Post‐fire changes in net shortwave radiation along a latitudinal gradient in boreal North America
Bibliographic record
Abstract
Understanding how a changing boreal fire regime is likely to influence regional climate requires detailed information about fire effects on the surface radiation budget. We used time series of satellite observations of surface albedo from 2000–2011 and fire perimeters since 1970 to study post‐fire changes in surface net shortwave radiation along a latitudinal transect in central Canada. Fire‐induced surface shortwave forcing (SSF) integrated over an annual cycle for the first 30 years after fire was similar (−4.1 W m−2 with a 95% confidence interval of −4.5 to −3.7 W m−2) between southern and northern boreal regions. The lack of a latitudinal difference in SSF was caused by counteracting latitudinal trends in seasonal contributions. Spring (March, April, and May) SSF increased with latitude, from −7.2 W m−2 in the south to −10.1 W m−2in the north, primarily because of delayed snow melt, which amplified albedo differences between unburned forests and recovering stands. In contrast, winter incoming solar radiation and summer albedo change decreased from south to north, resulting in a decreasing latitudinal trend in winter and summer SSF. Vegetation recovery was slower in the north, leading to smaller increases in summer albedo during the first decade after fire, and a prolonged phase of elevated spring albedo during the second decade. Our results indicate that fires reduce surface net shortwave radiation considerably for many boreal forest ecosystems in North America, providing further evidence that disturbance‐mediated shifts in surface energy exchange need to be considered in efforts to manage these forests for climate change mitigation.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".