<i>Sphagnum</i> mosses limit total carbon consumption during fire in Alaskan black spruce forests
Bibliographic record
Abstract
The high water retention of hummock-forming Sphagnum species minimizes soil moisture fluctuations and might protect forest floor organic matter from burning during wildfire. We hypothesized that Sphagnum cover reduces overall forest floor organic matter consumption during wildfire compared with other ground-layer vegetation. We characterized variability in soil organic layer depth and organic matter stocks in two pairs of burned and unburned black spruce ( Picea mariana (Mill.) BSP) stands in interior Alaska. In the unburned stands, microsites dominated by Sphagnum had more than twice as much soil organic matter·m –2 as microsites dominated by feather moss and (or) lichens. Whereas 20% of soil organic matter was consumed during fire in microsites dominated by Sphagnum, 45% was consumed in microsites dominated by the feather moss and (or) lichens. Across 79 recently burned black spruce stands, unburned moss abundance (primarily remnant Sphagnum hummocks), landscape position (backslope, flat upland, flat lowland classes), and the interaction among these variables explained 60% of postfire organic soil depths. We suggest that “Sphagnum sheep” could serve as a useful visual indicator of variability in postfire soil carbon stocks in boreal black spruce forests. Sphagnum mosses are important ecosystem engineers not only for their influence on decomposition rates, but also for their effect on fuel consumption and fire patterning.
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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 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".