Do citizens value climate change mitigation over biodiversity protection? Exploring citizen support for salt marsh management
Bibliographic record
Abstract
In December 2022, representatives adopted the Kunming-Montreal Global Biodiversity Framework (GBF). The overarching goal of the agreement is to halt biodiversity loss and restore natural ecosystems – and a much-cited target is the “30x30” target of protecting and restoring 30% of Earth by 2030. Salt marshes are highly productive coastal ecosystems relevant for both biodiversity and climate change mitigation but have experienced historical major losses and are among the habitats in need of protection and restoration. Currently, there is little knowledge about how salt marshes are valued from a societal perspective, which has important management implications. This is particularly the case in the Nordic region where awareness of these habitats is low. Using survey data from Norway, Sweden, Finland, Denmark, and Germany, this study contributes understanding how citizens value salt marshes by examining support for different management initiatives framed as contributing to the goal of either biodiversity protection or climate change mitigation. Generally, both respondents primed with information about the importance of salt marshes for biodiversity and for climate change mitigation were supportive of the management initiatives despite having little previous knowledge of salt marshes. For one initiative, respondents who were informed of the importance of salt marshes for biodiversity were slightly more likely to support the management initiative than those informed about the importance of salt marshes for climate change mitigation. Our study provides guidance for assessment of trade-offs from a human valuation perspective, thus supporting policy makers when considering arguments for salt marsh management within the context of the 30x30 targets for protected areas.
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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 | 0.006 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".