Barriers to enhanced and integrated climate change adaptation and mitigation in Canadian forest management
Bibliographic record
Abstract
Forests are sensitive to the effects of climate change and play a significant role in carbon cycles. This duality has important implications for forest management in terms of requirements for enhanced and integrated adaptation and mitigation interventions. Two ideal conceptual level changes could provide the means for implementation. First, the incorporation of climate change considerations into definitions of sustainable forest management (SFM) would provide mandates for enhanced approaches. Second, the mainstreaming of enhanced SFM would facilitate implementation. There are, however, factors that may impede implementation. Identifying and evaluating these factors informs our understanding of requirements for adaptation and mitigation mainstreaming. This study reviews, organizes, and interprets the literature for the purposes of identifying and evaluating potential impediments. Harmonization barriers pertain to differences between adaptation and mitigation in pre-existing frames and beliefs. Enabling barriers are psychological and institutional in nature. Implementation barriers include capacity deficits (e.g., funding limits, science and knowledge deficits regarding benefits, trade-offs, and synergies between adaptation and mitigation) and governance issues. Barriers are interrelated, dynamic, and subjective. Addressing barriers requires a holistic approach that recognizes the complex and dynamic nature of forest management policy change processes.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".