Are greenhouse gas fluxes lower from ley or perennial fallow than from arable organic soils? A systematic review protocol
Bibliographic record
Abstract
Abstract Background Cultivated peatlands are widespread in temperate and boreal climate zones. For example, in Europe about 15% of the pristine peatland area have been lost through drainage for agricultural use. When drained, these organic soils are a significant source of greenhouse gas (GHG) emissions. To reach climate goals, the agricultural sector must reduce its GHG emissions, and one measure that has been discussed is changing land use from cropland to ley production or perennial green fallow. This management change leads to lower reported emissions, at least when using the IPCC default emission factors (EF) for croplands and grasslands on organic soils (IPCC 2014). However, there was a limited background dataset available for developing the EFs, and other variables than management affect the comparison of the land use options when the data originates from varying sites and years. Thus, the implications for future policies remain uncertain. This protocol describes the methodology to conduct a systematic review to answer the question of whether ley production or perennial green fallow can be suggested as a valid alternative to annual cropping to decrease GHG emissions on organic soils in temperate and boreal climate. Methods Publications will be searched in different databases and bibliographies of relevant review articles. The comprehensiveness of the search will be tested through a list of benchmark articles identified by the protocol development team. The screening will be performed at title and abstract level and at full text level, including repeatability tests. Eligible populations are organic agricultural soils in temperate and boreal climate regions. Interventions are grasslands without tillage for at least 3 years, and comparators are annual cropping systems within the same study as the intervention. The outcome must be gas fluxes of either carbon dioxide (CO2), nitrous oxide (N2O), or methane (CH4), or any combination of these gases. Studies will go through critical appraisal, checking for internal and external validity, and finally data extraction. If possible, a meta-analysis about the climate impact of perennial green fallow compared to annual cropping on organic soils will be performed.
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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 | 0.075 | 0.109 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.015 | 0.014 |
| Bibliometrics | 0.018 | 0.011 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.007 | 0.004 |
| Insufficient payload (model declined to judge) | 0.072 | 0.010 |
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".