An assessment of variation in Idaho fescue [<i>Festuca idahoensis</i> (Elmer)] in southern Alberta
Bibliographic record
Abstract
Idaho fescue (Festuca idahoensis Elmer) is a native grass species that has attracted interest for use in revegetation, reclamation and other applications. However, there is a serious shortage of commercially available seed and concern that germplasm used will not be adapted to the site. A component of adaptation is genetic variability that allows a species to occupy a greater range of environments. Field trials were conducted in southern Alberta to determine the genetic variability of phenotypic and performance characteristics among genotypes of Idaho fescue. Since grazing pressure may contribute to genetic selection and may therefore affect the variability within a population, we also compared genotypes taken from a heavily grazed paddock with those taken from a lightly grazed paddock. Forty-nine genotypes from three populations were randomly sampled in 1992, propagated vegetatively to produce plants for replicated trials and planted in four locations in 1993. Nine plant characteristics were observed from 1993 to 1997. Since the genotypes were grown in common environments, variation among them was assumed to be caused by genetic differences. All variables were affected (P < 0.05) by population, test location and year, while the effect of population was also influenced by test location and year for a few variables. While the Idaho fescue plants expressed differences (P < 0.05) among populations for all selected traits, they displayed considerable overlap in the range of values for all variables both within and among test locations. Therefore, while the populations may be different, individuals within populations exhibit common attributes over a large range. This suggests that sufficient genetic variability exists in all populations to allow successful establishment over a large range of environmental variability. Results from a secondary test suggest that selection pressure, induced by grazing, resulted in genotypes that were smaller in crown circumference, had less spring vigor, had shorter flowering tillers and produced less seed. However, this observation needs further validation with a more robust test. Key words: Morphology, genotypes, seed yield, winter kill, grazing response
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".