Water budget analysis of small forested boreal watersheds: comparison of Sphagnum bog, patterned fen and lake dominated downstream areas in the La Grande River region, Québec
Bibliographic record
Abstract
A water budget analysis (precipitation (P), surface runoff (Q), evapotranspiration (ET) and storage variations (ΔS)) was completed over a 3-year span for two Sphagnum bogs, three patterned fens and two shallow lakes all located in the La Grande River watershed in central Québec. The high variability of P from 2005 to 2007 during summer and fall (July to October) allowed us to produce water budgets over a large spectrum of wetness conditions at seasonal and event timescales. Bogs and fens (not lakes) have the intrinsic ability to keep the water table near the surface most of the time, which affects Q. Fens and lakes showed a similar hydrological behavior when compared to bogs, in spite of differences in Q and ΔS variability due to the typical vegetation structure of fens. This structure also tends to produce sharper rises of Q when compared to lakes that have overall smoother hydrograms. The dominant water budget term for bogs, fens and lakes was ΔS, Q and ET, respectively. Finally, an adaptation of the Penman–Monteith equation was successfully used to estimate potential ET. This revised method is based on peatland vegetation identification that provides a simple weighing factor for stomatal resistance.
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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 | 0.001 | 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".