Short-term effects of mastication on fuel moisture and thermal regime of boreal fuel beds
Bibliographic record
Abstract
Mechanical mastication is becoming a common fuel management treatment to reduce vertical fuel connectivity, as well as crown fire initiation and potential fire-line intensity, but the moisture dynamics of these novel fuel types have been largely unstudied. We recorded concurrent in situ meteorological observations with moisture and temperature profiles (at depths of 5 and 13 cm) for masticated fuel beds in three treatments in a lodgepole pine (Pinus contorta Dougl. var. latifolia Engelm.) – black spruce (Picea mariana (Mill.) B.S.P.) boreal stand located in the Upper Foothills of west-central Alberta. Mulch at the 5 cm depth remained at or near 100% moisture content for a majority of the observation period within the treatment that lacked any residual canopy cover. Only during a 10-day rain-free period was substantial drying observed at a depth of 5 cm. At the interface with the underlying duff layer, mulch remained at upwards of 150% moisture content. Drying was typically <10% of potential evaporation rates, except on days after rain, when drying equal to 25%–100% of potential evaporation was observed. Thermal properties of the mulch showed approximately five times the thermal diffusivity of soils, but less than a fuel crib, suggesting that masticated fuel beds have a thermal and moisture regime more similar to soils than fuel cribs, with a diffusion-dominated regime enhanced by minor advection. Low moisture movement observed from depth to the surface promoted highly variable surface moisture that created surface mulch with temperatures far in excess of air temperatures during periods of full sun. Such excess temperatures are shown to be an efficient indicator of surface dryness and high ignition probability.
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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 | 0.001 | 0.000 |
| 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 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".