Close-to-nature silviculture in eastern Quebec: Advances over the last decade
Bibliographic record
Abstract
The increase in intensity of the harvesting of eastern Quebec’s forests has resulted in profound compositional changes at the stand level. The composition and structure of presettlement stands provide key benchmarks when implementing ecosystem-based management (EBM). A core principle of EBM is the emulation of natural disturbances, and it is hypothesized that forest resilience will be maintained. Managers have thus adapted some of their silvicultural activities to better mimic the main natural disturbances in eastern Quebec. These adaptations include using variable retention harvesting systems instead of clear-cuts and converting even-aged stands. Nevertheless, other close-to-nature silvicultural practices must be developed, as gaps between managed and unmanaged stands persist. Most importantly, there is a need to consider global change within EBM, which could be accomplished by prioritizing forest functions rather than composition or structure when establishing silvicultural objectives. Elements of the complex adaptive systems approach to increasing forest resilience can be incorporated into the larger-scale EBM approach. This could be done by considering the functional complementarity of species, forest function, and stand structure in forest management planning. These efforts must not be constrained, however, to allowable annual cut calculations, as these are not sufficiently sensitive to compare different management scenarios.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".