An initial assessment of winter microclimatic conditions in response to seismic line disturbance in a forested peatland
Bibliographic record
Abstract
Abstract Linear disturbances are widespread in the boreal region of Alberta, Canada. Despite their ubiquitous nature, little is known about their influence on over‐winter meteorological conditions and if and how they alter the snowpack and soil temperature profiles through altered energy and water balances in the wintertime. The presence of seismic lines could affect hydrological processes in both the wintertime and warm months. This will then affect plant communities and carbon cycling on these disturbances. Thus, understanding the effect of seismic lines on meteorological conditions during cold weather conditions will be important to better understand how they alter ecosystem function. Accordingly, this study aims to assess the effect of two seismic lines with different orientations created for petroleum resource exploration on energy and meteorological variables by comparing them with the near surface conditions in the adjacent wooded peatland area from October 2022 to April 2023. We observed 1.8 times higher photon flux density of photosynthetically active radiation on the linear disturbances than in the understory of the undisturbed locations and a greater negative net radiation on the seismic lines compared with that observed off the lines. Furthermore, the average wind speed on the seismic lines were eight and seven times higher at the east–west and south–north oriented seismic lines than the adjacent wooded peatland, respectively. Together, these changes resulted in a denser snowpack on the seismic line and overall higher snow water equivalent in the pre‐melt snowpack. This provided insulation for the soil, and soil temperature on the lines stayed above freezing 7 days longer at the east–west oriented site or retained non‐freezing condition at the south–north oriented site in the upper 15 cm. This would result in more microbial activity and potential higher over‐winter carbon releases.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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 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".