuring in a selfing grass,<i>Elymus glaucus</i>(blue wildrye)
Bibliographic record
Abstract
Source-related phenotypic variance was investigated in a common garden study of populations of Elymus glaucus Buckley (blue wildrye) from the Blue Mountain Ecological Province of northeastern Oregon and adjoining Washington. The primary objective of this study was to assess geographic patterns of potentially adaptive differentiation in this self-fertile allotetraploid grass, and use this information to develop a framework for guiding seed movement and preserving adaptive patterns of genetic variation in ongoing restoration work. Progeny of 188 families were grown for 3 years under two moisture treatments and measured for a wide range of traits involving growth, morphology, fecundity, and phenology. Variation among seed sources was analyzed in relation to physiographic and climatic trends, and to various spatial stratifications such as ecoregions, watersheds, edaphic classifications, etc. Principal component (PC) analysis extracted four primary PCs that together accounted for 67% of the variance in measured traits. Regression and cluster analyses revealed predominantly ecotypic or stepped-clinal distribution of genetic variation. Three distinct geographic groups of locations accounted for over 84% of the variation in PC-1 and PC-2 scores; group differences were best described by longitude and ecoregion. Clinal variation in PC-3 and PC-4 scores was present in the largest geographic group. Four geographic subdivisions were proposed for delimiting E. glaucus seed transfer in the Blue Mountains.Key words: Elymus glaucus, morphological variation, local adaptation, seed transfer, seed zones, polyploid.
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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 | 0.000 | 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 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".