On the carbon additionality of working forests
Bibliographic record
Abstract
Purpose Using a 62,742-ha working forest in New Brunswick, Canada, we examine the benefit and cost of carbon additionality at the landscape level. Design/methodology/approach The baseline scenario is set to maximize timber profit over a 100-year planning period, whereas the carbon scenario is set to have a 5- or 10-year rotation extension. Findings At a carbon price of $8/tCO2e, the benefit of additional carbon sequestration from the working forest cannot offset its cost. For the benefit-cost ratio to be one, the respective break-even price needs to be $21/tCO2e for the 5-year rotation extension and $25/tCO2e for the 10-year rotation extension. Originality/value This study analyzes the carbon additionality and economics of working forests at the 50–100 thousand hectare scale. Specifically, we examine the change in benefit and cost between a baseline scenario of timber management only and a scenario of rotation extension for both timber and carbon sequestration.
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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 | 0.003 |
| 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) | 0.004 | 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".