Resilience of Foothills Rough Fescue, Festuca campestris, rangeland to wildfire
Bibliographic record
Abstract
A three year monitoring program evaluated the effects of a December 1997 wildfire in southwest Alberta, on Foothills Rough Fescue grassland species composition, ground cover, herbage production, and forage quality.Changes in species abundance included a reduction in grass cover (p<0.10) after burning.Rough Fescue also increased seedhead production during the second year after fire (p =0.08).Relative to the unburned area, graminoid production declined (p< 0.05) by approximately 40% with burning, while forb production was unaffected.By the second growing season, live plant cover and herbage production had recovered on the burned area.The forage quality of individual Foothills Rough Fescue plants was greater on the burned area, with the greatest increase in crude protein in 1998 (p<0.10), and energy and total digestibility in 1999 (p< 0.05).Increased quality may be linked to the level of forage production, as well as a fire-induced delay in plant phenology.Although soil erosion appeared to be minimal, there was an increase in exposed soil and a corresponding decline in litter and mulch cover (p< 0.05).Greater nitrogen levels (p= 0.051) were found in creeks downstream of the burn area during 1998, indicating some nutrient losses may be attributed to the fire.Although the grasslands examined displayed considerable resilience to this severe wildfire, favourable recovery was probably linked to the high precipitation during 1998, when summer rainfall was 48% above average.
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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".