The reduction of organic-layer depth by wildfire in the North American boreal forest and its effect on tree recruitment by seed
Bibliographic record
Abstract
We compared prefire and postfire organic-layer depths in boreal forest types (14 fires) across Canada, and examined tree recruitment as a function of depth. There was extensive within-stand variation in depth, much of it due to clustering of thinner organic layers around boles. There were no significant differences in postfire organic-layer depth among sites with different prefire forest species composition, but sites in the eastern boreal region had thicker postfire organic layers than those in the western boreal region. Mean organic-layer depth was much greater in intact stands than after fires; overall, fire reduced organic-layer depth by 60%, largely because of increases in the area of thin (<3 cm) organic layers (1% in intact stands vs. 40% in postfire stands). There was more variation in organic-layer depth within postfire than within prefire stands; notably, some areas in postfire stands were deeply combusted, while adjacent parts were only lightly combusted. We speculate that the diminished role of energy loss to latent heat around tree boles increased organic-layer consumption around tree boles. Seedlings were clustered around burned tree bases, where organic layers were thinner, and the dependence of a species on thin organic layers was an inverse function of seed size.
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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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".