Recovery Rates of Black Spruce and Tamarack on Lowland Seismic Lines in Alberta, Canada
Bibliographic record
Abstract
The cumulative impact of decades of oil and gas exploration has left Alberta’s boreal forests densely fragmented by seismic lines, which are expected to naturally regenerate; however, recovery is often highly variable and generally poor in peatlands due to increased wetness and reduced microtopography. In this study, we evaluated seismic lines in lowland ecosites with some degree of successful natural regeneration to gain a better understanding of the natural recovery process in these areas. We compared stand characteristics between the seismic line (23 to 48 years post-disturbance) and the adjacent undisturbed forest. We found that soil properties were similar, but seedling (height < 1.3 m) density was significantly higher on the seismic line, with 252% more tamarack and 65% more black spruce than in the adjacent forest. Relative to the adjacent forest, there were significantly fewer trees (height > 1.3 m) on the seismic line, with an 84% and 50% reduction in black spruce and tamarack, respectively. By analyzing tree ring data from seismic lines, we found that the length of time before tree establishment was 10 years for black spruce and 8 years for tamarack. On average, it took 12 years for tree density to reach 2000 stems per hectare (sph). We modeled growth rates for black spruce and tamarack and found that they were growing faster than their adjacent forest counterparts, reaching 3 m after an average of 38 and 33 years, respectively. Stands on seismic lines were projected to a final stand age of 61 years using the Mixedwood Growth Model (MGM) to evaluate future stand characteristics.
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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".