Modelling the dynamics of white and red pine coarse woody debris in central Ontario
Bibliographic record
Abstract
Although forest management practices have been widely found to have negative effects on coarse woody debris (CWD), the long-term dynamics of these resources under partial harvesting systems in Ontario are poorly understood. I developed stage-based models of pine (Pinus strobus and P. resinosa) snag and downed woody debris decomposition over time. Using these decomposition models, a stand growth simulator, and data on the immediate impacts of harvesting and fire on CWD, I projected CWD accumulations in undisturbed pine stands, those subjected to periodic surface fires, and those managed under the uniform shelterwood silvicultural system. The modelled abundances of several types of CWD, particularly snags, were reduced at some or all points of the shelterwood harvest cycle relative to the other two scenarios. These simulation results suggest that additional management guidelines may be needed if adequate levels of specific CWD resources are to be continuously maintained in Ontario's shelterwood-managed pine forests.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".