Ageing forests and carbon storage: a case study in boreal balsam fir stands
Bibliographic record
Abstract
Abstract The pattern of change in carbon (C) accumulation with forest ageing can vary greatly amongst different forest types. Documenting how C accumulates in various forest ecosystems in the absence of logging makes it possible to predict what would be the outcome of extending forest rotations or in dedicating more land to conservation on C storage. This study was conducted in boreal balsam fir (Abies balsamea (L.) Mill.) forests of Quebec, in eastern Canada. We compared carbon stocks in forest pools (aboveground (live) biomass, deadwood, FH horizon and mineral soil) of mature (70 years after harvest) vs old-growth stands (stands with no signs or history of human disturbance). Total ecosystem C stocks were not significantly different between mature and old-growth stands. However, as mature stands transition to old-growth stage, there appears to be a shift of C from live biomass pools towards deadwood and soil FH horizons. Coarse woody debris in old-growth stands were also found to be at more advanced stages of decay. The variability of C stocks was also high amongst old-growth stands; however, there was no obvious difference in structural diversity between mature and old-growth stands. Results suggest that ageing balsam fir stands through the lengthening of forest rotations (e.g. past the maturity age of 70 years) or by placing them under conservation, while not creating an important C sink, still contributes to maintain large forest C stocks across landscapes. Preserving or increasing the presence of old-growth forests is an important aspect of ecosystem-based forest management; our study concludes that it could also be compatible with sustainable forest carbon management.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".