Surface water chemistry of burned and undisturbed watersheds on the Boreal Plain: an ecoregion approach
Bibliographic record
Abstract
The water chemistry of the euphotic zone in 12 lakes within burned and reference watersheds on Alberta's Boreal Plain was surveyed two years post-fire. Five burned and four reference lakes were located in the Boreal Foothills (mean elevation = 1048 m) and three reference lakes were situated at lower elevations in the Boreal Mixedwood ecoregion (748 m). Mean dissolved organic carbon (DOC) concentration in lake water from burned watersheds was 1.4-fold higher than in lake water from reference Foothills watersheds, whereas lake colour increased with the area of catchment burned divided by lake volume (r = 0.98). Reference Mixedwood lakes had higher mean total phosphorus (TP, 1.8-fold) and chlorophyll a (chl a; 4.4-fold) concentrations than reference Foothills lakes. Ten additional lakes from a previous study in boreal Alberta were used to further compare water chemistry between ecoregions. Boreal Mixedwood lakes (n = 13) had higher TP (2.3-fold), chl a (3-fold), and Ca 2+ + Mg 2+ (3.3-fold) concentrations than Boreal Foothills lakes (n = 9). Our data suggest an influence of forest fire on lake chemistry in the Boreal Foothills, and demonstrate the need for an ecoregion approach to detect the impacts of watershed disturbance on the Boreal Plain. Key words: watershed disturbance, forest fire, lake nutrients, lake elevation, phosphorus, chlorophyll a, anions, cations, dissolved organic carbon.
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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) | 0.000 | 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".