The economics of timber and bioenergy production and carbon storage in Scots pine stands
Bibliographic record
Abstract
We optimize timber and bioenergy production combined with carbon storage in Scots pine (Pinus sylvestris L.) stands, using an ecological-economic model. Forest growth is specified with a highly detailed process-based growth specification, and optimization is based on an efficient generalized pattern search algorithm. The optimized variables are rotation length, initial stand density, and the number, intensity, timing, and type of thinnings. The carbon pool includes all aboveground biomass (including dead trees) and timber products. The analysis includes the comparison of different carbon subsidy systems. The results are presented for the most relevant site types and thermal zones in Finland. Carbon storage increases the optimal rotation length, number of thinnings, and initial density at all forest sites. Carbon storage effects on stand density and harvests are strongest at poor sites. Timber output increases with carbon price. High natural mortality in our results implies notable carbon storage in dead trees and a positive contribution to biodiversity. The stand-level analysis is extended to a cost-efficient national-level carbon storage plan.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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 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".