The Effect of Temporary Certified Emission Reductions on Forest Rotations and Carbon Supply
Bibliographic record
Abstract
This paper examines the effect of the Clean Development Mechanism regulations that create temporary certified emission reductions on harvesting decisions, land use allocation, and the carbon supply in forest plantations. We develop a model that solves the landowner's harvesting decision when revenues from carbon uptake are included. Rotation intervals and carbon credit supply slightly increase. Fast growing tree species with shorter rotation intervals have relatively more inelastic carbon credit supply curves than slow growing tree species with longer rotations. With moderate carbon prices, most carbon sequestration gains originate from the extensive margin through the expansion of forest land, but approximately 22–35% of total carbon sequestered comes from the intensive margin through an increase in rotation intervals. The contribution to carbon sequestration from the intensive margin is more significant as the carbon price increases. Dans le présent article, nous avons examiné les répercussions que les règles du mécanisme pour un développement propre (MDP), qui délivre des unités de réduction certifiée des émissions temporaire (URCEt), ont sur les décisions de récolte, les changements d’utilisation des terres et l’offre de crédit de carbone dans les plantations forestières. Nous avons élaboré un modèle qui aide les propriétaires fonciers à prendre des décisions de récolte lorsque les revenus tirés de la séquestration du carbone sont pris en compte. Les intervalles de rotation et l’offre de crédit de carbone augmentent légèrement. Les essences à croissance rapide exigeant de courts intervalles de rotation ont des courbes d’offre de crédit de carbone relativement plus inélastiques que les essences à croissance lente exigeant de longs intervalles de rotation. Compte tenu des prix modérés du carbone, la plupart des gains tirés de la séquestration du carbone proviennent de la marge extensive associée à l’expansion des terres forestières, bien que près de 22 à 35 p. 100 de la quantité totale de carbone séquestré proviennent de la marge intensive associée à une augmentation des intervalles de rotation. La participation à la séquestration du carbone à partir de la marge intensive devient plus importante à mesure que le prix du carbone augmente.
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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) | 0.000 | 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".