Integrating climate change adaptation and mitigation objectives in British Columbia's forests
Bibliographic record
Abstract
Climate change mitigation and adaptation objectives have usually been treated separately in policies and interventions addressing climate change in the forests. However, increasing efforts have been directed towards the joint consideration of adaptation and mitigation objectives during the design of forest management interventions and policy. Not only are both climate objectives often compatible, but they also sometimes display synergies so that their combined effect is greater than the sum of their effects if implemented separately. Despite this potential, very few integrative initiatives have been attempted in practice. We use the case of the Canadian province of British Columbia (BC) to better understand the relationship between climate change adaptation and mitigation policy in the forests. Drawing on the review of existing forest management policy and a survey and semi-structured interviews with BC government officials, we address two major research objectives: (1) To what extent do current climate and non-climate BC forest management policies effectively integrate adaptation and mitigation objectives? (2) What challenges and opportunities are associated with the joint consideration of both objectives when developing forest management interventions and policy? Our results highlight the potential positive and/or negative ecological (e g., ecosystem resilience. biodiversity). economic (e.g., cost or profitability) and social (e.g., effect on livelihood) outcomes of considering both adaptation and mitigation objectives together during the design of forest management interventions. We also provide policy insights into when and how to consider mitigation and adaptation together and to successfully mainstream both objectives into climate and non-climate forest management policies.
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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 | 0.001 |
| 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 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".