Element export in runoff from eastern Canadian Boreal Shield drainage basins following forest harvesting and wildfires
Bibliographic record
Abstract
Element export rates from the drainage area of nine harvested, nine burnt, and 16 reference Boreal Shield lake basins in Haute-Mauricie, Québec, were estimated for the 3 years following harvesting or fires. Export rates from the drainage area of the basins were evaluated using lake sampling surveys, estimated hydrological budgets, and estimated nutrient retention during lake transit. Increases in K+, total N, and total P export rates were similar between harvested and burnt drainage areas. However, harvested drainage areas exported more dissolved organic C, while burnt drainage areas exported more Mg2+, NO3-, and SO42-. Potassium cumulative losses in runoff during the 3 years of the study were of a similar magnitude as volatilization losses during fires and corresponded to ~33% of the losses by biomass removal during harvesting. While the increased export rates for N and P following fires or harvesting represented negligible losses of nutrients for the forest, they were important supplementary inputs to lakes. The differences in element export rates observed between harvested and burnt drainage areas indicate that these disturbances have different impacts on biogeochemical cycles in the Boreal Shield forest.
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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 | 0.001 | 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".