Modelling hydrological responses of a peatland to disturbance by geologic exploration
Bibliographic record
Abstract
The slow recovery of trees in peatlands disturbed by linear clearings that arise from geologic exploration, also known as seismic lines, has spurred scholarly investigation into the underlying factors. The effect of tree canopy removal on the line on local water balance is one of the unanswered questions in past studies. Hence, this study aimed to provide insights into the impact of seismic lines on water balance components using CoupModel. Simulated values were compared with field measurements from a seismic line located in Fort McMurray, Alberta, Canada. The simulations indicated an increase in precipitation, soil moisture and temperature, and snow depth on the seismic line compared to undisturbed conditions with results aligned with the field measurements. Simulations also showed that the snow density on the seismic line was 4.6 % higher than the adjacent natural area (herein referred to as offline). Furthermore, the predicted shallower groundwater depth on the line was consistent with the observations. Although simulated net radiation off the line was higher than on the line, the actual evapotranspiration (AET) on the line was 8.3% higher than off the line. It was also found that evaporation from moss is the dominant component of the AET from the seismic line and adjacent natural area. However, greater precipitation inputs due to reduced interception outweighed the high AET on the seismic line, so that the seismic line had higher water storage than off the line by 38%. Sensitivity indicated the importance of site location (i.e., latitude), soil physical properties, and leaf area index parameters in simulations. As a consequence, the initial model of water balance necessitates future researchers to explore the impact of different seismic lines, particularly at the catchment scale, to better understand the cumulative impact of these disturbances on water balance in boreal ecosystems.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".