On the economics of Norway spruce stands and carbon storage
Bibliographic record
Abstract
We combine a process-based growth model for even-aged Norway spruce (Picea abies (L.) Karst.) with economics and optimization. Carbon storage is subsidized based on stand growth and product decay. We include detailed optimized thinnings and timber quality features and present cost functions for stand-level CO 2 storage. In contrast to earlier studies, our results suggest that changing thinning strategies and postponing thinnings are at least as important as lengthening the rotation period when considering economically efficient carbon storage. The role of thinning is most important in less fertile sites. Contrary to the generic Faustmann model, a higher interest rate increases rotation length on our fertile site. Including carbon release from decaying timber products as reductions from carbon subsidies only has minor effects on optimal solutions. The fertile site stores more discounted carbon. However, with a 1% interest rate, the less fertile site is cost-efficient up to 13 CO 2 t·ha −1 , and with a 3% interest rate, it is cost-efficient up to 14 CO 2 t·ha −1 . After these points, carbon storage on the fertile site becomes cheaper. The economic costs of carbon storage suggest that it is optimal to apply carbon storage in Norway spruce forests to meet greenhouse gas reduction commitments.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".