Effect of Fire Intensity and Depth of Burn on Lowbush Blueberry, <em>Vaccinium angustifolium</em>, and Velvet Leaf Blueberry, <em>Vaccinium myrtilloides</em>, Production in Eastern Ontario
Bibliographic record
Abstract
The effects of prescribed fire intensity and depth of burn were investigated on Lowbush Blueberry (Vaccinium angustifolium) and Velvet Leaf Blueberry (Vaccinium myrtilloides) stem density, blueberry production and the number of blueberries/stem in a clear-cut Jack Pine, Pinus banksiana, ecosystem of eastern Ontario. Blueberry production and stem density were significantly (P < 0.001) increased by low intensity prescribed fires of 597 and 1268 kW/m. In contrast, prescribed fires of medium and high intensities did not affect blueberry production and stem density. The number of blueberries/stem was not affected (P = 0.056) by prescribed burning, two years after treatment. Pearson's multiple correlation analysis showed that blueberry production (R: -0.683, P < 0.01), stem density (R: 0.733, P < 0.01) and the number of blueberries/stem (R: 0.803, P < 0.01) correlated with depth of burn. As well, blueberry production (R: 0.507, P < 0.05) and stem density (R: -0.504, P < 0.05) correlated with fire intensity. Depth of burn was a better predictor of berry production and stem density than fire intensity. These results suggest that only low intensity fires with little penetrating effect in the ground should be used to manage blueberry crops.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 teacher head, 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".