Ten‐year water table recovery after clearcutting and draining boreal forested wetlands of eastern Canada
Bibliographic record
Abstract
Abstract In boreal forested wetlands, the observed increase in the water table level after clearcutting (watering‐up) is often a threat to sustained ecosystem productivity. Hydrologic recovery refers to the processes by which a water table progressively drops back to its initial level after the cut. In eastern Canada, drainage is used operationally after clearcutting wet sites in order to lower the water table level and accelerate hydrologic recovery. The objective of this study was to evaluate the duration of the watering‐up caused by timber harvesting and the extent to which drainage affected the water table recovery on five peatlands and three hydromorphic mineral sites located in the St. Lawrence Lowlands of Québec (Canada). The mixed wood stands studied are dominated by balsam fir ( Abies balsamea (L.) Mill.), eastern white cedar ( Thuja occidentalis L.), and red maple ( Acer rubrum L). Results indicate that, 10 years after clearcutting, water table levels in undrained plots are still 5 to 7 cm higher than the pre‐cut levels. The slight recovery in water table level plateaued after the third year. Rainfall interception by vegetation was also monitored, and after 10 years had reached nearly 50% of the pre‐cut rate. The immediate water table drawdown following drainage mitigated watering‐up within 40 m of a ditch. The persistent watering‐up observed in this study should encourage using sylvicultural systems adapted to boreal forested wetlands in order to prevent productivity loss and stand conversion. Copyright © 2008 John Wiley & Sons, Ltd.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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 teacher head, 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".