Dynamics in tree structure and composition along boreal forest edges: A case study in Alberta’s in situ oil sands
Bibliographic record
Abstract
Forest edge effects, which result from changes in abiotic and biotic factors after disturbance, benefit early seral species while displacing interior forest specialists that rely on more stable, undisturbed conditions. This study investigated how anthropogenically-created forest edges, particularly in upland boreal forests of Alberta’s oil sands region, influence forest structure and composition. Due to underground bitumen exploration and extraction, the area has experienced significant forest fragmentation, creating an extensive network of footprints, with some footprints having local densities reaching up to 40 km/km 2 . We examined how the interaction of distance from forest edge and edge orientation across different gap sizes from oil sands disturbances influences size-dependent mortality, recruitment, and stem density of trees. Field data were collected in 2023 and 2024 along 46 forest edge sites, with edge effects found to be more pronounced with larger adjacent disturbance footprints. Large-tree mortality was higher along west-facing (direction of prevailing winds) edges, particularly against wellpad disturbances. Recruitment of trees was inversely related to edge distance, although local responses varied by orientation of the edge. For example, recruitment was higher along west-facing edges when compared to south-facing edges. Stem densities overall were highest near edges (0–20 m), supporting an edge sealing effect along edges of both disturbances. Our results emphasize edge orientation as a key factor influencing the magnitude and extent of edge effects in forest structure along linear and non-linear oil sands footprints. Given the extensive network of edges in the region, even minor edge effects can accumulate, leading to substantial, landscape-scale influence on forest structure and composition.
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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) | 0.000 | 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".