Effects of Narrow Linear Disturbances on Light and Wind Patterns in Fragmented Boreal Forests in Northeastern Alberta
Bibliographic record
Abstract
Forest fragmentation threatens forest biodiversity and ecosystem function. One of the concerns relates to increases in edge effects, which among other things affects the forest microclimate that influences the distribution and behavior of species. In Alberta, Canada, boreal anthropogenic disturbances from in situ oil exploration are increasing forest fragmentation, especially in the form of exploratory well pads and seismic lines (i.e., linear forest clearings created during the exploration phase of oil extraction). Dissection of these forests by seismic lines has the potential to change local patterns in wind and light, and thus may alter forest communities. Although alterations of these abiotic conditions are likely, the magnitude of these changes is unknown, particularly the effects of changes in the width and orientation of linear disturbances. Here we investigated changes in light and wind on seismic lines compared to that of adjacent undisturbed forests and nearby cleared openings. Specifically, we examined how seismic line characteristics (i.e., line direction, line width, and adjacent canopy height) altered local responses in these abiotic conditions. Generalized Linear Mixed Effect models predicted a 2-fold increase in average light intensity and maximum wind speeds, and a 4-fold increase in average wind speeds on seismic lines compared to adjacent forests. These changes did not approach the conditions in large openings, which compared to forests had a 3-fold increase in average light intensity, a 16-fold increase in average wind speeds, and a 4-fold increase in maximum wind speeds. Line width and orientation interacted with adjacent forest height altering the abiotic environment with wider lines having a 3-fold increase on maximum wind speed. We conclude that even localized, narrow (<10-m wide) forest disturbances associated with oil sands exploration alter forest microclimatic conditions. Recent changes in practices that reduce line width as well as promoting tree regeneration, will minimize the environmental effects of these anthropogenic disturbances.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".