Hydrological resilience to forest fire in the subarctic Canadian shield
Bibliographic record
Abstract
Abstract Understanding the role of forest fires on water budgets of subarctic Precambrian Shield catchments is important because of growing evidence that fire activity is increasing. Most research has focused on assessing impacts on individual landscape units, so it is unclear how changes manifest at the catchment scale enough to alter water budgets. The objective of this study was to determine the water budget impact of a forest fire that partially burned a ~450 km2subarctic Precambrian Shield basin. Water budget components were measured in a pair of catchments: one burnt and another unburnt. Burnt and unburnt areas had comparable net radiation, but thaw was deeper in burned areas. There were deeper snow packs in burns. Differences in streamflow between the catchments were within measurement uncertainty. Enhanced winter streamflow from the burned watershed was evident by icing growth at the streamflow gauge location, which was not observed in the unburned catchment. Wintertime water chemistry was also clearly elevated in dissolved organics, and organic‐associated nutrients. Application of a framework to assess hydrological resilience of watersheds to wildfire reveal that watersheds with both high bedrock and open water fractions are more resilient to hydrological change after fire in the subarctic shield, and resilience decreases with increasingly climatically wet conditions. This suggests significant changes in runoff magnitude, timing and water chemistry of many Shield catchments following wildfire depend on pre‐fire land cover distribution, the extent of the wildfire and climatic conditions that follow the fire.
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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 | 0.001 | 0.001 |
| 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".