Wet peatland utilisation for climate protection – An international survey of paludiculture innovation
Bibliographic record
Abstract
Drainage-base agriculture and forestry are key drivers of emissions from degraded peatlands. An important challenge of climate-oriented peatland management is an improved conservation of their huge carbon stocks. Paludiculture, the productive use of wet peatlands, is a promising land use alternative that reduces greenhouse gas emissions substantially since it requires rewetting of peatlands. As rewetting is accompanied by productive use, it offers a sustainability innovation for farmers and other land users. There is an emerging knowledge base on paludiculture but no empirical study of paludiculture and its diffusion as an international innovation. The paper closes this research gap presenting the results of a survey of paludiculture projects in a variety of global contexts. It shows paludiculture to be an emerging, science-driven and collaborative innovation that faces adverse path-dependency from drained peatland exploitation. There is a diversity of paludicultures for fuel, fodder, horticultural substrate and construction material, but these are rarely directly commercially viable. A third of initiatives see themselves in continuity with traditional but often marginalized uses of peatlands. Paludiculture is a complex, critical sustainability innovation mission calling for a multiple-objective strategy and a sustainability-oriented form of governance. As biomass from paludiculture per se can almost never compete with dryland alternatives, we recommend i) to initiate and sustain large-scale programmes to develop products that exploit the unique properties of wetland plants across market, public and communal uses, ii) to develop integrative concepts for payments for ecosystem services associated with wet peatlands, iii) a complementary focus on ending subsidies and policy support for drainage-based peatland use, as well as iv) inclusive stakeholder involvement from the start as well as sustained policy support to foster paludiculture as the productive niche within a culture of living sustainably with peatlands.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".