Afforesting Icelandic land: A promising approach for climate-smart forestry?
Bibliographic record
Abstract
Climate-smart forestry (CSF) is considered a promising approach for climate change adaptation and mitigation strategies, as highlighted in several European policy documents. This paper describes a prospective approach to introducing an incentive-based scheme to facilitate the implementation of CSF through a case study in Iceland. It is argued that the payments for ecosystem services (PES) scheme allows for effective CSF management and long-term sustainability if introduced in compliance with local, cultural, and social values. In a case study of an Icelandic afforestation programme, we conducted an institutional analysis of the PES scheme and assessed its effect on the sustainable provision of forest ecosystem services for the long term. We provide preliminary findings on the application of CSF in the 30-year-old Icelandic afforestation programme scheme. The perspectives of forest and policy experts, as well as local farmers participating in the scheme, were crucial for assessing the effectiveness of PES scheme performance in Iceland.
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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 | 0.002 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".