Impacts of an intense wildfire smoke episode on surface radiation, energy and carbon fluxes in southwestern British Columbia, Canada
Bibliographic record
Abstract
A short, but severe, wildfire smoke episode in July 2015, with an aerosol optical depth (AOD) approaching 9, is shown to strongly impact radiation budgets across four distinct land-use types (forest, field, urban and wetland). At three of the sites, impacts on the energy balance are also apparent, while the event also appears to elicit an ecosystem response with respect to carbon fluxes at the wetland and a forested site. Greatest impacts on radiation and energy budgets were observed at the forested site where the role of canopy architecture and the complex physiological responses to an increase in diffuse radiation were most important. At the forest site, the arrival of smoke reduced both sensible and latent heat flux substantially but also lowered sensible heat flux more than the latent heat flux. With widespread standing water, and little physiological control on evapotranspiration, the impacts on the partitioning of turbulent fluxes were modest at the wetland compared to the physiologically dominated fluxes at the forested site. Despite the short duration and singular nature of the event, there was some evidence of a diffuse radiation fertilization effect when AOD was near or below 2. With lighter smoke, both the wetland and forested site appeared to show enhanced photosynthetic activity (a greater sink for carbon dioxide). However, with dense smoke, the forested site was a strong carbon source. Given the extensive forest cover in the Pacific Northwest and the growing importance of forest fires in the region, these results suggest that wildfire aerosol during the growing season potentially plays an important role in the regional ecosystem response to smoke and ultimately the carbon budget of the region.
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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 | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".