Harvest volumes and carbon stocks in boreal forests of Ontario, Canada
Bibliographic record
Abstract
We used models to project forest carbon stocks for a series of harvesting scenarios for 29 boreal forest management units totalling 23.3 million ha in Ontario, Canada. Scenarios evaluated for 2020 to 2050 ranged from a no harvesting option to annual harvesting of 2% of the total merchantable volume present in 2020. For each scenario, we estimated the following carbon quantities: (a) forest ecosystem carbon stocks, (b) sum of carbon stocks in forest ecosystem and harvested wood products (HWP) minus emissions associated with HWP production and decomposition, and (c) net greenhouse gas (GHG) effects of harvesting estimated as (b) combined with emissions avoided by substituting HWP for non-wood materials. The average of each carbon quantity for 2020 to 2050 was linearly dependent on the annual harvest volume. The developed relationships were used to estimate harvest volumes for which the three carbon quantities would equal equilibrium forest ecosystem carbon stocks for a pre-suppression natural disturbance cycle. These estimates indicate the range of harvest volumes for which resulting carbon stocks would equal or exceed those in an unmanaged forest. Also discussed are possible criteria for determining annual harvest volume.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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 teacher head, 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".