Recovery rates of white spruce and balsam fir on seismic lines in NW Alberta, Canada
Bibliographic record
Abstract
Anthropogenic disturbances have marked Alberta's boreal forest with an extensive network of seismic lines. These are linear disturbances (3–10 m wide) created during oil and gas exploration that have fragmented woodland caribou habitat, resulting in the loss and degradation of ecosystem services. The natural regeneration of trees on seismic lines can support predator-use reduction in caribou habitats; for this reason, 3 m tall trees at a minimum density of 2000 stems per hectare (sph) has been cited as the target for seismic line recovery. However, there is currently no regulatory requirement for their restoration. As such, there is limited baseline ecological knowledge of natural forest recovery on seismic lines, including the rate of tree regrowth. This study aimed to fill this gap by comparing the growth of two common conifer species, white spruce and balsam fir, on seismic lines to trees in the adjacent, mature forest in an upland conifer mixedwood stand located in northwest Alberta. The results showed that white spruce and balsam fir regenerating on seismic lines will take approximately 29–33 years to reach the 3 m tall and 2000 sph criteria, which should support predator-use reduction of seismic lines. It is difficult to determine whether the regeneration rate on seismic lines will be impactful to the restoration of the woodland caribou habitat; this impact will be further investigated in modelling exercises for land use planning purposes.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".