Vegetation and prescribed fire: Implications for Stone's sheep and elk
Bibliographic record
Abstract
ABSTRACT Fire is the dominant single natural disturbance influencing northern mountain and boreal landscapes. We evaluated fire‐induced changes in forage resources for 2 focal ungulates, Stone's sheep (Ovis dalli stonei) and elk (Cervus canadensis), in northern British Columbia, Canada. We implemented 4 prescribed fires and monitored short‐term vegetation (quantity and quality) and ungulate (Stone's sheep and elk) responses. We took measurements prior to burning, the year of burning, and 1 year after burning in treatment areas and adjacent unburned control areas in winter and summer at 2 scales. At a fine scale, we used vegetation transects and pellet counts; at the landscape scale, we used Landsat imagery for vegetation and aerial survey flights for animals. Following prescribed fire, shrub cover declined and burned communities increased in herbaceous cover. Plant species diversity also declined but increased to almost that of unburned areas by 1 year after burning. Burning increased quality of forage most (2–7 percentage points more digestibility and 0.3–6.3 percentage points more crude protein than unburned areas) in the summer of the burn. In winter, forage biomass and available digestible dry matter increased to pre‐burn levels by 1 year after burning. Stone's sheep and elk always used burned areas more than unburned control areas in winter at both scales. Whereas elk used sites with higher forage quantity, Stone's sheep appeared to respond to forage quality at the fine scale. Ungulate grazing during the 2 years of this study did not alter forage quantity on burned or unburned sites, as determined from range exclosures. Based on our findings in this area, maximum benefits to elk would be achieved from large prescribed fires on south‐aspect slopes that result in the greatest amounts of forage biomass. Smaller prescribed fires at high burn intensities on west‐aspect slopes intermixed with rocky outcrops and talus scree (less frequented by elk) would most benefit Stone's sheep requirements for high‐quality forage and escape terrain. © 2018 The Wildlife Society.
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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 | 0.000 | 0.000 |
| 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) | 0.001 | 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".