Dynamic old-growth forests? A case study of boreal black spruce forest bryophytes
Bibliographic record
Abstract
Old-growth forests have sparked significant interest over the last twenty years and definitions have evolved from structure based to process based, acknowledging the diversity of forests that could be considered old growth. However studies frequently group all forests over a certain age into a single type, negating the dynamic processes that create old growth. In this study we examine a 2350-year chronosequence in boreal black spruce forests in northwestern Quebec to determine whether continued community change can be observed in the bryophyte layer. Bryophytes dominate the understory of boreal forests and influence ecosystem functioning, particularly in paludified forests where production exceeds decomposition in the organic layer. Community composition and richness changed throughout the chronosequence with no evidence of a steady state associated with an old-growth phase. In contrast the bryophyte community continued to evolve with multiple phases being evident. These results suggest that old-growth forests on the Clay Belt of northwestern Quebec and northeastern Ontario, Canada, should be regarded as part of the continuous gradient in forest development rather than a single state. This complicates conservation of these forests as multiple phases should be considered when planning forest reserves.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".