The effects of harvest intensity and seedbed type on germination and cumulative survivorship of white spruce and balsam fir in northwestern Quebec
Bibliographic record
Abstract
The effects of different harvest intensities, including uncut, 1/3 and 2/3 partial cuts, clearcuts with and without slash, were investigated on the germination and cumulative survivorship of white spruce and balsam fir over 2 consecutive years. We also investigated the regenerative capacity of both species on three different seedbeds across all harvest intensities. The seedbeds included were mineral, humus, and organic soil. At the germination stage, both species were strongly affected by seedbed type (p < 0.032). The germination rates of fir seeds in partial cuts were significantly greater than clearcut treatments, but spruce remained unaffected at this stage by harvest intensity. The addition of slash improved the germination rates of fir relative to the clear-cut plots without slash. The germination rates the following year were reduced on mineral soil for spruce. The cumulative survivorship at the end of the third summer still showed a significant seedbed response for both species (p < 0.007) and a significant harvest response for fir (p < 0.005). The cumulative survivorship of the second fir cohort was no longer affected by either harvest or seedbed type. Spruce, however, was still affected by seedbed type (p = 0.006). The data from this study provide us with a more detailed description of the fate of cohorts recruited following a harvest operation. Still, what remains to be studied is the fate of these cohorts over the next 510 years.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 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".