Boreal tree regeneration after fire and fuelwood harvesting in coastal Nunatsiavut
Bibliographic record
Abstract
Consecutive landscape-scale disturbances are known to influence boreal forest regeneration, yet few published data exist on the compounding effects of natural and anthropogenic disturbance on regeneration in subarctic forests. We conducted a dendroecological study of eastern coastal boreal forest regeneration two decades after fire at three subarctic forest stands that are important sources of fuelwood for the people of Nunatsiavut (Labrador, Canada). We quantified spruce (Picea spp.) and balsam fir (Abies balsamea (L.) Mill.) seedling regeneration, standing dead tree density, trees harvested within burned forests, and aged proximal unburned stands. Age of unburned forest varied with site; however, each exhibited continuous regeneration over several decades. Despite low seedling regeneration at each site (stems·m −2 ; less than 35% of pre-fire stem density), model results indicated harvesting post-fire did not impact seedling regeneration. Findings suggest a negative pressure on seedling abundance from increased presence of tall multi-stemmed shrubs, yet we argue that because stands exhibit a range in tree age, shrubs may be a set of early successional species rather than indicating a change in successional trajectory. Examination of a larger chronosequence within coastal forest stands of Nunatsiavut is warranted to further understand forest regeneration in the eastern subarctic under changing disturbance regimes.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".